Huazhong University of Science and Technology (HUST) is welcoming students from Oxford University to take part in research internships in Wuhan, China. This year, HUST offers 25 projects, including 30 positions in total, which provide interns with challenging and meaningful internship experiences and Chinese cultural immersion classes over the summer.

The duration of 2024 Summer internship program is from the later June to the beginning of August, 2024. The 25 projects are:

² Internship in Scientific Research

①China-EU Institute for Clean and Renewable Energy

#1 Prof. Hu Song’s research team (Positions: 1-2)

#2 Associate Researcher Li Huayao’s research team (Positions: 1-2)

#3 Prof. Yang Qing’s research team (Position: 1)

#4 Prof. Yang Qing’s research team (Position: 1)

#5 Prof. Chen Rong’s research team (Positions: 1-2)

#6 Prof. Luo Cong’s research team (Positions: 1-2)

#7 Prof. Yang Jun’s research team (Positions: 1-2)

#8 Prof. Guo Limin’s research team (Position: 1)

#9 Prof. Guo Limin’s research team (Position: 1)

#10 Prof. Chen Huanxin’s research team (Positions: 1-2)

#11 Prof. Zhao Yongchun’s research team (Position: 1)

②Wuhan National High Magnetic Field Center

#1 Prof. Zhu Zengwei’s research team (Position: 1)

#2 Prof. Xin Guoqing’s research team (Position: 1)

#3 Prof. Li Jing’s research team (Position: 1)

③Wuhan National Laboratory for Optoelectronics

#1 Prof. Tang Jiang’s research team (Position: 1)

#2 Prof. Lu Peixiang’s research team (Position: 1)

#3 Prof. Wang Jian’s research team (Position: 1)

④School of Electronic Information and Communications

#1 Prof. Yang Peng’s research team (Position: 1)

#2 Prof. Liu Qiong and Prof. Yang You’s research team (Position: 1)

² Internship in Chinese law, Chinese governance, and Chinese Economy

①School of law

#1 Prof. Wang Xigen’s research team (Position: 1)

②College of Public Administration

#1 Prof. Zhang Yi’s research team (Position: 1)

#2 Prof. Seah Shuo’s research team (Position: 1)

③School of Economics

#1 Prof. Peng Bin’s research team (Position: 1)

#2 Prof. Sun Ya’s research team (Position: 1)

#3 Prof. Ye Jinqi’s research team (Position: 1)

This year marks the 10th anniversary of "HUST-Oxford" Summer Internship Program and the University of Oxford specially built up the webpage to celebrate the partnership between two universities: https://www.careers.ox.ac.uk/article/10-years-of-internships-at-hust 

HUST also specifically produced a commemorative video for celebrating the 10th anniversary of "HUST-OXFORD" Summer Internship Program: http://iso.hust.edu.cn/info/1240/4483.htm 

Besides, please feel free to watch our promotional video for hands-on information of HUST campus views, scientific strength, and internship details: http://discover.hust.edu.cn/fore/courses/courseDetail.do?sid=22110110195012811716642

² Internship in Scientific Research

①China-EU Institute for Clean and Renewable Energy

#1 Prof. Hu Song’s research team (Positions: 1-2)

Introduction to the project (lab):

This project provides new ideas on the utilization of multi-energy and treatment of typical solid wastes (waste tire and waste fan blade). As is known to all, the production of solid wastes has been growing as the industry development, and would lead to serious pollutions to the environment if they are not treated improperly. However, solid wastes such as waste tire, waste fan blade and son on are still important resources. Thus, if these solid wastes can be treated to prepare high-value products, the industry can be better developed and the environment can be promoted to be green.

Is there a way to comprehensively utilize multi-energy to treat waste tire and waste fan blade to obtain high-grade energy chemicals? Our team-ICCST (Institute of Clean Combustion Science and Technology) has achieved treatments of waste tire to prepare high-content limonene and waste tire to prepare high-concentration bisphenol A by innovating pyrolysis technology. Besides, we also revealed corresponding mechanisms in treatment of wastes and preparations of high-value chemicals as shown below.

The current research results show that the technology has exciting application potential. In order to further promote the application, we need to carry out more necessary assessments on economics and environments to determine the accurate market positioning. This is a very meaningful and fun project.

This project is supported by National Natural Science Foundation of China (NSFC) (No. 52076097). Sufficient funds and measures can ensure the successful and safe promotion of the project. We are a very international team and own rich experience in guiding exchange students. We have received 9 Oxford students and 13 international students have been working in the research group. We sincerely welcome students interested in energy and waste treatment.

This lab provides excellent experimental system in clean and advanced environment, some typical photos are shown below.

Project Aims:  

This internship project aims to investigate the application prospect of the synergistic utilization of multi-energy and treatment of solid wastes (waste tire and waste fan blade) in China, including experimental results analysis, economic analysis and environment impact analysis. In other words, it is to match technology and market through research, data acquisition and computational analysis.

Of course, we also provide technical research posts, and abundant scientific research instruments will be fully open to you. We can witness how waste tire or fan blade are converted into gas, oil and char. Also, the useful chemicals can be prepared and recovered.

We will cultivate the basic knowledge of energy and resources, the basic principles of new thermal conversion technology, and the basic process of technology transformation. At the same time, we will also organize the investigation of the resources and environment around Wuhan.

Methods:

This project applies the methods of laboratory visit, experiment observation, data research, process model establishment, computer simulation, data analysis, etc.

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of experiments conduction and processes.

2. Learning the data acquisition, collection and analysis.

3. A skill in usage of ASPEN and OPEN LCA soft wares to conduct research.

4. An ability in paper writing and oral presentation.

Project summary

This project is significant for the utilization of multi-energy to treat waste tire and fan blade. The research accords with the energy conversion technology development and high-value treatment of solid wastes, and the students can learn more with the project.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the fields of energy utilization, waste treatment, thermal conversion technology and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly energy, chemistry, physics, mathematics and so on.

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#2 Associate Researcher Li Huayao’s research team (Positions: 1-2)

Introduction to the project (lab):

1. Background of the project.

Artificial olfaction, also known as machine olfaction or electronic nose technology, refers to the creation of systems that mimic the human sense of smell using electronic sensors and pattern recognition algorithms. Much like how our sense of smell works through detecting and recognizing different odors, artificial olfaction aims to replicate this capability using technology.

These systems typically consist of an array of chemical sensors that can detect and analyze the volatile compounds present in odors. The sensors respond to the chemical components in the air and produce signals that are then processed and analyzed by machine learning algorithms or pattern recognition techniques. This analysis helps identify and characterize different odors or chemical compositions.

Applications for artificial olfaction are diverse and growing. They are used in industries such as food and beverage, environmental monitoring, healthcare, agriculture, and even security. For instance, electronic noses can be employed to assess food quality, detect spoilage, identify specific substances or gases in the environment, diagnose diseases based on breath analysis, or even detect explosives or drugs in security scenarios.

The ongoing development of this technology aims to enhance its sensitivity, accuracy, and versatility, allowing it to perform increasingly complex olfactory tasks, contributing significantly to various fields by leveraging the power of machine-based smell detection and identification.

2. The content of the project

(1) Nanomaterial design and synthesis

(2) MEMS-type sensor fabrication

(3) Deep learning algorithms design

(4) Electronic nose assembly and application

Project Aims:  

The aim of this project is to realize the smart artificial olfactory system, and its application in the environment monitoring and exhaled breath analysis.

Methods:

1. Material synthesis and characterization

2. Device simulation and fabrication

3. Algorithm design (by Python)

4. Data analysis (by Python and SPSS)

Learning outcomes:

By the end of this project interns should have gained:

5. An ability in logical thinking and systematic design

6. An ability in material synthesis, device fabrication and data analysis

Project summary

This project focuses on the realization of artificial olfactory, including material synthesis (chemical synthesis), device fabrication (MEMS technology), algorithm design (Python) and data analysis (SPSS or Python), and application in environment monitoring and breath analysis.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of materials, semiconductor device, or algorithm and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly (chemistry, semiconductor physics or computer science).

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#3 Prof. Yang Qing’s research team (Position: 1)

Introduction to the project (lab):

The Energy and Economics lab mainly focuses on study of energy system, climate change, resources and environment, and their interactions. The lab has formed a multi-disciplinary talent team covering energy system modeling utilizing big data and artificial intelligence methods, Life Cycle Assessment (LCA), renewable energy potential evaluation, environmental and economic impacts analysis, etc., and has accumulated sufficient experience and strength. The team has carried out a series of pioneering work in the field of carbon footprint calculation, energy system transformation pathway design, etc. The team has completed a number of national key scientific research projects and published more than 100 SCI papers in high-level academic journals, including PNAS and Nature Communications.

The project we are currently working on is the environmental impact assessment of renewable energy, especially photovoltaic solar energy generation units. We focus on the impacts of renewable energy development on the environment in China, and its feedback on carbon emissions.

Project Aims:  

The aim of this intern project is to realize evaluation of renewable energy development impacts on the environment in China, mainly focusing on solar energy. The project may reveal the relationship between the fast renewable energy development and environmental consequences, and would provide suggestion for policy makers to rationally design the development pathway of renewables.

Methods:

1. Geographic Information System (GIS)

2. Remote sensing (RS)

3. Python programming

4. Machine learning algorithms, mainly image classification and recognition

5. Cloud computing platform, mainly Google Earth Engine

Learning outcomes:

By the end of this project interns should have gained:

1. An ability in using GIS software

2. A deeper understanding of cloud computing platforms such as Google Earth Engine

3. An ability in reading and writing Python programs

4. An ability in scientific paper reading and writing

Project summary

Development of renewables is important to achieve net-zero emission goal and mitigate climate change impacts. However, construction of renewable energy generation units will also lead to various negative environmental impacts, including influence on biodiversity, food security and water scarcity. Thus, it is urgently needed to quantify the impacts of renewable energy development on the environment.

The project mainly focuses on evaluating carbon footprints of photovoltaic solar energy generation units in China, it will try to identify the carbon-emission-related characteristics of commercial-scale solar energy generation units in China via remote sensing images, and then quantify the environmental impacts of these currently installed commercial solar units, giving policy makers an overall view on the rapid development and constructions of solar farms and their environmental impact.

All interns having basic knowledge about renewables and interest in GIS, machine learning (image recognition), cloud computing and Python programming are welcomed to participate in the project. Looking forward to you joining!

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of renewables and environment interactions and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly renewable energy and machine learning.

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#4 Prof. Yang Qing’s research team (Position: 1)

Introduction to the project (lab):

The Energy and Economics lab mainly focuses on study of energy system, climate change, resources and environment, and their interactions. The lab has formed a multi-disciplinary talent team covering energy system modeling, Life Cycle Assessment (LCA), renewable energy potential evaluation, environmental impacts analysis, etc., and has accumulated sufficient experience and strength. The team has carried out a series of pioneering work in the field of carbon footprint calculation, energy system transformation pathway design, etc. The team has completed a number of national key scientific research projects and published more than 100 SCI papers in high-level academic journals, including PNAS and Nature Communication.

The project we are currently working on is the environmental impact assessment of renewable energy. We focus on the impacts of renewable energy development on the environment in China, and its feedback on climate change.

Project Aims:  

This project aims to assess the impact of environmental conditions on renewable energy generation, mainly focusing on wind power and solar energy. The project may reveal the relationship between renewable energy development and environmental changes, and would provide suggestion for policy makers to rationally design the development pathway of renewables.

Methods:

This project applies the methods of Geographic Information System (GIS), Remote sensing (RS), Python programming, Life Cycle Assessment (LCA).

Learning outcomes:

By the end of this project interns should have gained:

1. An ability in using GIS software

2. An ability in performing LCA analysis

3. An ability in reading Python programs

4. An ability in scientific paper writing

Project summary

Developing renewable energy is important to achieving net-zero emissions targets and mitigating the effects of climate change. However, renewable energy is also affected by the environment. Changes in environmental conditions (such as wind speed and solar radiation) can cause instability in renewable energy. This instability restricts the development of renewable energy to a certain extent, so an evaluation index system is urgently needed to evaluate the impact of environmental conditions on renewable energy.

The project focuses primarily on assessing the impact of changes in meteorological conditions on wind and solar energy in China, as well as carbon emissions from renewable energy construction. The project will attempt to evaluate the performance of Chinese wind and solar power plants under different conditions from multiple indicators, then quantify the impact of environmental conditions on wind and solar power plants, and predict their future power on a time scale through machine learning.

All interns with a basic understanding of renewable energy and an interest in GIS, Python machine learning, and LCA are welcome to join the project. We look forward to your joining!

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of renewables and environment interaction evaluation and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly renewables.

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#5 Prof. Chen Rong’s research team (Positions: 1-2)

Introduction to the project (lab):

This laboratory is actively involved in cutting-edge and interdisciplinary research within the realm of micro/nano manufacturing. Our primary research focus encompasses the exploration of nanomaterials, nano devices, and their associated processes. Moreover, our aim is to leverage these advancements to address the impending challenges in the fields of energy and electronics. One noteworthy development is the establishment and broadening of the selective atomic layer deposition method. This innovative approach has been extended into the domain of green energy catalysis, contributing to the development of crucial catalysts for emerging energy technologies and environmental governance solutions. Substantial progress has been achieved in pivotal technologies such as hydrogen fuel cells and solar cells, marking a series of notable accomplishments.

Project Aims:  

The objective of this project is to pioneer a robust technology for coating high-energy particles and precious metal nanoparticles, utilizing atomic layer deposition technology as the foundation. The primary emphasis is on crafting efficient precious metal catalysts tailored for hydrogen fuel cells. The ultimate goal is to minimize the reliance on precious metals in hydrogen fuel cells, thus optimizing their performance. Additionally, the project delves into the exploration of advanced preparation techniques for functional thin films specifically designed for solar cells.

Methods:

1. Research on the preparation technology of high-efficiency precious metal catalysts for hydrogen fuel cells based on micro/nano particle atomic layer deposition technology, to achieve the reduction of precious metals in hydrogen fuel cells.

2. Research on the preparation technology of functional thin films in solar cells based on micro/nano particle atomic layer deposition.

Learning outcomes:

By the end of this project interns should have gained:

7. Deep understanding of the application of micro/nano particle atomic layer deposition technology in hydrogen fuel cells and perovskite solar cells.

8. Proficiency in surface coating technology for lithium batteries and hydrogen fuel cells using micro/nano particle atomic layer deposition, coupled with expertise in the preparation of functional thin films for perovskite solar cells.

Project summary

This project developed a stable high-energy particle and precious metal nanoparticle coating based on atomic layer deposition technology, focusing on the preparation technology of high-efficiency precious metal catalysts for hydrogen fuel cells, achieving the reduction of precious metals in hydrogen fuel cells, and research the preparation technology of functional thin films for solar cells.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

Prof. Chen obtained her Master and PhD degrees from Stanford University in 2006. Before she joined HUST as a full professor in 2011, she was a senior research scientist in Intel Labs and Applied Materials, Inc.

Prof. Chen is engaged in the frontier and cross fields of micro/nano manufacturing. The research direction mainly includes atomic layer deposition methods, processes and equipment and expanded to the fields of green energy catalysis, including the development of key catalysts in new energy technologies and environmental governance technologies. And a series of outstanding achievements have been made in key technologies such as hydrogen fuel cells and solar cells.

We are interested in the undergraduate interns.

The interns should have an interest in and study the basic knowledge about a range of fields, particularly in fuel cells and solar cells.

No matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#6 Prof. Luo Cong’s research team (Positions: 1-2)

Introduction to the project (lab):

1. Background of the project. This project will focus on CO₂ capture and utilization technologies.

2. The content of project is to learn knowledge about capture and utilization of carbon dioxide, including adsorbent technology, chemical looping, oxygen-enriched combustion, CO₂ conversion and utilization, etc. Besides, we will have a visit to 3MW oxy-fuel combustion facility for CO₂ capture.

Project Aims:  

The aim of this project is to realize the issue of Global Warming and Greenhouse Effect by controlling carbon dioxide emissions.

Methods:

Experimental and simulation works in developing carbon capture and utilization technologies, including the design of CO₂ sorbent, solvent, and oxygen carriers, operation of lab-scale bench tests.

Learning outcomes:

By the end of this project interns should have gained:

1. Understanding of carbon capture and utilization technologies

2. Learning the CO₂ capture demonstration projects in China

Project summary

This project is to report on the progress in CO₂ capture and utilization in China.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns. Students from Singapore, Malaysia, Thailand, China, as well as those who love Chinese cultures, are highly expected, and we will organize additional tours in or around Wuhan city in one weekend.

The interns should have an interest in the field of CO₂ capture and utilization, and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly chemical engineering, mechanical engineering, and so on.

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#7 Prof. Yang Jun’s research team (Positions: 1-2)

Introduction to the project (lab):

The background of project:

Renewable energy is clean and low-carbon, and both nuclear and renewable energy are expected to contribute for the low-carbon environment. It becomes interesting to establish a coupling system of nuclear energy and renewable energy as well as energy storage with intelligent control. Many studies have been carried out on the coupling of nuclear energy, renewable energy and energy storage.

The contents of project:

To investigate various kinds of coupled energy system and particularly demonstrate the operation mechanism of an idea design of a nuclear power plant coupled with energy storage system.

Project Aims:  

This project provides an opportunity to build a simple numerical model to investigate and show the operation mechanism of an innovation design of coupled energy system.

Methods:

This project requires to establish a numerical model, with MATLAB or other tools, to reflect the operation of innovation design of energy coupled system.

Learning outcomes:

By the end of this project interns should have gained:

1. Understanding the idea of coupled energy systems.

2. An ability in using some multi-dimensional software to do basic 2D or 3D design.

3. An ability in programming to perform fundamental heat and energy transfer related calculation.

Project summary

This project is a training to study and establish a simple demonstration model to show the operation mechanism of a coupled energy system.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of energy system (undergraduate) and have already demonstrated strong research potential (graduate).

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly thermodynamics, heat transfer and so on (undergraduate).

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

Basic understanding of AUTOCAD, SolidWorks is a plus. Basic programming skill with MALAB, Python or C/C++ is preferable.

#8 Prof. Guo Limin’s research team (Position: 1)

Introduction to the project (lab):

The VOCs are one of the main air pollutants in China and results in haze and high ozone level in the urban area. This project will offer the opportunity to understand the research for volatile organic compounds (VOCs) abatement by catalytic combustion. From the catalyst preparation, microstructure/surface property characterization to catalytic performance evaluation, the student can devote to the whole research process for the catalytic combustion abatement of VOCs. In addition, the site visit on the company can be offered depending on the situation in order to further understand the practical solution for VOCs abatement in China.

Project Aims:

The aims of this project are to design and synthesize effective catalysts for VOCs abatement, including catalyst preparation, catalyst characterization and their catalytic activity evaluation.

Methods:

This project applies the methods including:

1. Catalyst preparation: Hydrothermal, Sol-gel and so on;

2. Catalyst characterization: XRD, H2-TPR, O₂-TPD, SEM and so on;

3. Catalytic activity evaluation: the fixed-bed reactor.

Learning outcomes:

After this project interns, the student can learn:

1. A very good chance to understand the air pollution control in China

2. An ability in catalyst preparation.

3. An ability in catalyst characterization.

4. An ability in catalytic activity evaluation

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of industrial catalysis, especially in air pollution control (undergraduate) and have already demonstrated strong research potential (graduate).

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly chemistry, nanomaterials and so on (undergraduate).

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#9 Prof. Guo Limin’s research team (Position: 1)

Introduction to the project (lab):

This project provides a scheme of CO₂ catalytic conversion. CO₂ has attracted a lot of attention over the last 20 years due to the link between the increases in CO₂ emissions with the rise in global temperatures and especially recently high motivation for carbon neutral society scenarios (2050 for EU and Japan; 2060 for China). Rather than viewing the CO₂ as a waste material, the conversion of CO₂ to value added products, such as methane, methanol, ethanol, olefin and other hydrocarbons, has attracted much attention.

Project Aims:

The aims of this project are to catalyze CO₂ to methanol. By the means of catalytic pathway design and catalysts synthesize to achieve the high activity and selectivity. Moreover, our lab also aims at better understanding CO₂ activation and catalytic mechanism by using variety of characterization methods.

Methods:

This project applies the methods including:

-catalyst preparation

-catalyst characterization: XRD, SEM, TEM, In-Situ DRIFTS measurements etc.

-catalytic activity measurements

Learning outcomes:

By the end of this project interns, the student can learn:

1. An ability in catalyst preparation.

2. An ability in catalyst characterization.

3. An ability in catalytic activity measurements.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of chemistry (undergraduate) and have already demonstrated strong research potential (graduate).

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly chemistry, nanomaterials, photovoltaics and so on (undergraduate).

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#10 Prof. Chen Huanxin’s research team (Positions: 1-2)

Introduction to the project (lab):

1. Background of the project.

This project will focus on the hot issue of high energy consumption of building HVAC systems. In the building system, the energy consumption of Heating, Ventilation and Air Conditioning (HVAC) system accounts for 40%-60% of the energy consumption of the whole building system. Therefore, it is of great significance to construct an energy consumption prediction model for the internal air conditioning system of the building and realize high precision energy consumption prediction.

In recent years, with the development of technologies such as the Internet of Things, the measured data collection level of HVAC system is constantly improving, but there are still problems such as data quality that limit the development of energy consumption prediction. At the same time, in 2021, the Ministry of Housing and Urban-Rural Development issued a document pointing out that it is necessary to promote intelligent production, promote intelligent construction, develop digital design, build Internet platforms for the construction industry and accelerate the digital transformation and upgrading of the construction industry. Therefore, it is worth studying how to improve energy consumption prediction effect, promote energy conservation and carbon reduction of buildings and improve energy efficiency of buildings based on new digital technologies such as big data and artificial intelligence under existing deficiencies.

Therefore, this project will take building HVAC system as the research object, develop energy consumption prediction model, effectively analyze its energy performance and energy saving potential, and control building operation mode, improve energy utilization efficiency and reduce energy consumption and carbon emissions.

2. The content of project.

To develop building HVAC energy consumption prediction system, it is necessary to integrate geometeorological information and building operation information, collect the operation data of HVAC system, display the operating status of equipment in real time, and carry out automatic analysis and information feedback. The project needs to achieve two important functions:

1) Detect abnormal running state of HVAC system and provide warning.

2) Real-time collection and prediction of energy consumption data of building HVAC system.

An energy consumption forecasting system need to be established from four aspects: data acquisition, data calculation, data display and data application. Data acquisition is when sensors of HVAC systems and equipment send real-time data to computing servers via the Internet of Things according to specified communication protocols. Data calculation is to use big data analysis method and machine learning algorithm to analyze real-time data and give results, such as abnormal alarm information, energy consumption distribution information, energy consumption prediction results, optimization control signals, etc. For example, real-time monitoring of HVAC system, abnormal alarm and record, equipment asset information, energy consumption prediction results, energy saving and optimization control history, comprehensive statistical analysis report, etc. Data display is the display of all information from the system in the form of charts, tables and graphs, etc. Data application refers to the evaluation of future energy saving measures or other improvement plans by managers or decision makers based on available information.

To achieve above goal, the interns will be provided with real data collected form HVAC in commercial buildings. This internship also provides the opportunity to visit and learn from the cooling plant commercial buildings, and guidance about how to apply data-driven for application purpose in HVAC systems will be also provided.

Project Aims:  

This internship project aims to develop energy consumption prediction model of building HVAC system, realize data acquisition and transmission, and carry out real-time monitoring and control of system operation and energy consumption. At the same time, when system abnormalities and excessive energy consumption are found and demand side responds to demand, timely warning and control can be achieved, and real-time energy consumption prediction can be made to predict short-term energy consumption with high precision.

Methods:

1. The operation and maintenance system software of this project is mainly written as Python and R language.

2. The visual design of vehicle and subway station structures in this project can be done by using SketchUp, EnergyPlus and Autodesk Revit software.

3. The object of this project is building HVAC system, and the main method is big data analysis. Therefore, big data analysis and machine learning algorithm are used widely in this project.

4. The air conditioning equipment data and communication protocol will be provided. Energy consumption prediction methods will be trained and guided by our research group.

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of building HVAC system.

2. Learning the real cooling system of commercial building.

3. Deep understanding of how to apply big data analysis and artificial intelligence method into energy consumption prediction system.

4. An ability in programming based on python and R language.

5. An ability in designing energy prediction model of building HVAC system based on Sketchup, EnergyPlus and Autodesk Revit software.

Project summary

The intelligent operation and maintenance system of building air conditioning system is meaningful and significant for energy saving. The project will be interesting for interns, and we are looking forward to your joining.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of big data analysis, machine learning, smart city, intelligent operation and maintenance of HVAC systems and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly mechanical equipment, heating, ventilation and air condition system, programming, big data analysis.

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#11 Prof. Zhao Yongchun’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

This project will focus on photocatalytic CO₂ reduction. CO₂ actively responds to the energy crisis and greenhouse effect. Driven by the sunlight, the technology of photocatalytic CO₂ reduction could converse CO₂ into renewable hydrocarbon fuel under mild reaction conditions.

2. The content of project is learning the methods of catalyst synthesis, characterization, experimental design and data analysis.

Project Aims:  

This internship project aims to develop new and efficient photocatalyst for photocatalytic CO₂ reduction, design new photocatalytic conversion pathways for CO₂, and reveal the mechanism for photocatalytic CO₂ reduction.

Methods:

1. Catalyst synthesis

2. In-situ characterization

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of the technology of photocatalytic CO₂ reduction.

2. Learning the methods of materials synthesis.

3. An ability in material characterization and data analysis.

Project summary

This project is advanced materials synthesis for photocatalytic CO₂ reduction and mechanism unveiling.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in the undergraduate interns.

The interns should have an interest in the field of photocatalysis and have already demonstrated strong research potential.

In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly chemistry, nanomaterials.

It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

②Wuhan National High Magnetic Field Center

#1 Prof. Zhu Zengwei’s research team (Position: 1)

Introduction to the project (lab):

Background of the project.

This project will focus on transverse thermal transport on topological materials.

1. The Nernst effect refers to the generation of an electric field perpendicular to both the temperature gradient and the magnetic field when a temperature gradient is applied in the presence of a magnetic field. This effect is used to detect magnetic vortices in superconductors, as well as to study the topological properties of materials.

2. In topological materials with a topological band structure which means that their electronic states cannot be smoothly deformed into a band without topological defects., the Nernst effect is closely related to the topology of the band structure, and its temperature dependence and field dependence have attracted much attention. This effect has also been proposed as a way to detect topological phase transitions and to study the topological properties of materials and also anomalous Nernst effect can directly detect the topological properties.

Nernst effect in topological materials has potential applications in the fields of spintronics, superconductivity, and topological phase transitions, providing new opportunities for exploring new physical phenomena and developing new devices.

Project Aims:

The internship project aims to measure the Nernst effect on a known topological material, gather data, and analyze how the topological properties impact the Nernst effect.

Methods:

1. Measuring Nernst effect

2. Change temperature and magnetic field

3. The results will be compared to those obtained from other topological materials.

Learning outcomes:

By the end of this project interns should have gained:

1. A deep understanding of topological materials.

2. Knowledge of thermal transport

3. The ability to work with electric and thermal transport as well as data analysis.

Project summary

This project involves cutting-edge research on topological materials, with the Nernst effect serving as an effective method for studying topological properties.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of experimental physics and have already demonstrated strong research potential.

3. In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly condense matter physics, quantum materials.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#2 Prof. Xin Guoqing’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

This project will focus on nanoelectronics fabrication. In the post-Moore Era, Transition metal dichalcogenides (TMDs) shows great potentials to replace Silicon materials for the nanoelectronics fabrication. Devices built up with TMDs show much superior electrical and optical performance, with potentials to further reduce the size of device and enhance the data density and processing capability.

2. The content of project is learning the methods of catalyst synthesis, characterization, Experimental design and data analysis.

Project Aims:

This internship project aims to develop new transition metal dichalcogenides materials, design new device structure, fabricate nanoscale devices and reveal the working mechanism of the device.

Methods:

1. Semiconductor fabrication process

2. Electrical characterization and data analysis

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of the transition metal dichalcogenides materials.

2. Learning the semiconductor fabrication process.

3. An ability in device characterization and data analysis.

Project summary

This project focuses on nanoscale devices fabrication and working mechanism understanding.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of semiconductor nanoelectronics and have already demonstrated strong research potential.

3. In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly semiconductor physics, electronics, nanomaterials.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#3 Prof. Li Jing’s research team (Position: 1)

Introduction to the project (lab):

1. Introduction of the lab.

We are an experimental condensed matter physics group, and we’re mostly interested in probing and understanding the behavior of electrons. When there’re lots and lots of electrons, the collective behavior of them may cause very exotic physical phenomena such as superconductivity, charge density wave, etc., and when there’re only a few of them, their behavior is dominated by quantum mechanics, where discrete and quantized physical properties are expected. The behavior of electrons determines the “personality” of electronic materials, and how to understand and control the behavior of electrons in novel materials is the key to the prosperity of modern era of electronic devices. In our lab, we study a class of materials called 2D van der Waals materials, consisting only one or a few layers of atoms. These materials cover a wide range of novel physical properties, and they push the size limit of modern electronic devices to the extreme. We stack different materials together like assembling LEGO blocks, and employ the state-of-the-art nanofabrication techniques to define them into micro- to nanoscale devices. As physicists, we like to cool the devices down to temperature close to absolute zero, and we use electrical transport and optics techniques to create and probe very exotic electronic states.

2. The content of this project is learning the methods of staking the “LEGO blocks” of 2D van der Waals semiconductors to form heterostructures onto a single mode fiber-top, and probing the rich correlated electronic states in these devices using one of the world’s strongest magnet at Wuhan National High Magnetic Field Center.

Project Aims:

This internship project aims to develop new and efficient 2D van der Waals micro device fabrication techniques onto single fiber-tops, to design and modify optical-electrical sample probes used for pulsed magnetic field experiments, and to carry out magneto-optical measurements in pulsed magnetic field.

Methods:

1. van der Waals materials exfoliation and dry transfer technique

2. nano fabrication techniques

3. low temperature and optics techniques

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of the physics in 2D van der Waals semiconductors.

2. Learning the methods of micro-device fabrications.

3. Learning low temperature and optics techniques.

Project summary

This project is designed for those who want to gain experience in advanced skills of 2D van der Waals materials synthesis, nano- and micro-device fabrication, and low temperature physics.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in undergraduate interns.

2. The intern should have a background in one of the following fields: Physics, Material Science, Electronic Engineering or related subjects.

3. The intern should be willing to perform hands-on work, and is willing to learn, develop and share new techniques.

4. The working language can be English for non-Chinese speakers.

③Wuhan National Laboratory for Optoelectronics

#1 Prof. Tang Jiang’s research team (Position: 1)

Introduction to the project (lab):

Study on High Efficiency Tandem Perovskite Solar Cells

Extensive research on perovskite-based photovoltaics (PV) over the past decade led to rapid development, with power conversion efficiencies (PCEs) exceeding 25.2% being realized. Hybrid organic–inorganic metal halide perovskite semiconductors continue to attract enormous attention due to their exceptional optoelectronic properties, such as their high absorption coefficients, high carrier mobilities, and low recombination rates. The widely tunable band gap of these perovskites by compositional variations of the halide anion in the perovskite crystal structure allows strong light absorption in a broad spectral range. With their low material costs and a wide range of possible deposition techniques, perovskites qualify as promising candidates for next-generation multi-junction PV. Moreover, combined with established PV technologies, like wafer-based silicon or copper indium gallium selenide films, perovskite-based tandems are currently the most promising technology for terrestrial PV to enable PCEs exceeding the single-junction Shockley-Queisser limit.

The recent development in perovskite PV has been largely underpinned by advances in the composition and morphology of the perovskite absorber layer as well as progress in device architectures by employing passivation layers and optimizing hole and electron transport layers (HTLs and ETLs). Nevertheless, fundamental challenges, such as the toxicity of lead-based perovskites, the limited stabilities of the various layers-such as the perovskite absorber, charge trans-port layers (CTL), and combinations thereof-in terms of moisture, light, and heat stress remain to be solved. One promising route to cope the stability of the devices is via the replacement of organic CTLs with inorganic counterparts. In this regard, the HTLs, copper iodide (CuI), copper thiocyanate (CuSNC), and nickel oxide (NiOx) have been shown to promise good intrinsic chemical stability compared to the commonly used organic HTL spiro-OMeTAD. In addition, ETLs like zinc oxide (ZnO), tin oxide (SnO2), and mesoporous titanium dioxide (TiO2) are known to be intrinsically stable and have been demonstrated to result in highly efficient and stable perovskite solar cells.

However, conventional methods for layer deposition significantly limits the choice of materials, deposition techniques, and device architectures, due to solvent incompatibilities or process-induced damage of underlying layers during vacuum-based physical vapor deposition (PVD) and chemical vapor deposition (CVD) processes. Whereas the CTL under the perovskite must be robust against the perovskite deposition, many polar solvents have to be avoided for the layers, which are solution-processed on top of the perovskite to prevent decomposition or degradation. Similarly, high temperatures, radicals, and ion bombardment must be limited due to the possible damage of the underlying layers during PVD and CVD techniques such as sputtering, atomic layer deposition, or electron-beam evaporation. In this regard, metal-oxide or fullerene-based buffer layers are usually employed that protect the underlying absorber layer. Therefore, not every combination of ETL and HTL is accessible in a straightforward manner.

In this project, we will vigorously develop the technology of laminated perovskite solar cells.

Introduction of the Lab

Our research group, Optoelectronic Devices and 3D Integration Team (ODTI), was founded in May 2012, mainly focusing on the research of new photoelectric conversion materials and devices, hoping to do the basic research with new ideas in science and promising technology, in order to live up to the taxpayers’ money and the time of students and teachers. The research group attaches importance to students’ basic scientific research skills, emphasizes all-round development, advocates student-oriented management philosophy, and strives to create a happy and comfortable environment for scientific research and experiment. We sincerely invite students with passion and pursuit for scientific research to join us. Those with photoelectric physics and materials chemistry background are welcome.

The leader of ODTI is Professor Tang Jiang, Dean of the School of Optics and Electronic Information, Huazhong University of Science and Technology, and Deputy Director of Wuhan National Laboratory for Optoelectronics. The team has 9 professors, 5 associate professors, and nearly 200 post-doctoral, doctoral and master students. Relying on advantageous scientific research platforms such as Wuhan National Laboratory for Optoelectronics, School of Optics and Electronic Information, and Hubei Optics Valley Laboratory, our team is mainly engaged in the application of optoelectronic materials, devices and chips. Some research achievements have been made in antimony selenide thin film solar cells, quantum dot near infrared detectors, perovskite X-ray detectors and light-emitting diodes. The related work is published in Nature, Nature Photonics, Nature Energy, Nature Electronics and other journals.

Visit ODTI at: http://tfsc.wnlo.hust.edu.cn/

Wuhan National Laboratory for Optoelectronics (WNLO) is one of the six national research centers approved by the Ministry of Science and Technology of China in 2017. As an interdisciplinary research center, WNLO focuses on basic scientific and technological researches in the fields of optoelectronics for information, energy, and life science. In recent years, it has achieved fruitful results in fields including brain imaging, solar cells, ultrafast lasers, laser manufacturing, optoelectronic devices and integration, data storage etc.

Visit WNLO at: http://english.wnlo.hust.edu.cn/

Project Aims:

In this project, in view of the good photovoltaic performance of the perovskite, the perovskite thin films with narrow band gap (band gap width around 1.15 eV) and wide band gap (band gap width around 1.70 eV) are prepared by rotating coating method, thermal evaporation method and scraping method, respectively. The open-circuit voltage and current of the laminated cell are increased by additive doping and energy level regulation. The intermediate interconnect layer ITO is prepared by Reactive Plasma Deposition (RPD) technology, which effectively achieves efficient carrier tunneling compound and improves the device's filling factor and efficiency. Strive to achieve efficiency over 30%, MPP of the T50 performance stability over 1000 hours of laminated solar cells.

Methods:

1. Preparation of wide and narrow band gap perovskite thin films

Based on the structure of ABX3, the band gap of the perovskite material can be adjusted to 1.15 eV and 1.70 eV, respectively, by adjusting the components of the A cation and the X halogen ion. Perovskite films with stable performance and suitable band gap can be prepared by means of spinning coating, thermal evaporation and scraping coating.

2. High efficiency and stability of single perovskite solar cell preparation

Efficient and stable single perovskite solar cells with band gaps of 1.15eV and 1.70eV are prepared respectively to obtain large short circuit current and open circuit voltage, and strive to achieve efficiency of more than 20%, laying a foundation for the preparation of laminate cells.

3. Preparation of perovskite and perovskite laminated cells

(1) Study on interconnect layer between perovskite cell and perovskite cell. RPD and ALD technologies are used to prepare the intermediate junction layer, and the charge loss and transmission process at the intermediate junction layer are studied to obtain the maximum efficiency.

(2) Preparation of perovskite battery and perovskite battery integrated device. Optimized structure design and device fabrication of laminated cells.

Project summary:

In this project, we regulate the band gap of perovskite materials by adjusting its A-site cation and X-site halogen based on the CH₃NH₃PbI₃ perovskite ion respectively. Perovskite films with band gaps of 1.15 eV and 1.70 eV are prepared by rotating coating, thermal evaporation and scraping coating. Based on these thin films, a single perovskite solar cell with a band gap of 1.15eV and 1.70eV is prepared, respectively. The high short-circuit current and open-circuit voltage are obtained, and the efficiency is strived to exceed 20%, which lays a foundation for the preparation of laminated cells. RPD and ALD technologies are used to prepare the intermediate junction layer, and the two types of perovskite solar cells aree integrated to prepare the layered perovskite solar cells. The charge loss and charge transfer at the intermediate junction layer are studied, and the efficiency of the prepared integrated devices is more than 26%.

Assessment:

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in undergraduate interns.

2. The interns should have an interest in the field of big data analysis, solar cell, optoelectronic device, and have already demonstrated strong research potential. In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly image and date processing, preparation and characterization of semiconductor materials, SEM, TEM, XRD measurement, etc.

3. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our languages of instruction and work.

#2 Prof. Lu Peixiang’s research team (Position: 1)

Introduction to the project (lab):

Generation and Measurement of Attosecond Laser

Attosecond science has emerged as an important research area of ultrafast phenomena within the past decade. Owing to its numerous successes, attosecond science has created important new knowledge of the fundamental science of the interaction between electrons and photons. Recently, some key research topics have been identified, which are expected to make major breakthroughs for the next attosecond frontiers, such as the MHz high-repetition high-order harmonic frequency combs for the joint frontier of precision spectroscopy and ultrafast science, attosecond-pump/attosecond-probe experiments for observing and controlling electronic processes in atomic and molecular physics, and nonlinear science occurring on the attosecond time scale.

To seriously tackle the above interesting research topics, one of the most important issues is the development of high-power isolated attosecond pulses (IAPs) and/or attosecond pulse trains (APTs). IAPs and APTs are produced using high-order harmonic generation (HHG) in gases. To date, high-power APTs have successfully been generated owing to research on high harmonic energy scaling using a loose-focusing geometry. APTs with sufficiently high energy in the microjoule range with a high conversion efficiency on the 10⁻⁴ level were generated, which are intense enough for implementing some applications, such as nonlinear attosecond optics without the assistance of laser pulses, single-shot femtosecond holography and an external injector for a seeded free-electron laser (FEL) in the extreme-ultraviolet (XUV) region. In contrast, the output energy of IAPs is still not sufficient for various applications, although the shortest pulse duration achieved is sub-100 as. The widespread application of IAPs has been limited because of the low photon flux and the complexity of the laser systems required to produce IAPs. At present, the production, characterization, and application of high-energy IAPs are still under active investigation.

Theoretically, synthesized sub-cycle driver pulses with a “perfect waveform” were proposed for optimized HHG and IAP production, and the enhancement of the HHG by using these synthesized waveforms was experimentally and theoretically studied. On the basis of the above results, synthesized few/multicycle driving pulses are expected to enable scaling up of the energy and efficiency of IAP generation. To obtain IAPs with pulse energies reaching the microjoule level, a Terawatt (TW)-class waveform synthesizer is necessary, which requires the use of high-energy femtosecond lasers that are all operated at low repetition rates (e.g., 10 Hz). In this project, we will set up a Terawatt (TW)-class two-color laser waveform synthesizer to generate a high-power IAP. We expect the pulse duration of the IAP to be about 200 as and the pulse energy can reach about 300 nJ.

Introduction of the Lab

Ultrafast Optics (UFO) Lab in HUST mainly engages in the studies of strong field ultrafast optics. The research interests include attosecond pulse generation, atomic, molecular, and optical physics in strong-field, and ultrafast micronano optics. In the past twenty years, the UFO Lab has achieved many fruitful research results. The group members have published nearly 600 SCI papers in PRL, Nature Photonics, Nature Communications, Optics Letters, Optics Express, PRA, and other academic journals. The UFO Lab has 15 in-service teachers and good experimental conditions, which can guarantee the successful implementation of this project.

Visit UFO at: http://ufolab.phys.hust.edu.cn/

Wuhan National Laboratory for Optoelectronics (WNLO) is one of the six national research centers approved by the Ministry of Science and Technology of China in 2017. As an interdisciplinary research center, WNLO focuses on basic scientific and technological researches in the fields of optoelectronics for information, energy, and life science. In recent years, it has achieved fruitful results in fields including brain imaging, solar cells, ultrafast lasers, laser manufacturing, optoelectronic devices and integration, data storage etc.

Visit WNLO at: http://english.wnlo.hust.edu.cn/

Project Aims:

In this project, we aim to produce a high-power IAP (200 as, 300 nJ) with a TW-class two-/three-color laser waveform synthesizer and measure its spatio-temporal profile with an all-optical method.

Methods:

For the generation of high-power IAP, we will build a TW-class waveform synthesizer for two- or three-color laser fields. The synthesized laser field will interact with rare gases (e.g., Ar, Ne, Xe, and so on) to generate high-order harmonics. We will optimize the synthesized laser waveform to optimize the power and duration of the generated IAP.

To precisely manipulate the waveform of the synthesized laser, we will build a stability-control system for the synthesizer. In this system, we have to eliminate the relative timing and phase jitters as well as stabilizing carrier-envelope phases (CEPs) for each channel in the synthesizer.

For the measurement of the generated IAP, we will build an attosecond streaking camera equipment. Meanwhile, we will also develop an all-optical method to measure the pulse duration of the attosecond laser.

Learning outcomes:

By the end of this project interns should have gained:

9. The construction of a multi-channel (two-color, three-color) femtosecond laser coherent synthesizer and its stability-control system.

10. The construction of attosecond streaking camera equipment.

11. The all-optical measurement of attosecond laser.

Project summary:

In this project, we intend to carry out experimental research on the generation and measurement of high-power attosecond laser. In this project, we will use a terawatt femtosecond laser in combination with a multi-channel laser coherent synthesis scheme to interact with rare gases to generate high-power attosecond pulses. And the generated attosecond laser will be measured and characterized by the attosecond streaking camera technology or the all-optical method.

Assessment:

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in undergraduate interns.

2. The interns should have studied basic knowledge about a range of fields in science and technology, particularly quantum mechanics, electrodynamics, optics, and signal processing.

3. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our languages of instruction and work.

#3 Prof. Wang Jian’s research team (Position: 1)

Introduction to the project (lab):

Research on Silicon based Multi-Dimensional Multiplexing Optical Communication System

In recent years, with the rapid development of modern information technology, data communication traffic has also shown an explosive growth, which puts forward higher requirements for data storage, interconnect communication and signal processing. Using photons as information carriers in optical communications could take the unique advantages of high speed, large bandwidth and low latency, while silicon integrated photonics features the characteristics of high integration, low power consumption and low cost, providing a promising platform for the development of modern communication networks. Besides, photons could offer multiple physical resource dimensions such as frequency/wavelength, polarization, time, complex amplitude, and spatial structure as shown in Fig. 1, which could be developed into various multiplexing technologies as well as hybrid multi-dimensional multiplexing technology, providing the possibility for the further improvement of communication capacity. Therefore, the research on silicon integrated photonic chips for multi-dimensional multiplexing and processing has important strategic significance for the development of future high-speed and large-capacity communication networks.

Although multiple multiplexing technologies such as wavelength-division multiplexing (WDM), polarization-division multiplexing (PDM), mode-division multiplexing (MDM) and advanced modulation formats have developed rapidly in the past few decades, challenge remains to handle hybrid multi-dimensional multiplexing signals applied in fiber-to-chip optical processing systems. Not only the multi-dimensional signal processing puts forward higher requirements to the performance of on-chip integrated devices, including bandwidth limitation, polarization sensitivity and so on.

However, challenges remain to realize multidimensional hybrid multiplexing data transmission and signal processing between few-mode fiber transmission links and on-chip optical processing networks, since the optical coupling between fiber and chip almost exclusively in single mode regime.

Introduction of the Lab.

The Multi-Dimensional Photonics Laboratory (MDPL) is led by Professor Wang Jian. The group is mainly focusing on the multiple physical resource dimensions of photons (frequency, time, polarization, complex amplitude, space), especially the new dimension, i.e., space dimension of photon. The research interests include: high-speed and large-capacity vortex beam/vector beam/structured light multi-dimensional optical communication, data center and high-performance optical interconnection, free space/underwater/optical fiber/chip optical communication and optical interconnection, high-speed and large-capacity intelligent multi-dimensional optical signal processing, space division multiplexing optical amplification technology, manipulation of multi-dimensional optical field on chip, silicon-based photonic integrated chip, optoelectronic integration chip, femtosecond laser direct writing photonic integrated chip, surface plasma/metamaterial/metasurface devices, special transmission fiber/active fiber/optical fiber devices.

Prof. Wang Jian’s research interests include optical communications, optical signal processing, silicon photonics, photonic integration, orbital angular momentum, and structured light. He is a fellow of Optica, SPIE, and IEEE. He has been the Principal Investigator of >20 earmarked grants (NSFC, 973, etc.). He has published over 240 refereed international journal papers on Science, Science Advances, Nature Photonics, Nature Communications, Light: Science & Applications, Physical Review Letters, Optica, Laser & Photonics Reviews, ACS Photonics, Nanoscale, Nanophotonics, Photonics Research, Optics Express, Optics Letters, etc. He has authored and co-authored over 150 international conference papers on OFC, ECOC, CLEO, etc. He has also given over 110 tutorial/keynote/invited talks in international conferences including the invited talk at OFC2014 and tutorial talk at OFC2016.

Wang Jian has done pioneer works in twisted light communications employing orbital angular momentum (OAM) multiplexing, which facilitates sustainable capacity increase of optical communications. Wang Jian and co-workers demonstrated terabit-scale free-space OAM communications (Nature Photonics, 6, 488, 2012, times cited: 2608; Science, 337, 655, 2012). Wang Jian has later played a leading role in twisted and structured light communications as well as multi-dimensional optical communications. He studied fundamental properties of spin angular momentum (SAM), OAM and vector beams (Nature Communications, 12, 4186, 2021; Physical Review Letters, 127, 233901, 2021; Laser & Photonics Reviews, 11, 1700183, 2017, Cover; Laser & Photonics Reviews, 14, 2000249, 2020, Cover), implemented outdoor free-space and adaptive underwater OAM communications, demonstrated OAM amplifier (Research, 2020, 7623751, 2020) and record 300-km fiber OAM communications. He realized structured light communications (Bessel, Airy, vector) and demonstrated the direct fiber vector eigenmode multiplexing transmission (Light: Science & Applications, 7, 17148, 2018, Cover). He authored/co-authored important review articles and comments on twisted (Photonics Research, 4, B14, 2016, times cited: 378; Advances in Optics and Photonics, 7, 66, 2015, times cited: 927) and structured light communications (Nature Photonics, 12, 249, 2018). These works were interviewed by the Nature Photonics editor (Dr. Rachel Won) (Nature Photonics, 11, 619, 2017).

Wang Jian and co-works have made an important breakthrough in multi-dimensional entanglement transport through single-mode fiber (SMF) (Science Advances, 6, eaay0837, 2020). By entangling spin-orbit degrees of freedom of a biphoton pair, passing the spin photon down the SMF while accessing multiple OAM subspaces with the other, multi-dimensional entanglement transport was realized, showing distinct advantages of deployment over legacy networks with conventional SMF.

Wang Jian has done innovative works in photonic integrated devices on different platforms for twisting and structuring light. Wang Jian demonstrated on-chip OAM generator (Optics Letters, 43, 3140, 2018, Editor’s Pick), all-fiber OAM generator (Optics Letters, 40, 4376, 2015), metasurface for structuring light (Optics Letters, 38, 932, 2013), and integrated vector laser (ACS Photonics, 6, 3261, 2019, Cover). Very recently, he demonstrated ultra-compact broadband polarization diversity OAM generator with 3.6x3.6 μm2 footprint (Science Advances, 5, eaau9593, 2019).

Wang Jian has also done lots of works of great significance in chip-scale optical signal processing. Some representative contributions include terabit-scale on-chip optical interconnects, chiral silicon photonic circuits (Optica, 6, 61066, 2019), subwavelength slot waveguides (Physical Review Letters, 127, 233902, 2021), subwavelength grating slot microring resonators (Nanoscale, 12, 15620, 2020), reconfigurable multi-functional photonic signal processor (ACS Photonics, 7, 1235, 2020, Cover) and programmable multi-task photonic signal processor (ACS Photonics, 7, 2658, 2020, Cover) on a silicon chip.

Wuhan National Laboratory for Optoelectronics (WNLO) is one of the six national research centers approved by the Ministry of Science and Technology of China in 2017. As an interdisciplinary research center, WNLO focuses on basic scientific and technological researches in the fields of optoelectronics for information, energy, and life science. In recent years, it has achieved fruitful results in fields including brain imaging, solar cells, ultrafast lasers, laser manufacturing, optoelectronic devices and integration, data storage etc.

Visit WNLO at: http://english.wnlo.hust.edu.cn/

Project Aims:

In this project, we will propose to use silicon-based integrated photonic devices to realize multi-dimensional fiber-to-chip optical processing system for hybrid wavelength-, mode- and polarization-division multiplexing signals.

First of all, in order to solve the few-mode fiber transmission link to the silicon integrated optical processing chip, the efficient mode coupling device between few-mode fiber and multi-mode photonic chip needs to be designed. We propose a multi-mode coupler based on heterogeneous waveguides, which enables the direct coupling for multiple guided modes between FMF and silicon integrated chip. The proposed multi-mode coupler consists of tapered FMF and silicon integrated multistage waveguide tapers buried in the polymer waveguide, where the tapered fiber acts as one transition optical waveguide to reduce the mode spot size as well as the coupling loss, while the silicon integrated multistage waveguide tapers are used to realize mode conversion.

Secondly, the multi-dimensional multiplexing processing on the silicon-based chip needs to be designed. The silicon multiple guided modes are demultiplexed into fundamental TE and TM modes based on the cascaded ADC structure, then PR structure is introduced to rotate the fundamental TM mode into fundamental TE mode. The silicon integrated chip takes advantages of parallel cascaded micro-ring resonator array to perform the signal processing function as reconfigurable optical add-drop multiplexer (ROADM). Finally, the chip can realize multi-dimensional fiber-to-chip optical processing system for hybrid wavelength-, mode- and polarization-division multiplexing signals.

Methods:

This project mainly adopts FDTD and EME algorithms for simulation and design of silicon-based integrated photonic devices: the efficient mode coupling device between few-mode fiber and multi-mode photonic chip, mode (de)multiplexer, micro-ring (wavelength (de)multiplexer) and polarization (de)multiplexer so as to build the whole silicon based processing chip. For the fabrication of devices, we will use electron beam lithography (EBL) technology to fabricate silicon-based integrated photonic devices.

Project summary:

After decades of development, the traditional single-mode optical fiber communication has approached its Shannon capacity limit and have begun to have a new capacity crisis. Photons offer multiple physical resource dimensions such as polarization, frequency/wavelength, amplitude, phase, time, etc. The exploration of new dimensions and multi-dimensional integration of photonics is the key to the sustainable expansion of optical communications. Silicon-based integrated photonics has the characteristics of high integration, low power consumption and low cost, which provides a promising platform for the development of optical communication networks. This project studies the key technical issues in multi-dimension multiplexing processing, and realizes the hybrid wavelength-, mode- and polarization-division multiplexing on chip with photonic integrated devices, and realizes the multi-dimension signal processing system of fiber-to-chip- to-fiber.

Assessment:

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in undergraduate interns.

2. The interns should have an interest in the field of optical communication, optical processing, and integrated optics. In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly optical communication, optical processing, and integrated optics.

3. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our languages of instruction and work.

④School of Electronic Information and Communications

#1 Prof. Yang Peng’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

The prototype of the Metaverse originated from the fiction novel Snow Crash, demonstrated a vivid universe created by computers. Metaverse has revolutionized the way in which humans interact with multimedia through intensive visual and auditory stimulation, making users deeply immersed in a virtual world. The fundamental technologies behind Metaverse are Virtual Reality (VR), multimedia networking, and human-machine interaction.

2. The content of project is key technologies and interesting ideas on Multimedia Communications and Networking for Metaverse.

Project Aims:

This internship project aims to:

1. Learning the fundamentals of multimedia networking, including network architecture and transmission protocols

2. Getting familiar with Virtual reality (VR) video coding, including multi-view cameras, mapping and coding

3. Understanding mobile edge computing, including end-edge-cloud coordinated framework, communication resource allocation.

Methods:

1. Literature review

2. Interactive VR system development and Prototyping

3. Theoretical analysis and transmission scheme design

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of the technology of virtual reality

2. Learning the transmission protocols of multimedia networking

3. Prototyping skills of real VR systems

Project summary

This project is on the enabling technologies of Multimedia communications and networking for Metaverse.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of multimedia communications and have already demonstrated strong research potential.

3. In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly Calculus and Probability Theory.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#2 Prof. Liu Qiong and Prof. Yang You’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

Recently, Neural radiance fields (NeRFs) have drawn great attention and are now important cornerstones of metaverse and augmented reality research, as is their stronger efficiency and more imaginative rendering performance.NeRFs refer to a suit of deep neural networks that are used to learn and represent objects or scenes. Generally speaking,NeRFs have five main characters: volumetric rendering, novel view synthesis, factorizable embedded space, multi-view consistency and weighted importance sampling.In this project, we mainly use nerf for 3D reconstruction work.

2. The content of project is learning the current state of research on neural radiation fields, how they work and how to train a neural network model that meets the metrics by using an existing training set.

Project Aims:

This internship project aims to train a neural radiation field that can clearly represent a 3D model and optimize the neural network to improve its performance in a certain way.

Methods:

1. Training 3D models with neural networks

2. Representing 3D Models with volume Rendering

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of how neural radiation fields work.

2. Gain the ability to use neural radiation fields to achieve novel view synthesis.

3. Gain the ability to optimize the neural radiation field based on experimental phenomena and results.

Project summary

This program focuses on giving students an understanding of what a neural radiation field is and how to train it well.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. Interns should be motivated to learn and be able to overcome difficulties.

3. The interns should have an interest in the field of deep learning and 3D reconstruction and have already demonstrated strong research potential.

4. In addition, they should have studied the basic knowledge about a range of fields in science and technology, particularly computer programming languages python, linear algebra and deep learning.

5. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

² Internship in Chinese law, Chinese governance, and Chinese Economy

①School of law

#1 Prof. Wang Xigen’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

Until recently, artificial intelligence has become an important strategic field for competition among countries. In this context, China urgently needs to build a new paradigm of systematic, supportive and normative rule of law for artificial intelligence. This project will focus on how to promote and standardize the development of artificial intelligence in China.

2. The content of project is learning the development of rule of law for AI and how these laws and regulations be operated in China.

Project Aims:

This internship project aims to let the interns gain the knowledge on the laws and regulations on AI in China and in Europe. The interns would also gain some key methods of legal analysis.  

Methods:

1. System analysis method

2. Empirical analysis

3. Normative analysis

Learning outcomes:

By the end of this project interns should have gained:

12. The knowledge of laws and regulations on AI in China and in Europe.

13. Methods of legal analysis.

Project summary

In order to promote the development of the related laws and regulations on AI, this project would find out the legal index system which suitable for the development of artificial intelligence by analyzing and evaluating the four aspects of legislation, enforcement, judicature and law-abiding.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of law or management or AI or computer science and technology and have already demonstrated strong research potential.

3. The interns should have an ability to search the relevant literature or documents by the related databases or be willing to learn the skills.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

②College of Public Administration

#1 Prof. Zhang Yi’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

This project will focus on the digital transformation of governments. After entering the digital age, it is a challenging issue how to effectively use advanced digital technology to transform governance paradigm, so as to improve government governance efficiency and enhance public trust in the government, which is of important theoretical and practical value.

2. The content of project is to learn the theory of government digital transformation, investigate the real cases of government digital transformation, and master the methods to carry out in-depth research on government digital transformation.

Project Aims:

The research objective of this project is to clarify the driving factors and mechanism of government digital transformation, analyze the impact of government digital transformation on governance effectiveness, and propose the optimal path of government digital transformation.

Methods:

1. Case study

2. Quantitative analysis method

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of the relationship between digital technologies and governance paradigms.

2. Learning the underlying mechanisms of digital transformation of governments.

3. An ability to analyze multiple cases to extract generalized theories.

Project summary

This project will clarify the mechanism, impact and path of digital transformation of governments

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of public administration as well as digital technology, and have already demonstrated strong research potential.

3. In addition, they should have studied the basic knowledge about a range of fields in social science, particularly public administration and public policy.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

#2 Prof. Seah Shuo’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

With the acceleration of global urbanization, urban security issues have become a focus of social attention. From terrorist attacks, natural disasters to criminal incidents, they can all pose serious threats to urban security. How to detect and effectively respond to risks related early on has become an important research topic for urban managers and various sectors of society. The development of big data technology has provided new ideas and methods for urban safety risk warning research.

Project Aims:

By this project, we plan to integrate the concepts of refinement, intelligence, and scientificity into the entire process of urban emergency management before, during, and after the crisis, promoting the high integration of urban emergency management and big data technology; Applying the latest achievements of big data to the governance of natural disasters, accident disasters, public health incidents, and social security incidents enables data support for prevention preparation, prediction and early warning, decision-making response, and rescue recovery in urban public crisis governance.

Methods:

1. Risk analysis

2. Data mining

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of the relationship between urban security and big data

2. Learning the methods of risk analysis.

3. An ability in material characterization and data analysis.

Project summary

One of the advantages of big data technology is correlation analysis, which evaluates and predicts security risk points by comparing and analyzing the security risk correlation of various types of data.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of public security and big data analysis and have already demonstrated strong research potential.

3. In addition, they should have studied the basic knowledge about a range of fields in public administration and data mining software.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.

③School of Economics

#1 Prof. Peng Bin’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

Machine learning (ML) methods hold great promise in the field of health financing. This project is applying ML methods in health financing-related subjects. These include predicting health expenditure, risk scoring, fraud detection, identification of households for targeted policies, health oriented benefit package design, and analysis of the effects of health coverage scheme design on health service utilization. Machine learning algorithms can analyze vast amounts of data to provide insights and predictions that can help policy makers and institutes better plan and manage resources, reduce unnecessary expenses, and improve the quality and efficiency of healthcare services.

Project Aims:

This internship project aims to apply Machine Learning methods in health financing-related topics, e.g. Predicting health expenditure, Risk scoring, Fraud detection and other potential related topics.

Methods:

Machine Learning Methods

Learning outcomes:

By the end of this project interns should have gained:

1. Deep understanding of machine learning methods and their applications in health financing-related fields.

2. Ability of proficient using data analysis software such as Python or Stata.

3. Better understanding of the development of health economics and welfare analysis.

Project summary

The project is about Machine Learning applications in health financing-related topics, including:

(1) Predicting health expenditure: Predict future health expenditure based on patients' historical data and other relevant information. This prediction can assist medical institutions in better planning and managing medical resources, including budget, staff, and equipment.

(2) Risk scoring: Analyze patients' medical records and data, and provide risk scores based on this information. This approach enables more accurate assessments of patients' health statuses and medical needs, thus providing better personalized medical services.

(3) Fraud detection: Use machine learning algorithms to analyze large amounts of medical claims data to identify possible fraudulent activities. This helps medical institutions reduce unnecessary medical expenses and improve the efficiency of fund utilization.

(4) The impact of health insurance plan design on healthcare utilization: Analyze large amounts of medical records and insurance data to understand the impact of different health insurance plan designs on healthcare utilization. This approach allows for optimizing insurance plans to better facilitate healthcare utilization and improve the efficiency of medical resource utilization.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in undergraduate interns.

1. The interns should have an interest in the field of economics and have already demonstrated strong research potential.

2. The interns should have studied the basic knowledge about a range of fields in economics or business analysis related, particularly health economics and econometrics.

3. The interns should have math foundations in calculus, linear algebras, probability and statistics and with proficient in using Python is more welcomed.

4. It is not a matter of whether the interns understand Chinese or not, English as well as Chinese are our languages of instruction and work.

#2 Prof. Sun Ya’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

In recent decades, China has witnessed a rapid economic transformation, marked by urbanization and industrialization. Amidst this wave of modernization, there is a growing recognition of the importance of preserving and promoting the nation's rich cultural heritage. Intangible Cultural Heritage (ICH), encompassing traditions, customs, rituals, and crafts passed down through generations, stands as a testament to China's profound history and diverse cultural tapestry.

As the nation endeavors to balance economic development with cultural preservation, a burgeoning interest has emerged in understanding how Intangible Cultural Heritage Projects (ICHPs) contribute to local employment dynamics. These projects, often funded by governmental bodies, NGOs, or private enterprises, aim to safeguard, revive, and promote intangible cultural practices across various regions in China. The intricate relationship between ICHPs and local employment is a multifaceted aspect that warrants comprehensive exploration.

Project Aims:

This project aims to delve into the intricate interplay between Intangible Cultural Heritage Projects in China and their influence on local employment. Through a comprehensive examination of case studies, interviews with stakeholders, and analysis of socio-economic indicators, we seek to unravel the nuanced dynamics at play and provide valuable insights into how the preservation of intangible cultural heritage can be harnessed to foster sustainable development and inclusive prosperity at the local level.

Methods:

Interview; Literature review; Data analysis; Case studies

Learning outcomes:

By the end of this project interns should have gained:

1. Analyze the complex relationship between Intantible Cultural Heritage Projects (ICHPs) in China and their socio-economic impact on local employment.

2. Evaluate the effectiveness of ICHPs in preserving and promoting intangible cultural heritage while simultaneously contributing to local economic development.

3. Identify key factors influencing the success or challenges of ICHPs in creating employment opportunities within different regional contexts in China.

4. Understand the potential positive and negative consequences of ICHPs on local communities, with a focus on issues such as cultural commodification, gentrification, and sustainable tourism.

5. Formulate informed recommendations for policymakers, stakeholders, and practitioners involved in ICHPs, aiming to maximize positive socio-economic outcomes for local communities.

6. Develop critical thinking skills to assess the balance between cultural preservation and economic development, considering the diverse cultural landscape and socio-economic disparities in China.

7. Communicate findings effectively through written reports, presentations, and discussions, demonstrating a nuanced understanding of the interplay between cultural heritage preservation and local economic dynamics in the Chinese context.

Project summary

This project aims to investigate the intricate dynamics between Intangible Cultural Heritage Projects (ICHPs) in China and their impact on local employment. Against the backdrop of rapid economic development and urbanization, the preservation of China's diverse intangible cultural heritage has gained prominence. ICHPs, designed to safeguard and promote these cultural practices, are expected to play a pivotal role not only in cultural preservation but also in fostering local economic development.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

We are interested in undergraduate interns.

- Currently enrolled in an undergraduate program with a focus on economics

- Strong academic foundation in econometrics

- Proficient in Stata, python and R

- Excellent verbal and written communication skills.

- Analytical and problem-solving abilities.

- Ability to work collaboratively in a team environment.

- Demonstrated interpersonal skills and ability to build positive relationships.

#3 Prof. Ye Jinqi’s research team (Position: 1)

Introduction to the project (lab):

1. Background of the project.

This project will focus on the gap between urban and rural medical insurance benefits, and the policy analysis of The Integration of Basic Medical Insurance for Urban and Rural Resident. Using structure model and data analysis to continuously strengthen the redistributive function of medical insurance while reasonably determining the level of benefits to align with the economic development level and the capacity of the funds

The content of project is learning the methods of big data analysis, economic experimental and survey design.

Project Aims:

This internship project aims to develop a welfare analysis to estimate the total value of the basic medical insurance of urban and rural residents. Provide policy implementation to enhance the fairness and inclusiveness of basic medical insurance coverage and benefits, gradually narrowing the gaps between systems, population groups, and regions.

Methods:

1. Structure model-welfare analysis

2. Econometric model and data analysis

Learning outcomes:

By the end of this project interns should have gained:

14. Deep understanding of the background of health insurance system in China.

15. Learning the methods of policy analysis and data analysis.

16. An ability to develop survey and collect data.

Project summary

This project is to theoretically and empirically estimate the value of medical insurance integration to rural recipients of the integrated basic medical insurance in China.

Assessment

Oral presentation is required by the end of internship.

Applicant profile:

1. We are interested in the undergraduate interns.

2. The interns should have an interest in the field of health economics and have already demonstrated strong research potential.

3. In addition, they should have studied the basic knowledge about a range of fields in economics, particularly health economics, econometrics.

4. It is no matter whether the interns understand Chinese or not, English as well as Chinese are our language of instruction and work.