Contact
Biography
Minglei You received his PhD degree from the University of Durham (U.K.) in 2019 and master degree from the Beijing University of Posts and Telecommunications (China) in 2014. In 2012, he was a short-term visiting student at the University of Electro-Communications (Japan). Since 2014, he has been with the University of Durham as a recipient of the Durham Doctoral Scholarship. From 2019 to 2021, he was a Postdoctoral Research Associate with the Durham University (U.K.) and Loughborough University (U.K.). Since 2021, he has been with the University of Nottingham as an Assistant Professor. His recent research interest includes Internet of Things, Machine Learning for communications, Testbed Design, Smart Grid, cyber security and Integrated Energy Systems. He was recognized as an Exemplary Reviewer for IEEE Wireless Communications Letters.
Teaching Summary
EEEE3087 - Mobile Technologies
EEEE4119 - Artificial Intelligence and Intelligent Systems
Research Summary
Job Opening: EV Charging System Portal Designer - Clean Energy (KTP Associate) (25 months fixed term 33k-40k, deadline Aug 22)
Application Link: https://jobs.nottingham.ac.uk/Vacancy.aspx?ref=ENG354023
Location: Jubilee Campus
Salary: £33,000 to £40,000 per annum (pro-rata if applicable) depending on skills and experience. Salary progression beyond this scale is subject to performance.
Closing Date: Tuesday 22 August 2023
Reference: ENG354023
University of Nottingham (UoN) invites applications for a Portal Designer to join our exciting collaboration with Kingsmill Industries (UK) Limited.
Based at Kingsmill in Pinxton, North Nottinghamshire, you will have the unique opportunity to lead the design and development of a cloud-based energy management tool for connecting and aggregating clean-energy devices. You will work within Kingsmill's close team, reporting to the General Manager of the Clean Energy Division and alongside another Associate who will be developing the power electronic convertor for Electric Vehicle Supply Equipment (EVSE).
As an enthusiastic graduate, this is a career-development opportunity for you to manage a Knowledge Transfer Partnership (KTP). Fully supported by academic experts in power electronics and IoT technologies within the internationally renowned Power Electronics, Machines and Control (PEMC) research group, you will be instrumental in delivering a high-profile and commercially strategic project that will enable Kingsmill Industries to compete in the renewable energy sector. Through the KTP, you will help Kingsmill to acquire know-how in cloud-based computing to manage and control future green energy products.
You will have the opportunity to demonstrate your ability to develop commercially viable, innovative solutions and communicate complex information to a variety of audiences, including Kingsmill's engineering and management teams and their client base. An awareness of commercial drivers and previous industrial experience is desirable, but not essential.
You should hold an Honours Degree in Electrical and/or Electronic Engineering or Computer Science, ideally with a postgraduate qualification in Cloud-Computing/Software Engineering/Data Management, or equivalent industrial/commercial experience in this area. You should have knowledge and experience of designing and programming embedded computing systems. You should also have experience of cloud-based computing systems.
As a people-orientated individual, you will have the ability to influence and engage collaboratively with Kingsmill, UoN and other stakeholders. As a proactive person, you will have the passion and desire for creating something new and be enthusiastic and motivated to organise your own time effectively and have a flexible approach to prioritising work tasks. Throughout the KTP, you will be fully supported and mentored to nurture your talent. You will have your own budget of £2,000 pa for training and CPD, helping you develop your skillset and reach your personal and professional career goals.
UoN is committed to providing competitive employment packages whilst supporting the well-being of its staff to help them reach their full potential. As a University of Nottingham employee, you will have access to the resources of UoN and a range of benefits and rewards, including staff discounts, travel schemes and an attractive pension scheme.
KTP is a UK Government scheme promoting sustained and mutually beneficial relationships between universities and industry.
The post is offered on a full time (39 hours per week), fixed term contract for 25 months.
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Currently, there are openings for the following PhD projects:
Project Title: PhD (iCASE) "IoT and Machine Learning Technology for Condition Monitoring in Variable Speed Motor Drives"
Note that this is a funded position and the funding is for UK students only.
Are you interested in starting a PhD at Nottingham this September? We have an exciting project with Siemens which will integrate Internet of Things technologies with power electronic drives used for industrial applications. The main aim is to research how AI and machine learning technologies can be used for condition monitoring of commercial motor drives, exploiting the fact that there may be many hundreds of these drives working on different applications (fans, pumps in factories, treadmills in gyms, hoists and lifts in buildings) all connected together via the internet. Please feel free to contact Prof Mark Sumner (mark.sumner@nottingham.ac.uk) or Dr Minglei You (minglei.you@nottingham.ac.uk) if you need any further information.
Project Title: PhD Studentships in Electromagnetic Compatibility for 25kV Rail Systems, funded by Network Rail
Note: This is a funded position with UK full scholarship. International applications are welcome but the scholarship will only cover part of the fees and the applicant will need to pay the difference.
Strategy, Implementation and Analytical Tool for Handling Large volume of 25kV Railway AC Electrical System Electromagnetic Compatibility (EMC) Measurement Data
Measurement systems on 25kV overhead line systems generate terabytes of data that, if processed correctly, can yield insights into the interaction of electrical and electronic systems on the 25kV network. This PhD aims to identify and develop data storage and processing methods and associated mathematical models that will allow full-system analysis based on historic and future measurement data. An academic or technical background in the area of databases, data management, mathematics and software development is required. The PhD is offered jointly by the Optics and Photonics, and Power Electronics, Machines and Control (PEMC) research groups, with funding and industrial guidance from Network Rail. Please contact Dr Minglei You (Minglei.You@nottingham.ac.uk) or Dr Peter Christopher (Peter.Christopher@nottingham.ac.uk) for more information.
Project Title: Artificial Intelligence enabled Smart Cities
Project Description:
UK has set a clear target for the net zero carbon emission by 2050, which demands innovation in all sectors of the UK economy. Applicants are invited to undertake a 3 year PhD program with the PEMC group at the University of Nottingham, focusing on the decarbonization via Smart Cities, with the support with the advanced technologies such as Artificial Intelligence (AI), Information technologies (ICT), and Internet of Things (IoT).
This project is related to the development of AI enabled Smart Cities to support the aforementioned tasks with the following actions:
1. Develop The system modelling and analysis for typical Smart City scenarios (such as homes, buildings and roads) with the integration of advanced technologies/applications (such as ICT, IoT, Renewable Energy, EVs, Battery Electrical Systems, Thermal Energy Systems, and Energy Market).
2. Develop AI and numerical based strategies to address the long-standing and foreseeable challenges, such as 1) the forecasting and uncertainty due to renewable energy sources, 2) big data due to ubiquitous sensors and controllers, and 3) proactive energy management strategies based on both historical and real-time energy usage.
3. Develop scalable control algorithms and/or smart energy management strategies, which enables the smart integration and control of the distributed devices in the home/building/road scenarios, as well as new services to encourage more efficient energy consumptions, e.g., incentive schemes like demand side management, and second-life EV batteries.
We are seeking talented candidates with:
1. First or upper second class degree in Electrical and Electronic Engineering, Computer Science or related scientific discipline.
2. First rate analytical and numerical skills, with a well-rounded academic background.
3. Desirable to have good knowledge regarding AI, ICT, IoT, control theory and electrical skills.
4. Background with relevant programming languages and toolboxes, e.g., MATLAB, Python, PyTorch, Keras, and C/C++.
5. A driven, professional and self-motivated work attitude is essential.
6. The ability to produce high quality presentations and written reports.
This is an excellent opportunity to work on novel AI-based solutions to address the decarbonization challenges via IoT, Smart Cities and Energy Systems, with key skills and knowledge in high-impact research and practical applications.
Other PhD openings are available in the following topics:
1. Internet of Things with applications for Energy Systems and Vehicular Networks.
2. The integration of AI and advanced Information and Communication Technologies in the Energy System.
3. Artificial Intelligence enabled Integrated Energy Systems.
4. Testbed Design and Prototype Implementation for AI-enabled Wireless Communication Systems and Integrated Energy Systems.
5. Signal Processing for advanced Wireless Communication Networks.
I welcome enquiries from potential PhD candidates from Home, EU and international countries, who are interested in the following research areas: Internet of Things, Integrated Energy System, Multi-vector Energy Systems, Machine Learning, AI, Smart Grid, Signal Processing and Wireless Communication Networks.
There are PhD vacancies and scholarship opportunities are available. Self-funded PhD candidates are welcome.
For general information regarding scholarship information, see the followings:
https://www.nottingham.ac.uk/studywithus/international-applicants/scholarships/research-scholarships.aspx
Please feel free to contact me if you are interested and/or need more information.
Selected Publications
YOU, MINGLEI, WANG, QIAN, SUN, HONGJIAN, CASTRO, IVAN and JIANG, JING, 2022. Digital twins based day-ahead integrated energy system scheduling under load and renewable energy uncertainties Applied Energy. 305, 117899 YOU, MINGLEI, ZHENG, GAN, CHEN, TIANRUI, SUN, HONGJIAN and CHEN, KWANG-CHENG, 2021. Delay Guaranteed Joint User Association and Channel Allocation for Fog Radio Access Networks IEEE Transactions on Wireless Communications. 20(6), 3723-3733 CHEN, TIANRUI, ZHANG, XINRUO, YOU, MINGLEI, ZHENG, GAN and LAMBOTHARAN, SANGARAPILLAI, 2021. A GNN based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks IEEE Internet of Things Journal.
Future Research
Job Opening: EV Charging System Portal Designer - Clean Energy (KTP Associate) (25 months fixed term 33k-40k, deadline Aug 22)
Application Link: https://jobs.nottingham.ac.uk/Vacancy.aspx?ref=ENG354023
Location: Jubilee Campus
Salary: £33,000 to £40,000 per annum (pro-rata if applicable) depending on skills and experience. Salary progression beyond this scale is subject to performance.
Closing Date: Tuesday 22 August 2023
Reference: ENG354023
University of Nottingham (UoN) invites applications for a Portal Designer to join our exciting collaboration with Kingsmill Industries (UK) Limited.
Based at Kingsmill in Pinxton, North Nottinghamshire, you will have the unique opportunity to lead the design and development of a cloud-based energy management tool for connecting and aggregating clean-energy devices. You will work within Kingsmill's close team, reporting to the General Manager of the Clean Energy Division and alongside another Associate who will be developing the power electronic convertor for Electric Vehicle Supply Equipment (EVSE).
As an enthusiastic graduate, this is a career-development opportunity for you to manage a Knowledge Transfer Partnership (KTP). Fully supported by academic experts in power electronics and IoT technologies within the internationally renowned Power Electronics, Machines and Control (PEMC) research group, you will be instrumental in delivering a high-profile and commercially strategic project that will enable Kingsmill Industries to compete in the renewable energy sector. Through the KTP, you will help Kingsmill to acquire know-how in cloud-based computing to manage and control future green energy products.
You will have the opportunity to demonstrate your ability to develop commercially viable, innovative solutions and communicate complex information to a variety of audiences, including Kingsmill's engineering and management teams and their client base. An awareness of commercial drivers and previous industrial experience is desirable, but not essential.
You should hold an Honours Degree in Electrical and/or Electronic Engineering or Computer Science, ideally with a postgraduate qualification in Cloud-Computing/Software Engineering/Data Management, or equivalent industrial/commercial experience in this area. You should have knowledge and experience of designing and programming embedded computing systems. You should also have experience of cloud-based computing systems.
As a people-orientated individual, you will have the ability to influence and engage collaboratively with Kingsmill, UoN and other stakeholders. As a proactive person, you will have the passion and desire for creating something new and be enthusiastic and motivated to organise your own time effectively and have a flexible approach to prioritising work tasks. Throughout the KTP, you will be fully supported and mentored to nurture your talent. You will have your own budget of £2,000 pa for training and CPD, helping you develop your skillset and reach your personal and professional career goals.
UoN is committed to providing competitive employment packages whilst supporting the well-being of its staff to help them reach their full potential. As a University of Nottingham employee, you will have access to the resources of UoN and a range of benefits and rewards, including staff discounts, travel schemes and an attractive pension scheme.
KTP is a UK Government scheme promoting sustained and mutually beneficial relationships between universities and industry.
The post is offered on a full time (39 hours per week), fixed term contract for 25 months.
/--------------------------------------------------------------------------------------------------------------------------------------------------/
Currently, there are openings for the following PhD projects:
Project Title: PhD (iCASE) "IoT and Machine Learning Technology for Condition Monitoring in Variable Speed Motor Drives"
Note that this is a funded position and the funding is for UK students only.
Are you interested in starting a PhD at Nottingham this September? We have an exciting project with Siemens which will integrate Internet of Things technologies with power electronic drives used for industrial applications. The main aim is to research how AI and machine learning technologies can be used for condition monitoring of commercial motor drives, exploiting the fact that there may be many hundreds of these drives working on different applications (fans, pumps in factories, treadmills in gyms, hoists and lifts in buildings) all connected together via the internet. Please feel free to contact Prof Mark Sumner (mark.sumner@nottingham.ac.uk) or Dr Minglei You (minglei.you@nottingham.ac.uk) if you need any further information.
Project Title: PhD Studentships in Electromagnetic Compatibility for 25kV Rail Systems, funded by Network Rail
Note: This is a funded position with UK full scholarship. International applications are welcome but the scholarship will only cover part of the fees and the applicant will need to pay the difference.
Strategy, Implementation and Analytical Tool for Handling Large volume of 25kV Railway AC Electrical System Electromagnetic Compatibility (EMC) Measurement Data
Measurement systems on 25kV overhead line systems generate terabytes of data that, if processed correctly, can yield insights into the interaction of electrical and electronic systems on the 25kV network. This PhD aims to identify and develop data storage and processing methods and associated mathematical models that will allow full-system analysis based on historic and future measurement data. An academic or technical background in the area of databases, data management, mathematics and software development is required. The PhD is offered jointly by the Optics and Photonics, and Power Electronics, Machines and Control (PEMC) research groups, with funding and industrial guidance from Network Rail. Please contact Dr Minglei You (Minglei.You@nottingham.ac.uk) or Dr Peter Christopher (Peter.Christopher@nottingham.ac.uk) for more information.
Project Title: Artificial Intelligence enabled Smart Cities
Project Description:
UK has set a clear target for the net zero carbon emission by 2050, which demands innovation in all sectors of the UK economy. Applicants are invited to undertake a 3 year PhD program with the PEMC group at the University of Nottingham, focusing on the decarbonization via Smart Cities, with the support with the advanced technologies such as Artificial Intelligence (AI), Information technologies (ICT), and Internet of Things (IoT).
This project is related to the development of AI enabled Smart Cities to support the aforementioned tasks with the following actions:
1. Develop The system modelling and analysis for typical Smart City scenarios (such as homes, buildings and roads) with the integration of advanced technologies/applications (such as ICT, IoT, Renewable Energy, EVs, Battery Electrical Systems, Thermal Energy Systems, and Energy Market).
2. Develop AI and numerical based strategies to address the long-standing and foreseeable challenges, such as 1) the forecasting and uncertainty due to renewable energy sources, 2) big data due to ubiquitous sensors and controllers, and 3) proactive energy management strategies based on both historical and real-time energy usage.
3. Develop scalable control algorithms and/or smart energy management strategies, which enables the smart integration and control of the distributed devices in the home/building/road scenarios, as well as new services to encourage more efficient energy consumptions, e.g., incentive schemes like demand side management, and second-life EV batteries.
We are seeking talented candidates with:
1. First or upper second class degree in Electrical and Electronic Engineering, Computer Science or related scientific discipline.
2. First rate analytical and numerical skills, with a well-rounded academic background.
3. Desirable to have good knowledge regarding AI, ICT, IoT, control theory and electrical skills.
4. Background with relevant programming languages and toolboxes, e.g., MATLAB, Python, PyTorch, Keras, and C/C++.
5. A driven, professional and self-motivated work attitude is essential.
6. The ability to produce high quality presentations and written reports.
This is an excellent opportunity to work on novel AI-based solutions to address the decarbonization challenges via IoT, Smart Cities and Energy Systems, with key skills and knowledge in high-impact research and practical applications.
Other PhD openings are available in the following topics:
1. Internet of Things with applications for Energy Systems and Vehicular Networks.
2. The integration of AI and advanced Information and Communication Technologies in the Energy System.
3. Artificial Intelligence enabled Integrated Energy Systems.
4. Testbed Design and Prototype Implementation for AI-enabled Wireless Communication Systems and Integrated Energy Systems.
5. Signal Processing for advanced Wireless Communication Networks.
I welcome enquiries from potential PhD candidates from Home, EU and international countries, who are interested in the following research areas: Internet of Things, Integrated Energy System, Multi-vector Energy Systems, Machine Learning, AI, Smart Grid, Signal Processing and Wireless Communication Networks.
There are PhD vacancies and scholarship opportunities are available. Self-funded PhD candidates are welcome.
For general information regarding scholarship information, see the followings:
https://www.nottingham.ac.uk/studywithus/international-applicants/scholarships/research-scholarships.aspx
Please feel free to contact me if you are interested and/or need more information.