Minglei You

Contact

• workRoom Room B26 PEMC Building
  Jubilee Campus
  Wollaton Road
  Nottingham
  NG8 1BB
  UK
• Minglei.You@nottingham.ac.uk

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. He is a Royal Society Short Industrial Fellow during 2024-2025. 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.

I welcome inquiries from potential PhD candidates and visitors from Home, EU and international countries, who are interested in the following research areas: Internet of Things, Integrated Energy Systems, AI, Smart Grid, Signal Processing, Reconfigurable Intelligent Surfaces, Wireless Communication Networks, 5G and beyond 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.

Teaching Summary

EEEE3087 - Mobile Technologies (Module Convenor)

EEEE4119 - Artificial Intelligence and Intelligent Systems

EEEE2063 - Design and Implementation of Engineering Software

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
• YOU, MINGLEI, ZHENG, GAN and SUN, HONGJIAN, 2021. A Data Augmentation based DNN Approach for Outage-Constrained Robust Beamforming In: ICC 2021-IEEE International Conference on Communications. 1-5
• 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.

• View all publications

Past Research

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.

• 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
• YOU, MINGLEI, ZHENG, GAN and SUN, HONGJIAN, 2021. A Data Augmentation based DNN Approach for Outage-Constrained Robust Beamforming In: ICC 2021-IEEE International Conference on Communications. 1-5
• 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.
• ZHANG, JUPING, YOU, MINGLEI, ZHENG, GAN, KRIKIDIS, IOANNIS and ZHAO, LIQIANG, 2021. Model-driven Learning for Generic MIMO Downlink Beamforming With Uplink Channel Information IEEE Transactions on Wireless Communications.
• YOU, MINGLEI, ZHANG, XINRUO, ZHENG, GAN, JIANG, JING and SUN, HONGJIAN, 2020. A versatile software defined smart grid testbed: artificial intelligence enhanced real-time co-evaluation of ICT systems and power systems IEEE Access. 8, 88651-88663
• ZHANG, JUPING, XIA, WENCHAO, YOU, MINGLEI, ZHENG, GAN, LAMBOTHARAN, SANGARAPILLAI and WONG, KAI-KIT, 2020. Deep learning enabled optimization of downlink beamforming under per-antenna power constraints: Algorithms and experimental demonstration IEEE Transactions on Wireless Communications. 19(6), 3738-3752
• HUA, WEIQI, YOU, MINGLEI and SUN, HONGJIAN, 2019. Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field In: 2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops). 204-209
• YOU, MINGLEI, LIU, QITAO and SUN, HONGJIAN, 2018. A cognitive radio enabled smart grid testbed based on software defined radio and real time digital simulator In: 2018 IEEE International Conference on Communications Workshops (ICC Workshops). 1-6
• YOU, MINGLEI, JIANG, JING, TONELLO, ANDREA M, DOUKOGLOU, TILEMACHOS and SUN, HONGJIAN, 2018. On statistical power grid observability under communication constraints IET Smart Grid. 1(2), 40-47
• YOU, MINGLEI, 2018. On Statistical QoS Provisioning for Smart Grid
• YOU, MINGLEI, HUA, WEIQI, SHAHBAZI, MAHMOUD and SUN, HONGJIAN, 2018. Energy hub scheduling method with voltage stability considerations In: 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops). 196-200
• YOU, MINGLEI, LIU, QITAO and SUN, HONGJIAN, 2017. New communication strategy for spectrum sharing enabled smart grid cyber-physical system IET Cyber-Physical Systems: Theory & Applications. 2(3), 136-142
• LIU, QITAO, YOU, MINGLEI, SUN, HONGJIAN and MATTHEWS, PETER, 2017. L-index sensitivity based voltage stability enhancement In: 2017 IEEE 85th Vehicular Technology Conference (VTC Spring). 1-5
• YOU, MINGLEI, LIU, QITAO, JIANG, JING and SUN, HONGJIAN, 2017. Power grid observability redundancy analysis under communication constraints In: 2017 IEEE/CIC International Conference on Communications in China (ICCC). 1-5
• YOU, MINGLEI, SUN, HONGJIAN, JIANG, JING and ZHANG, JIAYI, 2016. Unified framework for the effective rate analysis of wireless communication systems over MISO fading channels IEEE Transactions on Communications. 65(4), 1775-1785
• YOU, MINGLEI, SUN, HONGJIAN, JIANG, JING and ZHANG, JIAYI, 2016. Effective rate analysis in Weibull fading channels IEEE Wireless Communications Letters. 5(4), 340-343
• YOU, MINGLEI and SUN, HONGJIAN, 2016. Realising energy-aware communication over fading channels under QoS constraints In: 2016 IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB). 1-4
• YOU, MINGLEI, MOU, XIAOLIN and SUN, HONGJIAN, 2015. Effective capacity analysis of smart grid communication networks In: 2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD). 196-200
• YOU, MINGLEI and JIANG, TING, 2014. New method for target identification in a foliage environment using selected bispectra and chaos particle swarm optimisation-based support vector machine IET Signal Processing. 8(1), 76-84