Intelligent Battery Monitoring
AI-driven battery health and performance monitoring system for smart energy applications.
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1 min read
10
Project showcases
10+
Industrial stakeholders
£5.9M
Programme-scale funding
14+
Current postgraduate researchers
Flagship Projects
Our current portfolio focuses on demonstrable engineering outcomes, from energy hubs for rail and transport networks to AI-enabled battery diagnostics and integrated smart energy platforms.
Multi-Energy Hub
Building multi-energy hubs that integrate renewables, grids and transport networks to enable green mobility and low-carbon power systems.
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1 min read
Optical Fibre Sensing System
An AI-orchestrated data analytics platform for optical fibre sensing and environmental monitoring.
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1 min read
Smart Energy Systems
Creating intelligent energy systems that drive net-zero transition via multi-energy hubs, modular design, and AI monitoring.
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1 min read
NeuroLink AI: Next-Generation Brain-Computer Interfaces
Developing AI-powered brain-computer interfaces that can decode complex neural signals to restore mobility and communication for patients with neurological disorders.
Dr. sarah kim
QuantumML: Machine Learning for Quantum Materials Discovery
Accelerating the discovery of quantum materials for next-generation electronics and energy technologies through machine learning-guided computational design.
Maria rodriguez
MoleculeAI: Machine Learning Platform for Drug Discovery
An integrated AI platform for accelerating small molecule drug discovery through advanced machine learning models, molecular simulation, and experimental validation.
DeepFold: AI-Powered Protein Structure Prediction
Developing next-generation deep learning models to predict protein structures with unprecedented accuracy, accelerating drug discovery and understanding biological mechanisms.
CancerSeq AI: Precision Oncology Through Genomic Analysis
Leveraging AI and single-cell genomics to identify personalized treatment strategies for cancer patients, focusing on tumor heterogeneity and drug resistance mechanisms.
ClimateAI: Machine Learning for Climate Prediction & Mitigation
Advancing climate science through machine learning to improve prediction accuracy, understand extreme weather patterns, and accelerate carbon capture technology development.
Dr. elena vasquez
Research Focus Areas
Institute of Communication and Power Networks
Each research area supports a live project pipeline, connecting modelling, sensing, optimisation, and system deployment across infrastructure and energy applications
Active
Smart Energy Systems
Battery management, railway energy hubs, microgrids, EV charging, and district heating decarbonisation in whole-system energy settings
Microgrids
Battery Management
Rail Electrification
+2 more
12
team
50+
papers
EPSRC, Ofgem, National Grid
funding
Active
Communication Networks & Systems
Energy-efficient optical communications, network architectures, and systems research developed in collaboration with major telecom stakeholders
Optical Networks
Energy Efficiency
Network Systems
+2 more
8
team
40+
papers
EPSRC Programme Grant
funding
Emerging
Wireless Communications, Control & AI
Wireless systems, sensing, nonlinear modelling, model predictive control, and physics-informed AI for complex engineering applications
Wireless Communications
Control Systems
Physics-Informed AI
+1 more
6
team
28+
papers
UKRI and industry partners
funding
Smart Energy Systems
This project develops integrated smart energy architectures that connect power, transport, and industrial systems. It focuses on modular infrastructure, coordinated control, and whole-system optimisation to support deep decarbonisation.
- Integration across energy, transport, and manufacturing
- Modular design and power buffering for scalable deployment
- Coordinated communication and control for resilient operation
Intelligent Battery Monitoring
This project applies intelligent algorithms to monitor battery health and lifespan in real time. It supports energy storage reliability, predictive maintenance, and operational safety in renewables and electric mobility applications.
- Temperature, voltage, and cycling data acquisition
- Machine-learning based degradation and failure prediction
- Real-time battery status visualisation and analytics
Multi-Energy Hub
This flagship project explores how multi-energy hubs can connect renewables, traction networks, utility grids, and transport demand at scale. It is designed around practical deployment scenarios for greener mobility and future low-carbon power systems.
- 2,500+ potential sites across the UK rail network
- 10,000+ miles of rail context for infrastructure integration
- Whole-system planning, optimisation, and renewable interfacing
Meet Our Team
Researchers across smart energy, communications, and intelligent systems
Our team brings together expertise in energy systems, communication networks, wireless technologies, control engineering, and AI within the School of Electronic and Electrical Engineering.
Principal Investigators
Evan
Principal Investigator & Lab Director
Leading research in computational biology and machine learning applications to scientific discovery.
Machine Learning & AI
Computational Biology
Drug Discovery
Postdoctoral Researchers
Dr. Alex Wong
Postdoctoral Researcher
Applying computational methods to understand cellular mechanisms and develop therapeutic strategies.
Systems Biology
Network Analysis
Drug Repurposing
Dr. Michael Chen
Postdoctoral Researcher
Developing deep learning models for protein structure prediction and drug discovery.
Deep Learning
Protein Folding
Drug Discovery
PhD Students
Emily Davis
PhD Student (2nd Year)
Exploring neural network architectures for biological sequence analysis and prediction.
Neural Networks
Sequence Analysis
Natural Language Processing
Sarah Johnson
PhD Student (4th Year)
Investigating machine learning applications in genomic medicine and personalized healthcare.
Genomic Medicine
Machine Learning
Precision Medicine
Recent Publications
(2019).
An example preprint / working paper.
(2015).
An example journal article.
Journal of Source Themes, 1(1).
(2013).
An example conference paper.
In ICW.
Featured Research
An example preprint / working paper
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An example conference paper
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Events
Stay connected with our research community through talks, workshops, and collaborative events
Keynote: AI for Scientific Discovery
Keynote presentation on machine learning applications in computational biology and drug discovery.
Monthly Lab Seminar: Recent Advances in Quantum Materials
Dr. Maria Rodriguez presents recent breakthroughs in quantum materials discovery using machine learning.
Maria rodriguez
Hands-On Workshop: Machine Learning for Computational Biology
Interactive workshop teaching ML techniques for genomic data analysis and protein structure prediction.
Lab News & Updates
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Collaborators & Partners
Leading the way together
We work with universities, infrastructure operators, and industry partners to accelerate innovation in energy, communications, and intelligent engineering systems
Contact Us
Institute of Communication and Power Networks
Find Us
Professor Kang Li
Chair in Smart Energy Systems
Room 3.56, School of Electronic and Electrical Engineering
University of Leeds
Leeds, LS2 9JT
United Kingdom
Office Hours
Monday - Friday: 9:00 AM - 5:00 PM
Prospective PhD and collaboration enquiries are welcome by email
Connect With Us
Prospective Members
Interested in PhD study or research collaboration in smart energy, communications, control, and AI? Contact Professor Kang Li or view current opportunities.
View Open PositionsJoin Our Research Team
We welcome enquiries from strong applicants interested in PhD study, visiting research, and collaborative projects in smart energy systems, communication networks, wireless communications, control, and AI at the University of Leeds.