Doctor of Philosophy (PhD)
University of Bath
Topic: Power System Reliability
About Me
I am a PhD Student at the University of Bath, building on my previous MPhil from Royal Holloway, University of London. My research focuses on power systems, battery energy storage systems (BESS), and machine learning enabled decision support for energy system operations and planning.
I’m particularly interested in Power System Reliability, Optimal Power Flow (OPF/SCOPF), and Explainable AI (XAI) for intelligent contingency screening. My work combines data-driven learning with physically interpretable models to improve grid resilience, flexibility, and transparency.
This research supports UN Sustainable Development Goal 7: Affordable and Clean Energy, and the wider transition toward smarter, more efficient energy systems.
Alongside the research I work as a full stack developer across two part-time roles, building agentic AI solutions and web applications. Earlier, as Technical Lead for Machine Learning at HCL Technologies, I took ML features into production products.
Bilal Ahmad
Education
Master of Philosophy (M.Phil)
Royal Holloway University of London
Topic: Power System Optimisation Using Machine Learning
DTU PES Summer School 2026
Technical University of Denmark
Topic: Enhancing Power Distribution System
Reliability with Machine Learning
M.Tech Thesis
RWTH Aachen University
Topic: System Level Control of Inverters in DC Microgrid
Master of Technology (M.Tech)
IIT Roorkee
Electrical Power Systems
First Division with Distinction
Bachelor of Technology (B.Tech)
Aligarh Muslim University
Electrical Engineering
First Division
Skills Stack
Power systems research, applied machine learning, and the software that connects the two.
Power Systems
Modelling and optimising distribution networks reliability and uncertainty.
What I work on
- Optimal power flow: OPF and SCOPF
- Energy Systems Modelling
- Power electronics modelling
- Control system modelling
Libraries and solvers
- Pyomo
- PandaPower
- MATPOWER
- Gurobi
- Ipopt
Machine Learning
Designing domain-specific models, from PS optimisation to production features.
What I work on
- Explainable AI
- ML-based power system analysis
- Computer vision
- OCR, handwriten text extraction
Libraries
- Scikit-learn
- TensorFlow
- PyTorch
- huggingface-hub
- Pandas
- NumPy
Software Engineering
Building the tooling around the research, and the software infrastructure to deploy it.
What I work on
- Automated Power Systems frameworks
- Reproducible experiment pipelines
- Agentic AI based solutions
- Full-stack web development
Languages
- Python
- MATLAB
- Java
- JavaScript
- HTML
- CSS
Recognition
Fellowships
- URSA Fellowship Funded by the University of Bath, United Kingdom
- DAAD Fellowship Funded by the BMZ, Deutschland
- LSC Fellowship Funded by the University of London, United Kingdom
- MHRD Fellowship Funded by the Ministry of Human Resource Development, India
Award
Third Best Paper icSmartGrid 2025 — Glasgow, UK
Projects
- Power System Reliability in Adverse Weather Events
- Automated Procurement Framework for DNOs
- System-Level Control of Inverters in DC Microgrids
- Multilevel Inverter with MPP Tracking