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 aims to combine data-driven learning with physically interpretable models to enhance grid resilience, flexibility, and transparency.

This research aligns with UN Sustainable Development Goal 7: Affordable and Clean Energy, contributing to the global transition toward smarter, more efficient, and sustainable energy systems. I’m passionate about applying advanced computational techniques to support reliable and clean power networks of the future.

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Bilal Ahmad

URSA Fellow | DAAD Fellow | LSC Fellow | MHRD Fellow

Education

Doctor of Philosophy (PhD)
University of Bath
Topic: Power System Reliability
Master of Philosophy (M.Phil)
Royal Holloway University of London
Topic: Power System Optimisation Using Machine Learning
Visiting Researcher
DTU PES Summer School,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

Development

I am developing an automated framework of optimal procurement strategy for the Distribution Network Operator (DNO).

Things I enjoy developing:

Power System Security Models, Optimization Models, OPF models, Power Flow, Distribution System Modelling, Power Electronics Modelling, Control System Modelling.

Modules familiar with:

Pyomo, PandaPower, MATPOWER, Ipopt, Gurobi, SciPy, Pandas, NumPy, Matplotlib

Coding

As a Technical Lead at HCL, we added ML capabilities to existing products.

Languages:

MATLAB, Python, Java, HTML, CSS, JavaScript

Products Developed:

  • Handwritten Text Extraction
  • OCR
  • Catalogue Tagging
  • Sales Forecasting
  • Document Digitalisation
  • Image Noise Removal
  • ML Based Power Flow Analysis
  • Fully Automated OPF Framework
  • Fully Automated SCOPF Framework

Fellowships & Projects

Fellowships:

URSA Fellowship

LSC Fellowship

DAAD Fellowship

MHRD Fellowship

Awards:

Third Best Paper Award in icSmartGrid 2025, Glasgow, UK

Projects:

  • Power System Reliability in Adverse Weather Events
  • Automated Framework for DNO
  • System Level Control of Inverters in DC Microgrid
  • Multilevel Inverter with MPP Tracking