SystemsML
Project Overview
University
Year
About
Power generation and heavy industry produce much of the world’s greenhouse gas emissions, yet replacing existing power plants and industrial facilities will take decades. Conventional control systems are designed for predictable operating conditions and can perform poorly when fuels, loads or equipment conditions vary. SystemsML combines machine learning with digital models that account for this uncertainty, providing recommendations suited to real-world operating conditions. Verified deployments indicate substantial emissions reductions and cost savings without new physical infrastructure. The platform could help existing industrial assets operate more efficiently while supporting energy security and near-term decarbonisation.
Team
Waqar Muhammad Ashraf
Dr Waqar Muhammad Ashraf is a Postdoctoral Researcher at the University of Cambridge and Founder of SCALE Lab, with a PhD from University College London. His work develops safe, scalable AI for energy, chemical processing and manufacturing, translating advanced modelling and optimisation into practical decision-support tools for economic gains and environmental sustainability. His research has developed robust digital twins and operator-centred AI systems, with applications spanning to gas power plants and oil & gas sector. Combining academic research with 5.5 years of industrial experience, Dr Ashraf focuses on turning AI research into deployable technologies for economic gains and environmental sustainability.
Muhammad Irfan
Software Engineering & Deployment MSc Artificial Intelligence & Data Science, University of Hull – BSc Software Engineering Muhammad Irfan is a full-stack developer and solutions architect with expertise spanning front-end systems, back-end services, mobile applications, and cloud infrastructure. He leads software engineering, deployment, and integration for SystemsML, an AI-powered process control platform for safety-critical industries.
Talha Ansar
Talha Ansar is a Mechanical Engineering graduate from the University of Engineering and Technology (UET) Lahore and a researcher working at the intersection of trustworthy AI, process systems engineering, and industrial energy optimisation. He has contributed to research with University College London and The Alan Turing Institute, developing domain-consistent & enforced machine-learning and optimisation frameworks for large-scale energy systems. His work has appeared in journals including Energy and AI and Water Research and has been presented at international venues including NeurIPS and ESCAPE.