United Kingdom
I’m a research scientist at Meta, applying machine learning to improve ads targeting at scale. Previously, I worked on causal and agentic AI at a startup. I completed my PhD at Imperial College London, developing data-driven optimization for interconnected industrial systems in the OptiML PSE lab under the supervision of Dr. Antonio del Rio-Chanona and Prof. Nilay Shah. Always keen to connect on ML, causality, and optimization in large-scale settings under organizational constraints.
Applied research to drive AI agent and causal AI product offerings, focusing on evaluation and guardrailing efforts.
Reinforcement Learning for combinatorial optimization in middle-mile network design
• Continued my work with Dr. Zoltán Kís and Prof. Nilay Shah from my previous UROP and research project • Implemented a statistical model in Python to quantify RNA sequence identity • Compared data-driven and mechanistic approaches to RNA transcription design space creation • Worked towards an integrative Quality by Design framework for quick model building and design space creation in gProms and Python
Worked in a team on the competitive intelligence of European steam cracker sites • Used engineering and logistics considerations to estimate competitors’ steam crackerfeed slates and cost competitiveness • Assessed how European petrochemical companies are positioning themselves in the sustainability landscape • Analysis is used in-house in the European olefins market outlook to assist strategic planning