Professional Experience

Leading the application of machine learning and analytics for the structuring and valuation of natural gas and LNG structured assets and long-term bilateral deals.

Led Deep Hedging (Equity Derivatives) within the Machine Learning Centre of Excellence.

• Delivered over 2x training performance improvement

• Developed working model for transitioning research code to resilient production systems

• Mentored junior Quantitative Researchers and ML Engineers

Led large-scale compute optimisation for risk pricing by designing tokenisation-based data pipelines and applying NLP-driven preprocessing to improve throughput and resource utilisation.

• Accelerated inference for ML models (10s of µs) on a separate optimisation programme

• Implemented privacy-preserving machine learning practices

Firmwide AI Research - Synthetic data generation for privacy preserving machine learning

Data Efficient Reinforcement Learning with Gaussian Processes

Inference in high dimensional state space models

Applied data fusion and machine learning algorithms for predicting dike stability using pressure and temperature sensors. Sensor data was obtained from EU urban flood management program.

Simulation, modelling and characterization of silicon based Single Photon Avalanche Detectors (SPAD) for CERN and TIFR, Ooty labs.

Worked as a design engineer for Nortel Networks digital telephone systems. Managed a hardware product design cycle spread over 9 months and 3 continents from concept to field trials.