Arrykrishna Mootoovaloo is a quantitative researcher in London who develops probabilistic and machine learning models, with work spanning cosmology, generative AI and energy markets. Before moving into industry, he was a Research Fellow at the University of Oxford, developing deep learning and probabilistic models to accelerate scientific computation. He completed his PhD at Imperial College London, specialising in statistical machine learning, where his research focused on building Gaussian Process emulators to accelerate computationally expensive calculations in cosmology.
Professional Experience
Quantitative Researcher · Fuse Energy
- Build commodity hedging models, validated with a robust backtesting framework.
Quantitative Researcher (Intern) · Qube Research & Technologies
- Built a deep learning pipeline for hidden-signal detection with turnover control.
Research Fellow · University of Oxford
- Developed probabilistic ML for fast inference and supervised 4 summer interns.
Research Scientist (Intern) · Huawei Research & Development
- Researched interactive AI and built an API for diffusion-based image editing.
Postdoctoral Researcher · University of Oxford
- Applied machine learning to find unusual astronomical objects.
Data Scientist · Metrixs
- Built machine learning models for consumer and psychometric data.
Data Scientist · Arcturus
- Built a company-rating methodology, plus NLP and geospatial data tools.
Skills
- Quantitative research
- Commodity hedging, Monte Carlo simulation of forward and spot prices, forward-curve construction, backtesting, turnover control.
- Machine learning
- Deep learning, normalising flows, Gaussian processes, diffusion models, emulation of expensive simulations.
- Statistics
- Bayesian inference, MCMC and gradient-based sampling, model selection, uncertainty quantification.
- Tools
- Python, PyTorch, JAX, NumPy, SciPy, pandas.
Education
PhD in Physics · Imperial College London
Weak lensing, data compression and Gaussian processes, at the Imperial Centre for Inference and Cosmology (ICIC). Supervised by Alan Heavens, Andrew Jaffe and Florent Leclercq.
MSc in Astrophysics and Space Science · University of Cape Town
Research project on Bayesian statistics and radio astronomy at AIMS, through NASSP.
BSc (Hons) Physics with Computing · University of Mauritius
Final-year project on X-ray cavities (project overview).