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• I am a Machine Learning MSc graduate student and Google DeepMind Scholar at the University College London, specializing in learning algorithms and Financial Machine learning. Previously, I worked as an ML Architect in Ford GDIA's Independent Model Validation team, where I developed and validated Statistical and interpretable Machine learning models for Ford Credit at a global scale. Prior to this role, I served as a Quantitative Researcher at Trexquant Investments LLP (AUM$2B), applying quantitative and ML methods to build optimized equity portfolios in liquid markets.


• I am a recipient of the prestigious Endeavour research fellowship awarded by the Australian government and CRISIL's Best Doctoral Research Award in Investment Management (AI in Finance-Track). I hold a Ph.D. in Computational Finance from IIT Madras. My research work was supervised by Prof. M. Thenmozhi (IIT Madras). My thesis chapters are published in prestigious journals like European Financial Management, Finance Research Letters, Research in International Business and Finance, Carbon Management and Decision. My dissertation focused on focused on building statistical and ML models aimed at addressing the longstanding enigma in finance—how to explain merger waves? My Co-authors are Dr.Chinmoy Ghosh (University of Connecticut), Dr.MayHu (RMIT University), Dr.Robert Faff (University of Queensland), Dr.Syed Shams (University of Southern Queensland) and Dr.Veerasamy Sejian (University of Queensland)


• My recent research centers on the application of Deep Learning to Asset Pricing, with a specific focus on the generation of synthetic assets through adversarial methods. This approach is designed to test and enhance the model’s precision in forecasting actual market conditions. Demonstrated ability to solve complex problems using software such as Python, Stata, SAS, and Mathematica, with expertise in finance libraries (Pyfolio, Riskfolio), ML and DL libraries (PyTorch, Scikit-learn, Keras, TensorFlow, Pandas, NumPy), Explainable NN libraries (GamiNet), RL libraries (OpenAI Gym) and Survival Libraries (Scikit-survival, lifelines, pycox).


• Living in London, my spare time is often spent writing a blog focused on Learning Algorithms, and High-performance python codes. This blog is titled 'Probably Approximately Correct' , a tribute to the book written by my favorite Prof.Leslie I enjoy trekking and volunteering to teach math and computing to tribal girl children through the Tinklesevaa classroom sessions. Through my sketches, I actively promote diversity and inclusion. Feel free to explore my Behance profile or gallery section to see my artworks.