Rajiv Chaitanya Muttur
Applied ML Researcher | Reinforcement Learning & Financial Systems
Bengaluru, India
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Rajiv Chaitanya is an applied machine learning researcher who enjoys taking models out of papers and stress-testing them against reality. His work focuses on reinforcement learning, financial ML, and reproducible ML systems, with a particular interest in understanding where sophisticated methods actually help, and more importantly, where they quietly fail.
He builds end-to-end learning pipelines that account for real-world constraints such as risk, non-stationarity, and system trade-offs, rather than optimizing purely for benchmark performance. Rajiv is especially interested in failure modes, design decisions, and lessons learned when ML systems meet noisy, imperfect data.
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Rajiv Chaitanya Muttur
Applied ML Researcher | Reinforcement Learning & Financial Systems
Bengaluru, India
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