Apr 2025 – Oct 2025 · 6 mos · San Francisco, California, United States · Hybrid

Feb 2024 – Apr 2025 · 1 yr 2 mos · San Francisco, California, United States · Hybrid

• Synthetic data research
• Evaluation and benchmarking
• Adversarial research and red teaming
• MultiChallenge: A Realistic Multi-Turn Conversation Evaluation Benchmark Challenging to Frontier LLMs
• (ACL 2025) https://arxiv.org/abs/2501.17399
• FORTRESS: Frontier Risk Evaluation for National Security and Public Safety
• https://arxiv.org/pdf/2506.14922

Aug 2021 – Dec 2023 · 2 yrs 4 mos

• Scaled AUM from ₹50M to ₹100M while architecting cutting-edge quant systems—from LLM-powered dashboards and earnings-call AI pipelines to backtesting 50+ high-alpha strategies and executing 100K+ trades across top brokers.

Sep 2020 – Feb 2021 · 5 mos

• Market-neutral medium to long-term frequency alpha generation through comprehensive academic research focused on traditional deep learning

Jul 2020 – Dec 2020 · 5 mos

• Bachelors thesis on the intersection of Signal Processing <> Portfolio Optimization, specifically how to apply LSTMs on MV-GARCH models for covariance matrices estimation ensuring optimal diversification.
• Under the guidance of Dr. AG Constantinides.

Jun 2020 – Aug 2020 · 2 mos

• 1) Working with Differential Machine Learning and using the same to approximate the Cheyette Model for forward interest rate predictions.
• 2) Using Reinforcement Learning to harvest the Volatility Risk Premia
• Under the guidance of Dr. Blanka Horvath.

Apr 2019 – Oct 2019 · 6 mos

• Designed alphas with 17-42% returns per year with Sharpe ranging in 3-5 and worked on avoiding overfitting. Implemented Price, Fundamental and other datasets, decay, neutralization, universe, turnover, drawdown. Worked with mean reversion, momentum and other common trading strategies using the 5-year data across USA, Asia and Europe markets.