At NITI Aayog, I researched AI self-governance frameworks and incentive-based policy design, and contributed to briefs on responsible AI deployment, public AI literacy, and industry-academia collaboration. I also assessed international AI regulatory models for their applicability to India.
At OptAlpha, I engineered a financial dataset with more than 600,000 OHLC and volume entries, researched market patterns, and applied K-Means clustering to candlestick patterns. I also built visualizations to communicate trading insights.
In my speech LLM project, I introduced query repetition for multimodal speech inputs, achieving a 7.4% relative WER improvement without architectural changes. My work spans machine learning, AI governance, and applied data science, including a policy white paper on incentivizing AI governance in India.
