Sahil is an AI researcher and innovator with over three years of experience pioneering solutions in optimisation, safety, and responsible AI. His research on making large language models more self-aware and trustworthy includes over ten presentations at leading NLP venues such as NAACL, ACL, IASEAI and IEEE, showcasing new methods that reduce hallucinations by up to 20% and improve AI self-awareness by nearly 37% for safer responses. He has received over $7500 in fellowships and grants over the years for his impactful research.

Beyond his industrial work, Sahil loves bridging cutting-edge research with real-world impact, from designing an AI-powered geodatabase of 700,000 healthcare facilities that helps 1.4 billion people access emergency care in India to a fairness-driven AI algorithm for electoral boundary mapping to ensure free and fair elections. His experience as a guest researcher at TU Eindhoven and UC Irvine has shaped a truly global perspective on trustworthy and efficient AI design.

Driven by a vision to make AI safe, and impactful, Sahil continues to develop scalable frameworks that combine technical innovation with social responsibility ensuring AI systems serve humanity truthfully and with utmost safety.