Sahil Kale

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, 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 $5000 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 ethical and efficient AI design. Driven by a vision to make AI efficient, ethical, 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.