Fascinated with the intersection of AI, innovation, and intuitive explanations
Passionate about translating highly technical information into easily understandable forms
Believes it is ethically imperative that increasingly complex systems are understood by all affected individuals, regardless of technical training
Current research focuses on interpretable machine learning to generate human-understandable explanations of black-box models
Actively involved in the entrepreneurship community, exploring commercialization opportunities, fault-tolerant ML UX, and real-world ML solution innovations