Nilesh Ramgolam is an MPhil researcher at the Australian Institute for Machine Learning (AIML), University of Adelaide, specializing in reinforcement learning, human-in-the-loop AI, and large-scale computation. His recent work, “Enhancing Medical Decision-Making with Machine Learning,” explores how AI systems can learn to defer to human expertise with limited demonstrations, bridging human judgment and autonomous decision-making. Beyond research, Nilesh is deeply engaged in teaching computer science and software engineering, developing robust learning materials and automated grading systems. He also has extensive experience with high-performance computing (HPC) pipelines for large-scale virtual screening and generative drug discovery, leveraging GPU clusters and distributed systems to accelerate experimentation. Driven by curiosity and purpose, Nilesh is passionate about using AI to solve real-world problems that advance accessibility, trust, and economic empowerment.…Nilesh Ramgolam is an MPhil researcher at the Australian Institute for Machine Learning (AIML), University of Adelaide, specializing in reinforcement learning, human-in-the-loop AI, and large-scale computation. His recent work, “Enhancing Medical Decision-Making with Machine Learning,” explores how AI systems can learn to defer to human expertise with limited demonstrations, bridging human judgment and autonomous decision-making. Beyond research, Nilesh is deeply engaged in teaching computer science and software engineering, developing robust learning materials and automated grading systems. He also has extensive experience with high-performance computing (HPC) pipelines for large-scale virtual screening and generative drug discovery, leveraging GPU clusters and distributed systems to accelerate experimentation. Driven by curiosity and purpose, Nilesh is passionate about using AI to solve real-world problems that advance accessibility, trust, and economic empowerment.WWWW…