2025 AAAI / ACM SIGAI Doctoral Consortium Interviews Compilation

Summary

The episode compiles interviews with 23 doctoral consortium participants, showcasing a wide spectrum of AI research—from kernel learning for time‑series forecasting and explainable AI for robotics and cyber‑physical systems, to privacy‑preserving generative models, bias mitigation in large language models, and AI‑driven drug discovery. Guests highlight practical impacts such as real‑time health monitoring, semiconductor metrology, human‑activity recognition, and AI‑assisted network operations, while also addressing broader trustworthy AI concerns like fairness, privacy, and regulatory compliance. Across the interviews, the common thread is the pursuit of responsible, interpretable, and human‑centered AI that can be deployed safely in diverse domains.