Inviting reflections on how curiosity shapes flexible thinking, creativity, and problem-solving, the Indian Institute of Technology Gandhinagar hosted the Curiosity Conference 2026 on March 21–22. The third edition of the conference brought together scholars, scientists, artists, engineers, and school students to foster interdisciplinary dialogue. This year’s theme was at the intersection of art, science, and technology. The discussions focused on how education should focus on exploration-driven learning. Workshops, a poster session, hands-on activities, and panel discussions provided the platforms to participants for understanding that curiosity is a necessity that equips us to navigate an ever-evolving world.

At Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences, Yongtao Liu is building AI-driven “closed-loop” nanomaterials experiments that can plan measurements, interpret results in real time and choose the next step — accelerating discovery without removing human judgment. His focus is not just speed but trustworthy autonomy: systems must be interpretable, resilient to instrument artifacts and designed to avoid “false novelty,” where noise masquerades as new physics. Drawing on work such as novelty detection in conductive AFM studies of halide perovskites — linking local microstructure to unusual hysteresis behavior — Liu emphasizes that autonomous labs also demand better methods to validate and understand the massive data they produce. He is developing practical tools like AEcroscopy to standardize automated microscopy workflows and a Gated Active Learning Framework to prevent models from confidently learning from out-of-assumption data, while also pushing cross-facility autonomy that links fast measurements with slower synthesis. Ultimately, Liu envisions AI that helps scientists reason and explore vast experimental spaces — freeing researchers from repetitive tasks so they can focus on asking sharper questions.