Boundaries & Breakthroughs Panel Series | AI & High Performance Compute
Join the Institute for Matter and Systems for the first event in its new interdisciplinary panel series, featuring candid, cross-cutting conversations on the future of AI & High Performance Compute. This series gathers researchers from across disciplines to challenge assumptions, explore barriers, and imagine what it will take to turn promising prototypes into trusted, scalable solutions. Expect lively discussion that moves beyond the boundaries of any one field to uncover new questions, unexpected insights, and opportunities for collaboration.
Join us for the first session of the Boundaries & Breakthroughs panel series, where Georgia Tech researchers from across disciplines come together for candid, cross-cutting conversations on the future of AI & High Performance Compute.
This dynamic event will explore the evolving landscape of data infrastructure and artificial intelligence, challenging assumptions and uncovering the barriers that stand between promising prototypes and scalable, trusted solutions. Expect lively discussion that moves beyond the boundaries of any one field to spark bold ideas and unexpected insights at the intersections of materials, technology, and society.
Have a burning question or a unique perspective?
We invite attendees to submit questions in advance for our panelists to consider during the discussion. Whether you're curious about sustainability, ethics, scalability, or the future of AI-driven infrastructure, your input can help shape the conversation.
The conversation will explore topics such as:
- Expanding access to computational resources (foundation models and high-performance compute) for university researchers, enabling the design and validation of new materials, processes, and devices without reliance on massive proprietary datasets.
- Accelerating discovery through rapid in silico screening, optimization, and digital twin development.
- Advancing standardization and cross-disciplinary collaboration by providing transparent, adaptable models for specific applications.
Driving data-driven insights into complex phenomena, such as defect formation, material/interface stability, and device reliability, to advance the science of manufacturing and speed the development of next-generation semiconductors, materials, and process technologies.
On the panel:
Asif Khan, associate professor in the School of Electrical and Computer Engineering.
Moinuddin Qureshi, professor of Computer Science.
Suman Datta, Joseph M Pettit Chair of Advanced Computing and Georgia Research Alliance (GRA) Eminent Scholar and Professor in the School of Electrical & Computer Engineering.