Join iMAGiNE and the Chandra Family Department of Electrical and Computer Engineering for the iMAGiNE Symposium 2026. We are excited to be joined by AMD CTO, Mark Papermaster for our Keynote and Fireside Chat.
The iMAGiNE Consortium provides tools, methodologies, and knowledge for engineering the machines that support intelligent applications, from the smallest circuits to the largest systems. Prospective industry members and The University of Texas at Austin faculty, students, and alumni are welcome to attend!
Registration & Networking Breakfast: 8:30 - 9:00 AM, EER 0.804 (Mulva Foyer)
Welcome Remarks: 9:00 - 9:15 AM, EER 0.904 (Mulva Auditorium)
Roger Bonnecaze, Dean, Cockrell School of Engineering
Diana Marculescu, Chair, Chandra Family Department of Electrical and Computer Engineering
Opening Keynote: 9:15 - 10:00 AM, EER 0.904 (Mulva Auditorium)
Mark Papermaster, CTO, AMD
-- Enabling Efficient AI: Together We iMAGiNE --
AI is rapidly becoming pervasive—from the data center to the edge, to scientific research labs—unlocking new applications, productivity gains, and national-scale infrastructure. But this growth is colliding with a power wall. In this keynote, AMD CTO Mark Papermaster will share how constant innovation and holistic design, spanning chiplet-based modularity, rack-scale system design, and co-optimized software, can deliver step-function gains in compute efficiency and scalability. He will also look ahead to emerging frontiers, including new forms of acceleration like quantum, and highlight AMD’s role in advancing open ecosystems, embedded AI platforms, and deep partnerships with academia and industry.
Fireside Chat: 10:00 - 10:30 AM, EER 0.904 (Mulva Auditorium)
Diana Marculescu, Mark Papermaster
Panel: 10:30 - 11:30 AM, EER 0.904 (Mulva Auditorium)
-- Efficient AI at Scale --
As AI systems proliferate across the edge-cloud continuum, achieving efficiency at scale has become a defining challenge. This panel explores how AI performance and accuracy, energy consumption, and total cost of ownership intersect across edge devices and cloud data centers, where scaling AI often demands enormous infrastructure and power. The panel also uncovers a core tension of efficiency: as AI systems become more efficient and accessible, Jevons Paradox suggests that usage may expand dramatically, amplifying demands on datacenter and edge infrastructure while raising deep implications for privacy and trust. Panelists will debate how to balance efficiency-driven scale with safeguards that ensure trustworthy AI deployment across the edge and cloud.
Student Demos: 11:30 AM - 12:00 PM, EER 0.904 (Mulva Auditorium)
Join us for this session showcasing hands-on innovations in efficient AI systems for real-world deployment! The demos feature topics ranging from energy-harvesting platforms running AI for personal health and wellness, to small-footprint, low-power AI systems for embodied intelligence and robotics operating under tight energy and resource constraints.
Networking Lunch & Student Poster Session: 12:00 - 1:30 PM, EER 0.804 (Mulva Foyer)
Members Only Session: 1:30 - 3:00 PM, EER 0.806/0.808 (Multipurpose Room)