Georgia Institute of Technology

The program centers on “Trusted Sustainable Silicon Intelligence from Edge to Cloud,” with plenary papers and parallel technical presentations. Technical areas include analog circuits, data converters, digital circuits and architectures, image sensors and displays, medical circuits, memory, power management, RF and wireless systems, security, technology directions, and wireline. Tutorial topics include circuit design for autonomous vehicles, switched-capacitor power converters, adaptive clocking, time-domain ADCs, machine-learning accelerators, energy-harvesting sensors, mm-wave local-oscillator techniques, analog design automation, radar and sensing, and die-to-die interfaces. Six Advanced-Circuit-Design Forums address AI and HPC co-design; high-speed wireline data converters; electrical and optical connectivity; AI-optimized sensing; circuits for 6G communication, sensing, and edge AI; and silicon systems for quantum sensing and computing. Other program elements include “The Analog Renaissance: Can Unconventional Physical Computing and Optical Interconnects Define the Next Strategic Leap?”, a Student Research Preview with work-in-progress presentations and posters, an invited industry track on commercial chips and systems for AI training and inference, and demonstration sessions. The short course covers hardware security, including cryptographic architectures, hardware attacks and chip-level countermeasures, and hardware roots of trust. Plenary speakers include Marco Pieters, Executive Vice President and Chief Technology Officer at ASML, and Matt Murphy, Chairman and CEO of Marvell.

Under the theme “Chemical Engineering Reimagined,” the meeting covers chemical-engineering research, technologies, and emerging growth areas. Program guides highlight AI and machine learning, climate change, industrial careers, and early-career faculty. The AI and machine-learning program includes sessions on process development; polymer simulation, informatics, and data analytics; data-driven pharmaceutical process controls; AI-enabled process design, scale-up, and workforce readiness; nuclear chemical engineering; manufacturing-system modeling; computational catalysis; digital twins in energy systems; biomass utilization; and data-driven medicine. Featured discussions consider digital transformation, evolving industrial ecosystems, sustainability pressures, and changing workforce expectations, as well as ways to incorporate data science into chemical-engineering curricula, degree programs, certificates, and teaching of statistics and programming. Featured lectures address chemical engineers’ roles amid advances in AI, sustainable energy, and an interconnected global economy, and the use of catalysis to convert biomass, CO2, and end-of-life polymers into fuels, chemicals, and materials. Other lecture themes include carbon circularity, process intensification, renewable hydrogen, and pathways toward net-negative carbon manufacturing.