Title: Edge AI Acceleration: From Efficient Models to Efficient Circuits
Date: Monday, August 3, 2026
Time: 2:00 p.m. - 3:00 p.m.
Location: Marcus Nano, Conference Room 1117-1118

Abstract: In the landscape of Artificial Intelligence (AI), two complementary paradigms have emerged: cloud AI, which relies on centralized computing infrastructure, and edge AI, which performs intelligence directly on distributed devices at the network edge. Driven by the rapid growth of wearables, drones, and other Internet-of Things (IoT) devices, edge AI is increasingly pervasive and transforming the way intelligent services are delivered in everyday life.

This talk will focus on two key components of the edge AI design stack that critically influence the performance and energy efficiency of AI acceleration. First, we will discuss hardware-aware Neural Architecture Search (NAS), an automated framework for jointly optimizing neural network architectures and computing architectures for target workloads and deployment constraints. We will then explore recent advances in digital Compute-In Memory (CIM) and Compute-In- Logic (CIL) circuits, highlighting how architectural and circuit-level innovations can substantially improve the efficiency of AI computation. Finally, we will share how these approaches could potentially provide a practical pathway toward energy-efficient AI systems for next-generation edge platforms.

Bio: Bo Wang received the Ph.D. degree in electrical and electronic engineering from Nanyang Technological University, Singapore. In 2020, she joined Singapore University of Technology and Design, Singapore as an Assistant Professor. Her research interests span various aspects of energy-efficient architecture and circuit design, including machine learning acceleration, neuromorphic computing, compute- in-memory, and design automation for hardware-software co-optimization. She authored and co-authored many papers published at international journals and conference proceedings, including TNNLS, JSSC, TCAS-I, A-SSCC, DAC, ISLPED, etc.\

Prof. Wang received the Distinguished Design Award at the IEEE Asian Solid-State Circuits Conference (A-SSCC) in 2023.She was also a recipient of the Best Paper Award at the ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED) in 2023 and the International SoC Design Conference (ISOCC) in 2024 and 2014. She is an IEEE senior member.