Duke’s Semiconductor Game Changers: Yiran Chen

In January 2026, a landmark gift from the Lamond Family named the Pierre R. Lamond Department of Electrical and Computer Engineering (ECE) at the Pratt School of Engineering. The $57 million in total investment strengthens Duke ECE’s ability to shape the next era of computing technologies and fuel the department’s rapid rise in research and academic distinction.

The department’s namesake, Pierre R. Lamond, helped pioneer the semiconductor industry and later invested in semiconductor, systems and software companies as a venture capitalist in Silicon Valley.

In this series, Duke Engineering highlights faculty members whose work in semiconductor‑related research is already making an impact, and who are now positioned to accelerate that work through the transformative commitment from the Lamond Family.

Yiran Chen is the John Cocke Distinguished Professor of Electrical and Computer Engineering at Duke. He directs the National Science Foundation’s AI Institute for Edge Computing Leveraging Next Generation Networks (Athena), one of 29 national AI institutes in the United States. His research focuses on emerging memory systems, neuromorphic computing and edge AI hardware; technologies that aim to bring computation closer to where data is generated while dramatically reducing energy consumption.

How does your research contribute to advances in semiconductor technology?

One of my research focuses is neuromorphic computing, which is a concept that rethinks how hardware is designed by drawing inspiration from the human brain. The brain is remarkably powerful and energy efficient, in part because it integrates memory and computation seamlessly.

At the device level, my lab works on emerging memory technologies like memristors, which are devices that can retain information similar to a brain synapse. These devices open the door to new semiconductor architectures. Developing these systems requires advances across devices, circuits and system design, and semiconductors are the foundation that makes this new class of computing possible.

What is one major technical challenge your work is helping to address?

One of the most significant challenges in modern computing is energy inefficiency. As AI models continue to grow, there will be a bottleneck in the data moving between memory and processors.

Our work addresses this issue by co-locating memory and computation at the hardware level. By reducing data movement, neuromorphic systems can perform complex AI tasks with a small fraction of the power needed today.

What new applications could be unlocked with improved semiconductor hardware in the near future?

Edge devices, so named because they sit at the edge of much larger networks, will be able to run more intelligent AI systems in situ directly on the devices in the future with advanced hardware. At the Athena Institute, one application we’re working on is autonomous drones that can assist in search-and-rescue emergency operations. With neuromorphic hardware, machines could learn from data in real time and respond instantly.

How has Duke ECE built momentum in semiconductor research in recent years?

Duke ECE has developed strong momentum by bringing together expertise in many areas across circuits, systems and AI. Through our collaborative institutes and projects, we can move ideas quickly from devices to real-world applications. Our strengths in neuromorphic computing and edge AI build directly on that foundation.

Why is this moment critical for investment and growth in semiconductor research?

The invention of the transistor reshaped society by enabling modern computing, and today we’re at a similar inflection point. AI is changing rapidly—and making incredible leaps—but it will soon push our existing hardware to the limit. We need to rethink computing from the ground up to define the future of intelligent systems.