Duy-Thanh Nguyen serves as a Postdoctoral Associate in the Electrical Engineering Department at Yale University. His research focuses on the design of energy and area-efficient memory architectures tailored for AI applications, as well as low-power AI accelerators. Nguyen earned his BS in Computer Engineering from Vietnam National University (Ho Chi Minh City) - University of Technology and subsequently completed a combined MS/Ph.D. program at Kyung Hee University in South Korea. Prior to his appointment at Yale, he was a Research Associate at the National University of Singapore. Outside of his professional endeavors, Nguyen is an avid fan of Japanese anime, YouTube, and Netflix. He relishes his time at Yale, attending numerous concerts hosted by the Yale School of Music and taking pleasure in feeding squirrels on the campus grounds. [E-mail: duy-thanh.nguyen@yale.edu]

Graduate Students

Youngeun Kim received his B.S. degree in Electronic Engineering from Sogang University, in 2018 and M.S. degree in Electrical Engineering from Korea Advanced Institute of Science and Technology (KAIST), South Korea, in 2020. Starting from September 2020, he is pursuing his Ph.D. in the Intelligent Computing Lab. Prior to joining Yale, he pursued an AI research internship at Kakao Corporation & SK-Tbrain, South Korea. He also did Applied Scientist internship at AWS AI (Seattle, WA). His research interests include novel algorithms for foundation models (e.g., CLIP, DINO-V2), computer vision, algorithm-hardware co-design, and emerging devices for deep learning. Outside of the lab, he likes working out, swimming and running. [E-mail: youngeun.kim@yale.edu]

Yuhang Li received his B.Eng degree in computer science from the University of Electronic Science and Technology of China (UESTC). He also worked as a research assistant at the National University of Singapore, SenseTime Research, and UESTC previously. Currently, he is pursuing his PhD degree at Yale University advised by Professor Priyadarshini Panda. He also did Applied Scientist internship at Amazon Lab126 (Sunnyvale, CA).  His research interests mainly focus on efficient deep learning systems, including network quantization, pruning, spiking, and efficient AI-Generated Content. His goal is to build trustworthy and deployable systems & algorithms for deep learning applications. Outside the lab, he likes lifting, cooking as well as driving.  [E-mail: yuhang.li@yale.edu]

Yeshwanth Venkatesha received his B.Tech. degree in Computer Science and Engineering from Indian Institute of Technology, Kharagpur, India in 2017. Prior to joining Ph.D. program at Yale, he has worked as a software engineer and data scientist at Samsung R&D institue & Walmart Labs, respectively, in Banglaore, India. He is fascinated by AI applications deployed in embedded devices like smartphones, self-serving cars, and automated drones. His research focuses on designing algorithms to enable efficient processing of state of the art AI solutions on resource-constrained devices. His current work at the Intelligent Computing Lab explores the feasibility of using novel neuromorphic learning paradigms in the context of Distributed Learning. Outside of the Lab, Yeshwanth enjoys reading novels, playing cricket and chess, and currently attempting to learn Spanish.  [E-mail: yeshwanth.venkatesha@yale.edu]

Shiting (Ginny) Xiao received her B.S. in Computer Science from the Chinese University of Hong Kong, Shenzhen, and M.S. degree in Robotics from University of Pennsylvania, GRASP Laboratory. Starting from September 2023, she is pursuing her Ph.D. in the Intelligent Computing Lab advised by Prof. Priyadarshini Panda. Prior to starting at Yale, she worked with Prof. Kostas Daniilidis on multi-view 3D tracking and event-based cameras. Her research interests include computer vision, machine learning, neuromorphic computing, and event-based cameras. Outside of work, she likes music, reading, and badminton.

Donghyun Lee received his B.E. degree in Mechanical Engineering from Yonsei University, South Korea and M.S. degree in Precision Instrument from Tsinghua University, China. Currently, he is working as a research associate in the Intelligent Computing Lab at Yale advised by Prof. Priya Panda. Prior to joining Yale, he worked as an AI researcher at Dalchaebi and Ulsan National Institute of Science and Technology (UNIST), South Korea. His research interests center around neuromorphic computing, spiking neural network, efficient deep learning strategies such as quantization, knowledge distillation, and tensor decomposition. Outside of the research, he enjoys playing soccer and tennis. [E-mail: donghyun.lee@yale.edu]

Undergraduate Students

Nicole Tian I’m Nicole, a sophomore in Pauli Murray College and prospective Computer Science and History double major from San Jose. I’m interested in artificial intelligence with a focus on designing energy efficient spiking neural networks and using computer vision for semantic segmentation. Outside of research, I’m also involved with the Dwight Hall Socially Responsible Investment Fund and The Advocates for Human Rights as I’m also interested in understanding tech policy. In my free time, I like drawing, sculpture, and playing the drums and piano.