Team
Principal Investigator
Current Members
Hien Vu
PhD Student
Research Interests
- ML for remote sensing
- Low-power wireless sensing
Omkar Prabhune
PhD Student
Research Interests
- Efficient Machine Learning
- Computer Vision
Tong Chen
PhD Student
Research Interests
- Domain-specific accelerators
- Encryption hardware
Taewoong Yoon
MS Student
Research Interests
- Low-power edge AI
- Power optimization for ML
Hwangyu Cho
MS Student
Research Interests
- Domain-specific accelerators
- Approximate and stochastic computing
Soomin Lee
MS Student
Research Interests
- Approximate computing
- Hardware-Software co-design
Former Members
PhD Graduates
- Kyuin Lee, PhD ‘22, Dissertation “Secure, Usable and Practical Authentication for the Internet of Things,” Assistant Professor at the University of Houston
- Setareh Behroozi, PhD ‘22, Dissertation “Energy-Quality Scalable Hardware and Software Solutions for Energy-Efficient Approximate Computing,” Teaching Faculty at UW-Madison (now Assistant Teaching Professor)
- Jingjie Li, PhD ‘23, Dissertation “Empowering Security and Privacy-Preserving Interactions for Smart Device Users,” Lecturer (Assistant Professor) at the University of Edinburgh
- Tianen Chen, PhD ‘23, Dissertation “Designing Efficient Machine Learning Architectures for Edge Devices,” CPU IP and Methodology Engineer at Google
MS Graduates
- John Rupel, MS ‘21, Project “A Low-Power Wearable Device for Dairy Cow Eating Behavior Classification,” Embedded Electrical Engineer at Genus PLC
- Aishwarya Lekshmi Chithra, MS ‘22, Project “Accelerating Fully Homomorphic Encryption through Hardware Prefetching,” GPU Design Engineer at Qualcomm
- Farheen Asif, MS ‘24, Project “Custom Cache Replacement Policy for FHE,” Systems Software Engineer at Nvidia
- Unmesh Raskar, MS ‘25, Project “MooBot: RAG-based Video Querying System for Dairy Cattle Behavior and Health Insights,” ML Engineer at Cadence
Graduate Student Internship Employers
- Adobe
- Amazon
- AMD
- Cadence
- Dragonfruit AI
- GE Healthcare
- Intel
- Max Planck Institute
- Meta
- Nvidia
Younghyun KimAssociate Professor Contact Office: BHEE 322B Phone: 765-494-3378 E-mail: younghyun@purdue.edu LinkedIn | Scholar Affilliations Elmore Family School of Electrical and Computer Engineering Purdue Institute for Chips and AI Purdue Center for Education and Research in Information Assurance and Security (CERIAS) Purdue Applied AI Research Center (AARC) Semiconductors@Purdue NSF Athena AI Institute for Edge Computing Short Bio Younghyun Kim is an Associate Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. Before joining Purdue in 2024, he was a faculty member at the University of Wisconsin–Madison (2016–2023) and a Postdoctoral Research Assistant at Purdue University (2013–2016). He received his Ph.D. in Electrical Engineering and Computer Science in 2013 and his B.S. in Computer Science and Engineering with highest honors in 2007, both from Seoul National University. He is a recipient of the NSF CAREER Award (2019), the Meta Research Faculty Award (2021), and number of awards and recognitions for innovative publications, designs, and demonstrations. His research interests span efficient and secure computing, applied and physical AI, and IoT and cyber-physcal systems.