2024 DAC
Early Career Workshop
Co-located with the 61th Design Automation Conference (DAC)
An In-Person Experience, 9:00 AM - 5:00 PM (PST)
June 23th, 2024
Location 3016, Level 3 | Moscone West, San Francisco
Abstract
The DAC Early Career Workshop is a long-tradition forum for young and mid-career faculty and professionals in the fields related to electronic design automation (EDA) and any domain at its intersection. This workshop provides an opportunity for attendees to learn from successful people on diverse topics, such as getting research grants, establishing an impactful research group, building strong collaboration with industry and academic research, growing career both academically and professionally, and developing valuable soft skills towards a successful career.
This workshop will provide valuable suggestions for early-career faculty and professionals through short talks and panel discussions. During the session, the attendees can closely interact and network with some of the established academicians, professionals, and program officers of funding agencies in EDA-related fields and beyond.
Registration
Organizing Committee
Zhiding Liang (Rensselaer Polytechnic Institute)
Zhiding Liang is an incoming assistant professor at Rensselaer Polytechnic Institute (RPI) CS department. He is currently a PhD Candidate in the Department of Computer Science and Engineering at the University of Notre Dame under the supervision of Prof. Yiyu Shi start from 2021 Fall. The results of his research have been published in prestigious conferences and journals, including DAC, ICCAD, QCE, TCAD, and TVCG. He has been selected as a DAC Young Fellow in both 2021 and 2022. He has also been nominated as the recipient of the Edison Innovation Fellowship by the IDEA Center at the University of Notre Dame. He is devoted to quantum education and outreach; he is the co-founder of the Quantum Computer System (QuCS) Lecture Series, an impactful public online lecture series in the quantum computing community. He also led the organization of the first ACM/IEEE Quantum Computing for Drug Discovery Challenge at ICCAD, a top-tier computer science conference. He is one of the major contributors to the TorchQuantum library, which has been adopted by IBM Qiskit Ecosystem and PyTorch Ecosystem with 1.1K+ stars on GitHub. He received the B.S. in Electrical Engineering from the University of Wisconsin-Madison at Dec 2020.
Rickard Ewetz (University of Central Florida)
Rickard Ewetz is an Associate Professor in the Electrical and Computer Engineering (ECE) Department at The University of Central Florida. Professor. He received his Ph.D. degree in ECE from Purdue University in 2016. His research interests are broadly focused on the intersection of hardware and artificial intelligence. This includes creating electronic design automation algorithms, hardware/software co-design methodologies for emerging in-memory computing systems. He is actively working on AI/ML topics such as explainable AI, robust AI, and neuro-symbolic AI. Over the last ten years, he has published over 70 peer-reviewed articles, including 21 publications on the prestigious CS Ranking list (DAC, ICCAD, MICRO, AAAI, IJCAI). His research has received four (4) best paper nominations from top-tier venues such as ICCAD, DATE, ASP-DAC, and MILCOM. His research is supported by DARPA, DOE, NSF, AFRL, Lockheed Martin Corp, Cyber-Florida, and the Florida High Tech Corridor Council.
Mengxin Zheng (University of Central Florida)
Mengxin Zheng is an Assistant Professor in the Computer Science Department at The University of Central Florida. Professor. She received her Ph.D. degree in Intelligent Systems Engineering Department from Indiana University Bloomington in 2023. Her research interests mainly lie in machine learning security and cybersecurity systems, especially trojan attack strategies, defense mechanisms, and privacy protection in transformer models. Her research has been presented at prestigious conferences including DAC, NeurIPS, CVPR, ACL, and NAACL. She has been honored as a 2023 DAC Young Fellow and was the 2019 Cheng Wu Innovation Challenge runner-up.
Ganapati Bhat (Washington State University)
Ganapati Bhat is the Raymond and Beverly Lorenz distinguished Assistant Professor in the School of Electrical Engineering and Computer Science at Washington State University. He received his B.Tech degree in Electronics and Communication from Indian Institute of Technology (ISM), Dhanbad, India in 2012 and the PhD degree in Computer Engineering from Arizona State University in 2020. His research interests include energy optimization in computing systems, dynamic thermal and power management, and energy management for wearable systems. Dr. Bhat received the NSF CAREER award (2023), 2022 ACM Outstanding Ph.D. Dissertation Award in Electronic Design Automation, the 2021 ACM Transactions on Design Automation of Electronic Systems (TODAES) best paper award, and 2019 Best Paper Award at CASES: International Conference on Compilers, Architecture, and Synthesis for Embedded Systems during the Embedded Systems Week (ESWEEK). He serves as an Associate Editor of IEEE Embedded Systems Letters and IEEE Design & Test.
Steering Committee
IEEE CEDA Young Professionals Coordinator: Huiru Jiang (National Taiwan University)
ACM SIGDA Education Chair: Jingtong Hu (University of Pittsburgh)