Elyse Rosenbaum

For More Information

• CAEML website
• Home Page

Education

• Ph.D., Electrical Engineering, University of California, Berkeley, Dec. 1992

Biography

Elyse Rosenbaum is the Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. She received the Ph.D. degree in electrical engineering from University of California, Berkeley. She is the director of the NSF-supported Center for Advanced Electronics through Machine Learning (CAEML), a joint project of the University of Illinois, Georgia Tech and North Carolina State University. Her current research interests include machine-learning aided behavioral modeling of microelectronic components and systems, compact models, circuit reliability simulation, component and system-level ESD reliability, and ESD-robust high-speed I/O circuit design.

Dr. Rosenbaum has authored or co-authored about 200 technical papers; she has been an editor for IEEE Transactions on Device and Materials Reliability and IEEE Transactions on Electron Devices. She was the recipient of a Best Student Paper Award from the IEDM, Outstanding and Best Paper Awards from the EOS/ESD Symposium, a Technical Excellence Award from the SRC, an NSF CAREER award, an IBM Faculty Award, and the ESD Association’s Industry Pioneer Recognition Award. She is a Fellow of the IEEE.

Academic Positions

• Acting Associate Dean for Research, Grainger College of Engineering, Jul. 2024- Jan. 2025
• Professor, Electrical and Computer Engineering, Aug. 15, 2005 - present
• Associate Professor, Electrical and Computer Engineering, University of Illinois, Aug. 1999 - Aug. 2005
• Assistant Professor, Electrical and Computer Engineering, University of Illinois, Dec. 1992 - Jul. 1999

Other Professional Employment

• Member of Technical Staff, AT&T Bell Laboratories, Holmdel, NJ - Jun. 1984 to Jul. 1987

Other Professional Activities

• Director, Center for Advanced Electronics through Machine Learning. Aug. 2016 - present.

Graduate Research Opportunities

Research opportunities exist for students with interests in device physics, circuit design and machine learning. Students must have good communication skills and an electrical engineering background.

Undergraduate Research Opportunities

Students who have completed some or all of ECE 441, 482 and 483 are potentially able to assist with some of our research. There may also be opportunities for students who have studied machine learning or statistical learning theory. Juniors and seniors only.

Research Topics

• Electronic Design Automation
• Machine learning
• Semiconductor devices and manufacturing

Teaching Honors

• ECE Ronald W. Pratt Faculty Outstanding Teaching Award, 2022

Research Honors

• Best Paper Award, 2020 EOS/ESD Symposium
• Industry Pioneer Recognition Award, Electrostatic Discharge Association, Sept. 2016.
• Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering, Aug. 2016.
• Best Paper Award, 2014 EOS/ESD Symposium
• Outstanding Paper Award, 2011 Electrical Overstress / Electrostatic Discharge Symposium
• IEEE Fellow for "contributions to electrostatic discharge reliability of integrated circuits," 2011
• Best Student Paper Award, 2008 IEEE International Reliability Physics Symposium (Co-author and research supervisor)
• 2006 IBM Faculty Award
• 1996 NSF CAREER Award
• 1991 Roger A. Haken Best Student Paper Award (Int'l Electron Devices Meeting)

Recent Courses Taught

• ECE 342 - Electronic Circuits
• ECE 441 - Physcs & Modeling Semicond Dev
• ECE 482 - Digital IC Design
• ECE 585 - MOS Device Modeling & Design