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Elyse Rosenbaum

Elyse Rosenbaum
Elyse Rosenbaum

Administrative Titles

  • Bliss Scholar (2004-2007)
  • Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering
Professor
(217) 333-6754
407 Coordinated Science Lab

For more information

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.

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 Areas

  • Circuits
  • Device modeling
  • Digital integrated circuits
  • Integrated circuit reliability
  • Semiconductor electronic devices

Research Topics

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

Research Honors

  • Industry Pioneer Recognition Award, Electrostatic Discharge Association, Sept. 2016.
  • Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering, Aug. 2016.
  • IEEE Fellow for "contributions to electrostatic discharge reliability of integrated circuits," 2011

Courses Taught

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