Krishnendu Chakrabarty received the B. Tech. degree from the Indian Institute of Technology, Kharagpur, in 1990, and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1992 and 1995, respectively. He is now the Fulton Professor of Microelectronics in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU). Before moving to ASU, he was the John Cocke Distinguished Professor and Chair of Electrical and Computer Engineering at Duke University.
Prof. Chakrabarty is a recipient of the National Science Foundation CAREER award, the Office of Naval Research Young Investigator award, the Humboldt Research Award from the Alexander von Humboldt Foundation, Germany, the IEEE Transactions on CAD Donald O. Pederson Best Paper Award (2015), the IEEE Transactions on VLSI Systems Prize Paper Award (2021), the ACM Transactions on Design Automation of Electronic Systems Best Paper Award (2017), multiple IBM Faculty Awards and HP Labs Open Innovation Research Awards, and over a dozen best paper awards at major conferences. He is also a recipient of the IEEE Computer Society Technical Achievement Award (2015), the IEEE Circuits and Systems Society Charles A. Desoer Technical Achievement Award (2017), the IEEE Circuits and Systems Society Vitold Belevitch Award (2021), the Semiconductor Research Corporation Technical Excellence Award (2018), the Semiconductor Research Corporation Aristotle Award (2022), the IEEE-HKN Asad M. Madni Outstanding Technical Achievement and Excellence Award (2021), and the IEEE Test Technology Technical Council Bob Madge Innovation Award (2018). He is a Research Ambassador of the University of Bremen (Germany) and he was a Hans Fischer Senior Fellow at the Institute for Advanced Study, Technical University of Munich, Germany during 2016-2019. He is a 2018 recipient of the Japan Society for the Promotion of Science (JSPS) Invitational Fellowship in the “Short Term S: Nobel Prize Level” category.
Prof. Chakrabarty’s current research projects include: design-for-testability of 2.5D/3D integrated circuits; hardware security; failure prediction using AI/ML; AI accelerators; microfluidic biochips; AI for healthcare; neuromorphic computing systems. His research has been supported by the National Science Foundation, DARPA, Office of Naval Research, National Institutes of Health, Army Research Office, Semiconductor Research Corporation, and various corporations (Intel, IBM, Synopsys, Cisco, HP). He has published 27 books (with one book translated into Chinese) and over 840 peer-reviewed papers (including over 340 journal articles) on these topics. He holds 18 US patents and his research on microfluidic biochips has been licensed by Advanced Liquid Logic, Illumina, GenMark, and Baebies Inc. He has collaborated extensively with the semiconductor industry and his test technology solutions have been adopted by Intel, TSMC, Samsung, Mentor Graphics, and Qualcomm (https://www.src.org/award/tech-excellence/2018/). He is currently a Visiting Professor at NVIDIA. He has supervised 38 PhD dissertations, and his former students are now working at leading companies such as Intel, NVIDIA, TSMC, and Apple.
Prof. Chakrabarty is a Fellow of ACM, IEEE, and AAAS, and a Golden Core Member of the IEEE Computer Society. He is a member of the DARPA Microsystems Exploratory Council for 2022-2025. He was a Distinguished Visitor of the IEEE Computer Society (2005-2007, 2010-2012), a Distinguished Lecturer of the IEEE Circuits and Systems Society (2006-2007, 2012-2013), and an ACM Distinguished Speaker (2008-2016). Prof. Chakrabarty served as the Editor-in-Chief of IEEE Design & Test of Computers during 2010-2012, ACM Journal on Emerging Technologies in Computing Systems during 2010-2015, and IEEE Transactions on VLSI Systems during 2015-2018.
B. Tech., Indian Institute of Technology, Kharagpur (1990)
M.S.E., University of Michigan, Ann Arbor (1992)
Ph.D., University of Michigan, Ann Arbor (1995)
Design-for-testability of 2.5D/3D integrated circuits and heterogeneous integration
Design of AI accelerators, neuromorphic computing systems
Microfluidic biochips, AI for healthcare;
Selected Recent Publications:
- M. Ibrahim, Z. Zhong, B. Bhattacharya and K. Chakrabarty, "Efficient regulation of synthetic biocircuits using droplet-aliquot operations on MEDA biochips", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,
vol. 41, pp. 2490-2503, August 2022.
A. I. Arka, B. R. Joardar, J. R. Doppa, P. P. Pande and and K. Chakrabarty, "Performance and accuracy trade-offs for training graph neural networks on ReRAM-based architectures", IEEE Transactions on Very Large Scale Integration (VLSI) Systems, ol. 29, pp. 1743-1756, October 2021.
S. Jiang, F. Firouzi, K. Chakrabarty and E. Elbogen, "Resilient and hierarchical IoT-based solution for stress monitoring in everyday settings", IEEE Internet of Things Journal, vol. 9, pp. 10224-10243, June 2022.
A. Chaudhuri, J. Talukdar, F. Su and K. Chakrabarty, "Functional criticality analysis of structural faults in AI accelerators", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 41, pp. 5657-5670, February 2022.
J. Zhou, J. McNabb, N. DeCapite, J. Ruiz, D. Fisher, S. Grego and K. Chakrabarty, "Stool image analysis for digital health monitoring by smart toilets", IEEE Internet of Things Journal (accepted for publication), available on IEEE Xplore as Early Access (March 2022).
W.-K. Liu, B. Tan, J. M. Fung, R. Karri and K. Chakrabarty, "Hardware-supported patching of security bugs in hardware IP blocks", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 42, pp. 54-67, January 2023.
R. Pan, X. Li and K. Chakrabarty, "Unsupervised two-stage root-cause analysis with transfer learning for integrated systems", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (accepted for publication), available on IEEE Xplore as Early Access (May 2022).
P. Zhang, J. Rufo, C. Chen, J. Xia, Z. Tian, L. Zhang, N. Hao, Z. Zhong, Y. Gu, K. Chakrabarty and T. Huang, "Acoustoelectronic nanotweezers enable dynamic and large-scale control of nanomaterials", Nature Communications, 23 June 2021.
Synopsys, Mountain View, CA: 2022-2023
Cisco Systems, San Jose, CA: 2008-2010
Kevin Kennedy & Associates, Indianapolis, IN: 2008--2010
Advanced Technology Ventures, Waltham, MA: 2005
Spectrum Sciences & Software, Fort Walton Beach, FL 2005
Johnstech International Corporation, Minneapolis, MN: 1998-1999
Member of Scientific Advisory Board, Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI, German Research Center for Artificial Intelligence): 2021-
Member of Scientific Advisory Board, Genomtec: 2022-
Visiting Professor at NVIDIA, Santa Clara, CA: May 2022 to January 2023