Muhammad Shafique

Professor of Computer Engineering
Education: PhD Karlsruhe Institute of Technology, Germany

E-Mail: muhammad.shafique@nyu.edu

Research Areas: Brain-inspired Computing, Embedded Machine Learning and AI, Energy-Efficient Computing, Robust Computing, Fault-Tolerant and Secure Hardware, MPSoCs, FPGAs, Embedded Systems for CPS & IoT

Muhammad Shafique (M’11 - SM’16) received the PhD degree in computer science from the Karlsruhe Institute of Technology (KIT), Germany, in 2011. Afterwards, he established and led a highly recognized research group at KIT for several years as well as conducted impactful R&D activities in Pakistan. Besides co-founding a technology startup in Pakistan, he was also an initiator and team lead of an ICT R&D project. In Oct.2016, he joined the Institute of Computer Engineering at the Faculty of Informatics, Technische Universität Wien (TU Wien), Vienna, Austria as a Full Professor of Computer Architecture and Robust, Energy-Efficient Technologies. Since Sep.2020, he is with the Division of Engineering, New York University Abu Dhabi (NYUAD), United Arab Emirates.

His research interests are in brain-inspired computing, AI and machine learning hardware and system-level design, energy-efficient systems, robust computing, hardware security, emerging technologies, FPGAs, MPSoCs, and embedded systems. His research has a special focus on cross-layer analysis, modeling, design, and optimization of computing and memory systems. The researched technologies and tools are deployed in application use cases from Internet-of-Things (IoT), smart Cyber-Physical Systems (CPS), and ICT for Development (ICT4D) domains.

Dr. Shafique has given several Keynotes, Invited Talks, and Tutorials, as well as organized many special sessions at premier venues. He has served as the PC Chair, General Chair, Track Chair, and PC member for several prestigious IEEE/ACM conferences. Dr. Shafique holds one U.S. patent has (co-)authored 6 Books, 10+ Book Chapters, and over 250 papers in premier journals and conferences. He received the 2015 ACM/SIGDA Outstanding New Faculty Award, AI 2000 Chip Technology Most Influential Scholar Award in 2020, six gold medals in educational career, and several best paper awards and nominations at prestigious conferences like DATE, DAC, ICCAD, and Codes+ISSS. He also received two IEEE Transactions of Computer "Feature Paper of the Month" Awards, DAC'14 Designer Track Best Poster Award, and a Best Lecturer Award. He is a senior member of the IEEE and IEEE Signal Processing Society (SPS), and a member of the ACM, SIGARCH, SIGDA, SIGBED, and HIPEAC.

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