Energy Efficiency and Robustness of Advanced Machine Learning Architectures: A Cross-Layer Approach

About Alberto MarchisioMuhammad Shafique

Alberto Marchisio received his B.Sc. and M.Sc. degrees in Electronic Engineering from Politecnico di Torino Turin Italy in October 2015 and April 2018 respectively. He received his Ph.D. degree in Computer Science from the Technische Universität Wien (TU Wien) Informatics Doctoral College Resilient Embedded Systems Vienna Austria in September 2023. Currently he is a Research Group Leader with the eBrain Lab Division of Engineering New York University Abu Dhabi (NYUAD) United Arab Emirates. His main research interests include hardware and software optimizations for machine learning brain-inspired computing VLSI architecture design emerging computing technologies robust design and approximate computing for energy efficiency. He (co-)authored 30+ papers in prestigious international conferences and journals. He received the honorable mention at the Italian National Finals of Maths Olympic Games in 2012 and the Richard Newton Young Fellow Award in 2019.Muhammad Shafique (M11 - SM16) received his Ph.D. 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 collaborative R&D activities across the globe. Besides co-founding a technology startup in Pakistan he was also an initiator and team lead of an ICT R&D project. He has also established strong research ties with multiple universities in worldwide where he has been actively co-supervising various R&D activities and student/research Theses since 2011 resulting in top-quality research outcome and scientific publications. Before KIT he was with Streaming Networks Pvt. Ltd. where he was involved in research and development of video coding systems several years. In October 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 Dr. Shafique is with the New York University (NYU) where he is currently a Full Professor and the director of eBrain Lab at the NYU-Abu Dhabi in UAE and a Global Network Professor at the Tandon School of Engineering NYU-New York City in USA. He is also a Co-PI/Investigator in multiple NYUAD Centers including Center of Artificial Intelligence and Robotics (CAIR) Center of Cyber Security (CCS) Center for InTeractIng urban nEtworkS (CITIES) and Center for Quantum and Topological Systems (CQTS).Dr. Shafique has demonstrated success in obtaining prestigious grants leading team-projects meeting deadlines for demonstrations motivating team members to peak performance levels and completion of independent challenging tasks. His experience is corroborated by strong technical knowledge and an educational record (throughout Gold Medalist). He also possesses an in-depth understanding of various video coding standards and machine learning algorithms. His research interests are in AI & machine learning hardware and system-level design brain-inspired computing neuromorphic computing approximate computing quantum machine learning cognitive autonomous systems robotics wearable healthcare AI for healthcare energy-efficient systems robust computing machine learning secrity and privacy hardware security emerging technologies electronic design automation FPGAs MPSoCs embedded systems and quantum computing. 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 at premier venues. He has also organized many special sessions at flagship conferences (like DAC ICCAD DATE IOLTS and ESWeek). He has served as the Associate Editor and Guest Editor of prestigious journals like IEEE Transactions on Computer Aided Design (TCAD) IEEE Design and Test Magazine (D&T) ACM Transactions on Embedded Computing (TECS) IEEE Transactions on Sustainable Computing (T-SUSC) and Elsevier MICPRO. He has served as the TPC Chair of several conferences like CODES+ISSS IGSC ISVLSI PARMA-DITAM RTML ESTIMedia and LPDC; General Chair of ISVLSI IGSC DDECS and ESTIMedia; Track Chair at DAC ICCAD DATE IOLTS DSD and FDL; and PhD Forum Chair of ISVLSI. He has also served on the program committees of numerous prestigious IEEE/ACM conferences including ICCAD DAC MICRO ISCA DATE CASES ASPDAC and FPL. He has been recognized as a member of the ACM TODAES Distinguished Review Board in 2022. He is a senior member of the IEEE and IEEE Signal Processing Society (SPS) and a professional member of the ACM SIGARCH SIGDA SIGBED and HIPEAC. He holds one US patent and has (co-)authored 7 Books 20+ Book Chapters 350+ papers in premier journals and conferences and over 100 archive articles.Dr. Shafique received the prestigious 2015 ACM/SIGDA Outstanding New Faculty Award the AI-2000 Chip Technology Most Influential Scholar Award in 2020 2022 and 2023 the ATRCs ASPIRE Award for Research Excellence in 2021 six gold medals in his educational career and several best paper awards and nominations at prestigious conferences like CODES+ISSS DATE DAC and ICCAD Best Master Thesis Award DAC'14 Designer Track Best Poster Award IEEE Transactions of Computer Feature Paper of the Month Awards and Best Lecturer Award. His research work on aging optimization for GPUs featured as a Research Highlight in the Nature Electronics Feb.2018 issue. Dr. Shafique was named in the NYUs 2021 Faculty Honors List. His students have also secured many prestigious student and research awards in the research community