Subhasish Mitra is a Professor in the Department of Electrical Engineering and by courtesy in Computer Science at Stanford University’s School of Engineering. His pioneering work focuses on creating robust, error-tolerant hardware systems through the Resilient Silicon paradigm, addressing critical challenges in modern microprocessors and memory design. Education Ph.D. in Electrical Engineering, Stanford University, 1999 B.Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1994 His research spans Computer Architecture , VLSI Design , and Hardware Security , with breakthroughs in defect-tolerant circuits and aging-induced error mitigation. Mitra’s work bridges theoretical innovation and industrial adoption, notably in Intel’s high-volume manufacturing processes. Key recognitions include: IEEE Fellow (2015) for “contributions to design and test of robust microprocessors” ACM Fellow (2015) for foundational reliability frameworks Phil Kaufman Award (2020), EDA’s highest honor He leads Stanford’s Robust Systems Group with sustained funding from NSF, DARPA, and semiconductor industry partners, driving next-generation secure hardware for AI accelerators and IoT devices.
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نمایش ۷۲۱-۷۲۸ از ۷۲۸ استاد راهنما
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Sabih H. Gerezمشاهده پروفایل
استادیار
Sabih H. Gerez is an Assistant Professor specializing in Computer Architecture Design and Test for Embedded Systems , affiliated with the Digital Society Institute . With an ORCID ID of 0000-0003-4576-121X, his work focuses on low-power hardware design and energy-efficient computing. Research Interests : Energy efficiency, near-threshold voltage (Near-Vth) computing, flip-flop design, and optimization of digital circuits for embedded systems. Key Contributions : Development of ultra-low-voltage flip-flops, glitch-optimized Booth multipliers, and standard-cell libraries for Near-Vth systems. His work addresses power dissipation, noise margins, and performance metrics. Collaborations : Collaborated with researchers like Anuradha Chathuranga Ranasinghe and Muhammad Adeel Shafique on topics such as approximate MAC accelerators and power-efficient circuit design.
- Computer Science
- Design
- Energy Efficiency
- +۸ مورد دیگر
François-Raymond Boyer is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a B.Sc. and Ph.D. from Université de Montréal and teaches courses in programming and digital audio. His research spans: Computer architecture and VLSI systems Network processing and traffic management Digital audio signal processing Hardware acceleration and optimization He is affiliated with ReSMiQ (Strategic Cluster for Microsystems) and OICRM (Music Research Observatory). Recent publications focus on 5G network processing, modular programming frameworks, and high-speed traffic management architectures, primarily in IEEE Access and IEEE Transactions on VLSI Systems. Professor Boyer has supervised 3 PhD and 6 Master's students, with research topics including network architecture, audio processing, and hardware design. No scientific awards are mentioned in the available records.
Dr. Adrian Rendon Nava is a Researcher at Robert Gordon University's School of Computing, Engineering & Technology, affiliated with the Robotics & Autonomous Systems Research Group and Environment, Energy & Sustainability research theme. His work bridges electronics engineering, machine learning, and industrial applications through active research projects and specialized teaching. His academic credentials include: Bachelor in Electronics Engineering with Computing Major (Autonomous Metropolitan University, 2000) MSc in Microelectronics (National Polytechnic Institute, 2005-2007) PhD in Communications and Electronics (National Polytechnic Institute, 2014) Dr. Rendon Nava's research centers on Machine Learning and AI applications for IoT and Industry 4.0 systems, with specialized expertise in Deep Learning and One-shot Learning for cognitive neuroscience. His technical foundation in Microelectronics VLSI Circuit Design and embedded systems enables practical implementations in robotics and autonomous systems. Current work focuses on developing a novel composite inspection probe prototype with integrated data-logging capabilities. His 2025 publication on Jabi Lake water quality demonstrates interdisciplinary collaboration, applying chemometric analysis to environmental monitoring while maintaining his core focus on electronics and AI-driven solutions. This reflects his approach of leveraging computational tools for real-world engineering challenges. Dr. Rendon Nava actively supervises PhD candidates and teaches core engineering modules including Mechatronics, Metrology, and Analogue Electronics. His supervision emphasizes practical electronics implementation and AI integration in industrial systems. Within the Robotics & Autonomous Systems Research Group, he contributes to projects advancing sensor technologies and autonomous inspection systems, particularly through his leadership in composite material assessment instrumentation development.
Graziano Vernizzi serves as Professor in the Department of Physics and Astronomy at Siena University (formerly Siena College) since 2016, having previously held Associate Professor (2013-2016) and Assistant Professor (2010-2013) positions at the same institution. His academic journey includes a Research Professor role at Northwestern University (2006-2010) and prestigious postdoctoral appointments at the Niels Bohr Institute, University of Oxford, CEA/Saclay, Spinoza Institute, and Northwestern University. His educational background includes: B.S. in Physics, University of Parma, Italy (1995) Ph.D. in Physics, University of Parma, Italy (2000) Vernizzi's research integrates computational and theoretical physics to address nanoscale phenomena, with core interests in Random Matrix Theory, biophysics (RNA/ssDNA structures and membrane theory), soft condensed matter physics, and nanoscale science. He develops computational models to analyze complex systems where theoretical frameworks are essential for interpreting experimental data, driving technological innovation and expanding career opportunities in emerging scientific fields. His methodology frequently bridges mathematical rigor with physical applications across disciplinary boundaries. Analysis of his publication trends reveals consistent interdisciplinary work connecting mathematics, physics, and engineering. Key recurring themes include topological constraints in biological and electronic systems, statistical mechanics approaches to soft matter, and algorithmic innovations for verification problems. His research demonstrates particular strength in applying abstract mathematical concepts like random matrix theory to concrete biophysical and engineering challenges, resulting in publications spanning Physical Review journals, Soft Matter, and specialized engineering conferences. His scientific recognition includes: Trust-Co Excellence Honor for advancing the mission of Siena College (Trustco Bank, 2015) No information regarding student advising, research grants, or dedicated laboratory facilities was provided in the source material. His professional activities focus on computational research, course development in nanoscale physics, and interdisciplinary collaboration without mention of specific research teams or experimental facilities.
Sönke Appel serves as a Professor at the West Coast University of Applied Sciences, holding the Professorship for Computer Engineering / Microelectronics within the School of Technology and Department of Technology. His research focuses on hardware-centric domains: Computer Engineering Microelectronics Embedded Systems Digital Circuit Design VLSI Design Hardware Engineering Professor Appel maintains active teaching and research operations from his office in Building 1.1, Room 1,027 at Fritz-Thiedemann-Ring 20, 25746 Heide. He can be reached via email at appel@fh-westkueste.de or by phone at +49 (0) 481 8555-340.
Dr Runchun Mark Wang is a Researcher at the International Centre for Neuromorphic Systems (ICNS) at Western Sydney University, specializing in hardware acceleration for neural systems. He develops FPGA and mixed-signal analog VLSI platforms capable of simulating human-brain-scale neural networks and leads hardware design for the Neuromorphic Imager for Space Situational Awareness, providing open-source software tools for broader research access. His educational background includes: PhD from Western Sydney University (2013) MSEE from Shanghai Jiaotong University (2008) BSEE from East China University of Science and Technology (2003) Wang's research spans neuromorphic engineering, computational neuroscience, and hardware implementation of deep learning systems. His work bridges theoretical neural models with practical electronic systems, emphasizing scalable architectures for cognition simulation and space applications through integrated circuit design. Key recognitions include: Australian Research Council Postdoctoral Research Fellowship (2014–2017) Australian Postgraduate Research Award (2009–2013) Prior to academia, Wang worked as an industry SoC/ASIC design engineer, bringing practical hardware expertise to his current research leadership at ICNS. His projects focus on open-source neuromorphic tools and space-imaging technology with real-world deployment potential.
Hayssam El-Razouk serves as Associate Professor in the Electrical and Computer Engineering Department at California State University, Fresno within the Lyles College of Engineering. He holds a PhD in Electrical and Computer Engineering from Western University (2015) and maintains active industry connections through prior roles at IBM Canada and RedIron Technologies. Education: PhD in Electrical and Computer Engineering, Western University, London, Ontario, Canada (2015) MESc in Electrical and Computer Engineering, Western University, London, Ontario, Canada (2006) BEng in Electrical and Computer Engineering, Beirut Arab University, Beirut, Lebanon (2002) - First Rank Research Focus: Dr. El-Razouk's work centers on Hardware Security and Cryptographic Hardware , with significant contributions to VLSI Circuits Design for finite field arithmetic. His research bridges theoretical cryptography with practical implementations, emphasizing defect tolerance in digital circuits, data compression techniques, and pseudo-random sequence generation for secure communications. Current projects address emerging threats in embedded systems and IoT security. Publication Trends: Analysis of his 15 most recent publications (2025-2016) reveals consistent specialization in GF(2^m) arithmetic optimization using Gaussian Normal Basis and Polynomial Basis representations. His work demonstrates progressive refinement from foundational finite field operations (2016-2019) toward integrated security solutions (2020-2025), with increasing focus on side-channel attack resistance and hardware-software co-design for real-world applications including automotive systems and smart homes. Scientific Recognition: Natural Sciences and Engineering Research Council (NSERC) Canada Graduate Scholarship-Doctoral (2011-2015) Best Presenter Award, IEEE CCWC 2023 Best Paper Award, IEEE CCWC 2021 Outstanding Faculty Publication Award, CSU Fresno (2019, 2020) Jamal Abdul Nassir Golden Medal Distinction Award (2002) Research Funding and Mentorship: Dr. El-Razouk secured a $378,002 Department of Defense grant (W911NF-21-1-0210) in 2021 for hardware security research. He teaches core courses including ECE 150 (Cloud and Cybersecurity) and ECE 156 (Cryptography), supervising senior design projects on topics like RFID security and temperature monitoring systems. As an IEEE and ASEE member, he actively contributes to conference program committees and journal reviews.