Ramesh Karri is a Professor and Chair of the Electrical and Computer Engineering Department at New York University Tandon School of Engineering. He co-founded the NYU Center for Cyber Security (CCS) in 2009 and co-directed it from 2016-2024. He is also a Fellow of the IEEE and has led initiatives such as the Embedded Systems Challenge (ESC), a red-blue team cybersecurity competition. Education: Ph.D. in Computer Science and Engineering, University of California, San Diego (1993) B.E. in Electrical and Computer Engineering, Andhra University (1985) Research Focus: His work centers on hardware cybersecurity, including trustworthy integrated circuits, cyber-physical systems, nano-enabled security, and biochip security. He pioneered security-aware CAD tools and has developed metrics for hardware trojan detection through initiatives like the Trust-Hub. Awards & Leadership: Recipient of the Humboldt Fellowship and NSF CAREER Award Editor-in-Chief of ACM Journal of Emerging Computing Technologies Leadership roles at IEEE conferences (ICCD, HOST, DFTS) Grants & Labs: Directs the Center for Advanced Technology in Telecommunications (CATT) and NYU CCS. His labs focus on additive manufacturing security, digital microfluidic systems, and AI-driven hardware design.
Alessandro Gabrielli is a Full Professor at the Department of Physics and Astronomy "Augusto Righi" at the University of Bologna, where he also serves as Coordinator of the PhD Course in Physics. His primary scientific discipline is PHYS-01/A Experimental physics of fundamental interactions and applications. He is affiliated with both the National Institute for Nuclear Physics (INFN) and CERN in Geneva. His research focuses on experimental physics, particularly electronic technologies applied to particle accelerators. His current research activities center on the ATLAS experiments at CERN in Geneva and DUNE in the United States. More recently, he has expanded his research interests to include cybersecurity, artificial intelligence, and quantum computing, aligning with new international research initiatives in applied physics. Professor Gabrielli has been engaged in numerous national and international research projects, collaborating extensively with the National Institute for Nuclear Physics. He has coordinated multiple experimental research activities and authored over 1,000 publications in international peer-reviewed journals. His H-Index is 116 (SCOPUS, February 2025). His scientific recognition includes serving as Editor in Chief for MDPI Journals: Electronics since 2021, Guest Editor for special issues on Microelectronics in 2023, and Editor of Frontiers in Detector Science and Technology. He has also served as a reviewer for the Dutch Research Council (NWO) for a grant of €280,000. In terms of academic guidance, he has supervised 6 PhD theses in Physics, 1 PhD thesis in Data Science and Computation, and 14 Master's theses in Physics at the University of Bologna. His research has been supported by multiple grants, including a PRIN 2022 grant of 173k€ for "High performance microelectronics for low-noise cryogenic applications" and an AlmaIdea 2022 grant of 24,000€ for developing a Hardware Firewall. Professor Gabrielli is actively involved in international collaborations, having served as a "Visiting Scientist" at the Rutherford Appleton Laboratory in the UK (2009), "Visiting Professor" at the Center for Human Space Robotics at the Italian Institute of Technology (2012-2013), and "Project Associate" contractor at CERN (2008-2010). He currently coordinates the Bologna section of the INFN for the DUNE experiment and various ATLAS hardware activities.
Peter Milder is an Associate Professor in the Department of Electrical and Computer Engineering at Stony Brook University. His research focuses on hardware acceleration, FPGA-based systems, and domain-specific compilers for applications in machine learning, signal processing, and networking. He leads projects on automatic hardware generation tools like Argus for CNNs and FFT Gen for signal processing transforms. Education details are not explicitly provided in the text, but his work spans multiple interdisciplinary areas including formal verification (e.g., model checking on FPGAs), wireless edge computing (OPSEL protocol), and high-performance sorting algorithms. He has advised numerous PhD students and collaborates with researchers across academia and industry. Research Highlights: Developed voltage-scaling techniques for DNN accelerators. Created Waverunner, an FPGA-accelerated state machine replication system. Organized IEEE Transactions special issues and NSF-funded projects on edge computing and machine learning hardware. Awards: ACM TODAES Best Paper Award (2014). NSF grants for sparse transformer acceleration and FPGA-based spectrum sensing. Grants & Funding: NSF XPS Program (2015): Cloud FPGA deep learning. NSF ECCS (2020): Sparsity-aware NLP hardware. Lab/Collaborations: Collaborates with Professors Michael Ferdman, Fan Ye, and others on FPGA, edge computing, and embedded systems. His work often bridges hardware design with software frameworks.
Claudio Talarico is a Professor in the Department of Electrical and Computer Engineering at Gonzaga University's School of Engineering & Applied Science. He holds a Ph.D. in Electrical Engineering from the University of Hawaii and an M.S. from the University of Genoa, Italy. With industry experience at Infineon Technologies, IKOS Systems, and Marconi Communications, his expertise spans VLSI design, embedded systems, and hardware/software co-design. His research focuses on: Low-power/high-performance VLSI circuits Embedded system-on-chip design Computer-aided design methodologies Wireless communication systems Hardware/software co-design Recent publications (2020-2024) demonstrate strong emphasis on: Beam steering architectures for 5G/wireless systems Angle-of-arrival estimation techniques Time synchronization in body area networks Health monitoring platforms FPGA/digital implementations He teaches core courses including VLSI Circuits & Systems, Computer Hardware Design, and Digital Systems. No awards or current students are documented in available materials.
Angelo Dragone serves as a Distinguished Staff Engineer at SLAC National Accelerator Laboratory, operated by Stanford University. He currently holds the dual leadership roles of Deputy Associate Lab Director for the Technology Innovation Directorate and Program Director for Detector R&D and Applied Microelectronics. Dr. Dragone also contributes to academic instruction as an instructor for Advanced Integrated Circuit Design (EE 214B) at Stanford University during the Winter quarter. Dr. Dragone earned his Ph.D. in Microelectronics from the Polytechnic University of Bari, Italy, with research conducted at Brookhaven National Laboratory on mixed-signal readout architecture for radiation detectors. His professional journey includes working at Brookhaven National Laboratory from 2004 before transitioning to SLAC in 2008, where he has since established himself as a leader in detector technology. With over two decades of experience in scientific instrumentation, Dr. Dragone's research focuses on innovative radiation detector systems with applications spanning multiple scientific domains. His work encompasses: Design of ultra-fast X-ray detector architectures for X-ray Free-Electron Lasers Development of high frame rate, large dynamic range detector systems Creation of efficient, scalable systems with real-time processing capabilities Exploration of fundamental performance limits in radiation detection systems Applications in photon science, particle physics, medical imaging, and national security Dr. Dragone's publication record reveals a strategic evolution toward increasingly sophisticated detector technologies. His recent work demonstrates strong integration of advanced electronics with machine learning techniques for particle detection, while maintaining focus on practical implementation challenges in high-energy physics environments. The publications span fundamental physics measurements to cutting-edge circuit design, reflecting his dual expertise in both theoretical understanding and practical engineering solutions. As head of the Integrated Circuits Department within SLAC's Instrumentation Division, Dr. Dragone leads strategic R&D planning for the SLAC X-ray detectors Initiative. His leadership extends to the Applied Microelectronics program, where he guides research directions that bridge academic inquiry with real-world scientific applications. Under his direction, these programs have made significant contributions to advancing detector technology for major scientific facilities.
Mario Roberto Casu is an Associate Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as a contact person for the Degree Course in Electronic Engineering. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory and actively contributes to the VLSILAB research group. Dr. Casu received his laurea degree summa cum laude in electronics engineering and his Ph.D. in electronics and communications engineering from the Polytechnic University of Turin in 1998 and 2001, respectively. He has held visiting researcher positions at Columbia University (2010-2011), National University of Singapore (2017), and CEA Grenoble (2001), as well as a visiting professorship at Chongqing Technology and Business University (2016). His research spans several interconnected domains focused on hardware implementation of advanced computing systems. Dr. Casu's work primarily addresses Embedded Machine Learning through heterogeneous embedded systems (ASICs, FPGAs, CPUs, GPUs), System-on-Chip design including latency-insensitive approaches and Network-on-Chip architectures, Microwave Imaging for both biomedical (breast cancer and stroke detection) and industrial applications (food contamination detection), and Ultra-Wide Band technologies for biomedical applications. His research bridges theoretical design methodologies with practical industrial applications across biomedical, automotive, and food sectors. Dr. Casu's recent scholarly output demonstrates a clear trajectory toward optimizing hardware implementations for machine learning workloads, particularly through FPGA-based solutions and precision-scalable multipliers. His work increasingly integrates microwave sensing technologies with machine learning for specialized applications like food contaminant detection, while maintaining strong foundations in traditional VLSI design and system-level optimization techniques. As an academic leader, Dr. Casu serves on the editorial board of IEEE TRANSACTIONS ON AGRIFOOD ELECTRONICS and regularly participates in program committees for major international conferences including DATE, ICCAD, DAC, and VLSI-SoC. He has been involved in 9 national academic research projects (2 as principal investigator), 2 European academic research projects, and 7 national and international industrial projects (2 as principal investigator). Dr. Casu actively mentors the next generation of engineers, currently supervising multiple PhD students including Lorenzo Lagostina, Edward Manca, Teodoro Urso, Fabrizio Ottati, and Luca Urbinati. His teaching portfolio includes courses such as Integrated Systems Technology, Microelectronics Digital Design, and Embedded Electronic Systems for AI/ML across both bachelor's and master's programs in Electronic and Computer Engineering. His laboratory work centers around the VLSILAB Group at DET, where his team develops innovative solutions in hardware acceleration for machine learning, microwave imaging systems, and system-level design methodologies. Current projects include the EU-funded GreenChips-EDU initiative for sustainable microelectronics education and industry collaborations with companies like Infineon Technologies on coarse-grained reconfigurable array architectures for machine learning applications.
Claude Thibeault is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS), with a Ph.D. from Polytechnique Montréal and a B.Eng. from UQAC. His research focuses on microelectronics , integrated circuit testing , and fault tolerance , particularly in aerospace and FPGA systems. He leads the LaCIME lab, which specializes in communications and microelectronic integration. His work spans radiation effects on circuits , asynchronous design , and test methodologies . Recent publications analyze cosmic radiation impacts on FPGA architectures and knowledge-based diagnostic systems . He supervises numerous graduate students in projects related to hardware acceleration , chaotic communication systems , and power-aware testing . LaCIME emphasizes industry collaboration and technology transfer , with research axes in intelligent systems and connectivity . The lab actively recruits students with backgrounds in electrical or microelectronics engineering.
Ronan Farrell is a Professor in the Department of Electronic Engineering at Maynooth University’s Faculty of Science & Engineering and currently serves as Vice President Academic and Registrar. He earned a BE and PhD from University College Dublin (1993, 1998) and previously worked at ICI/Zeneca Chemicals (1993–1995) and Parthus Technologies (1998–2001) as a mixed-signal ASIC designer. His academic career at Maynooth spans from Lecturer to Professor (2016), with leadership roles as Head of Department (2012–2019) and Director of the Callan Institute (2008–2015). He leads SFI research initiatives in radio frequency electronics and sensor networks. Education: BE (1993), PhD (1998) – University College Dublin Leadership: Head of Electronic Engineering (2012–2019), Director of Callan Institute (2008–2015) Research Focus: Wireless system design, RF/mixed-signal electronics, technology transfer, and innovation. His work bridges theoretical advancements (e.g., MIMO capacity optimization) with practical applications (e.g., 5G transmitters, digital predistortion techniques). Publication Trends: Recent articles emphasize 5G wireless systems, power amplifier linearization, OFDM signal processing, and behavioral modeling. Collaborations span institutions in Ireland, Europe, and Asia, with a focus on hardware implementation and system optimization. Students & Collaborations: Mentions co-authors in publications but no explicit student list provided. Collaborates with researchers in Ireland, Germany, and China.
Marcello De Matteis serves as Associate Professor in the Department of Physics at the University of Milano-Bicocca, Italy, specializing in Application-Specific Integrated Circuit (ASIC) design for medical physics, high-energy experiments, and sensor systems. With over 35 ASICs developed since 2005—including principal design of 20+ chips across 0.5μm CMOS to 16nm FinFET technologies—he bridges electronics engineering with clinical applications in proton therapy and neuroscience. His educational background features a double degree from the Top Industrial Managers for Europe (TIME) program: Industrial Engineering, Polytechnic University of Madrid (2003) Electronic Engineering, Polytechnic University of Milan (2004) Research focuses on radiation-hardened analog circuits for particle detectors (ATLAS Muon Drift Tubes), proton therapy instrumentation (Proton Sound Detector project), and neuromorphic biosensors using neuron-electronic junctions. His work emphasizes low-power, high-precision front-ends for ionoacoustic imaging, with recent publications targeting FLASH radiotherapy monitoring and quantum computing interfaces. Analysis of his 15 most recent publications reveals dominant trends in medical physics instrumentation (70% of works), particularly ionoacoustic dosimetry for proton beam therapy, alongside growing contributions to neuromorphic engineering (20%) and radiation-hardened design (10%). All leverage advanced CMOS/FinFET nodes (28nm–12nm) to address noise, power, and radiation tolerance challenges in clinical and space applications. Key career recognition includes: Italian National Scientific Qualification for Full Professor (Electronics, 2020) Technical Program Committee roles for IEEE ESSCIRC, PRIME, and ICICDT conferences Associate Editor for Journal of Circuits, Systems and Computers (World Scientific) As Principal Investigator for INFN-funded projects since 2018, he coordinates multi-institutional teams across Italy and Germany on proton therapy instrumentation. His grant portfolio includes: Proton Sound Detector (INFN): 4-unit collaboration (Milano-Bicocca, CNAO, LMU Munich, INFN Catania) for real-time Bragg peak localization ScalTech28/FinFet16 (INFN): Rad-hard ASIC design in 28nm/16nm for high-luminosity LHC upgrades SAFIR GEM (2022): Submarine acoustic monitoring infrastructure funded by University of Milano-Bicocca Current leadership spans two research streams: CMOS 28nm biosensors for neuron-electronic interfaces and proton sound detectors for hadron therapy. Previously, he directed MEMS sensor development at University of Salento (2008–2012) and served as technical lead for ATLAS Muon Drift Tube ASICs. His industry collaborations include Infineon, IMEC, and STMicroelectronics, with recent work integrating PVDF ultrasound arrays for melanoma diagnosis and FinFET neurons for neuromorphic computing.
Oriol Farràs Ventura is an Associate Professor at the Department of Computer Engineering and Mathematics, Rovira i Virgili University (URV), and coordinates the PhD program in Computer Science and Mathematics of Security. He holds a BSc in Mathematics (2004), a BEng in Telecommunication Engineering (2005), and a PhD in Applied Mathematics (2010), all from Universitat Politècnica de Catalunya (UPC). His career includes roles as an Assistant Professor at UPC, Post-Doctoral Fellow at Ben-Gurion University, Juan de la Cierva Researcher at URV, and tenure-track Assistant Professor at URV. Research Interests : His work focuses on Cryptography, Combinatorics, Information Theory, and Matroid Theory, with particular emphasis on Secret-sharing Schemes, cryptographic protocol design, and theoretical foundations of secure communication. Recent contributions include advancements in post-quantum cryptography, hardware accelerators for cryptographic algorithms, and matroid-based frameworks for access structures in secret sharing. Teaching & Academic Roles : He teaches courses such as Cryptography and Information Security, Blockchain Technology, and Discrete Mathematics. He is an active member of research groups including COPRICA, CRISES, and CYBERCAT, and has served on program committees for EUROCRYPT 2025, ACM CCS 2024, and TCC 2020. Labs & Collaborations : His affiliation with the COPRICA group drives interdisciplinary research in computational security. He collaborates on initiatives like the Red RISC-V network for hardware-software integration and contributes to events such as the Workshop on Secret Sharing Schemes (2025) and the Doctoral Workshop in Computer Science and Mathematics (2024).
Ken Mai is a Principal Systems Scientist in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.S., M.S., and Ph.D. in Electrical Engineering from Stanford University. His research focuses on high-performance circuit design, secure IC design, radiation hardening, reconfigurable computing, and computer architecture. He has received prestigious awards including the NSF CAREER Award and the George Tallman Ladd Research Award. Education: Ph.D., Electrical Engineering, Stanford University, 2005 M.S., Electrical Engineering, Stanford University, 1997 B.S., Electrical Engineering, Stanford University, 1993 Research Interests: Dr. Mai’s work addresses challenges in nanometer-scale CMOS technology, including interconnect delay, leakage, and soft errors. His projects include secure IC design against hardware attacks, robust memory techniques using digital communications, 100GHz logic via cryogenic cooling, and bio-implantable computing platforms. He collaborates with neurosurgeons at the University of Pittsburgh for medical applications. Key Projects: Secure IC Design: Countermeasures against invasive/non-invasive attacks Robust Memory Design: Error correction codes for resilience 100GHz Logic: Cryogenically cooled CMOS for high-speed applications Bio-Implantable Systems: Low-power, high-density computing for medical devices Awards: NSF CAREER Award George Tallman Ladd Research Award Eta Kappa Nu Excellence in Teaching Award Teaching and Advising: He teaches courses like 18-322 (Digital Circuits), 18-617 (Memory Systems), and advises students including Mudit Bhargava and Mark McCartney. His lab, the VLSI Design Group, develops tools and methodologies linking circuit design to architectural design. Contact: Email: kenmai@ece.cmu.edu Website: Carnegie Mellon VLSI Design Group
Johnny Öberg is an Associate Professor at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology. He specializes in embedded systems, FPGA design, and fault-tolerant hardware architectures. His research focuses on radiation effects in electronics, machine learning acceleration, and network-on-chip (NoC) systems. He teaches and examines courses such as Computer Systems Architecture (IS2202), Embedded Hardware Design in ASIC and FPGA (IL2225), and Embedded Systems Design Project (IL2232). His work often bridges theory and practice, emphasizing real-world applications in aerospace, automotive, and IoT domains. Key research trends include improving reliability in SRAM-FPGAs through statistical fault injection, developing hardware-accelerated machine learning frameworks, and optimizing NoC architectures for predictable performance in mixed-criticality systems. Recent projects include the SAFEPOWER architecture for energy-efficient systems and collaborations on structural health monitoring using Lamb wave analysis. No scientific awards are explicitly mentioned in the provided texts. Johnny has advised on multiple degree projects but no specific student names are listed. His contributions include foundational work in GALS (Globally Asynchronous, Locally Synchronous) communication bridges and protocol grammars for low-power implementations. Labs/teams: Active involvement in the ICES (Innovative Centre for Embedded Systems) and the Suaineadh project for space-deployable structures. Collaborates on interdisciplinary initiatives like the ABB NoC and Panacea NoC prototypes.
Frank Kagan Gürkaynak is Director of the Microelectronics Design Center (DZ) and a Researcher at ETH Zurich's Department of Information Technology and Electrical Engineering (D-ITET). He leads the PULP open-source hardware project and works closely with Prof. Luca Benini in the Integrated Systems Laboratory (IIS). His academic journey includes BSc/MSc from Istanbul Technical University and a PhD from ETH Zurich. Roles: Microelectronics Design Center Director, Senior Scientist in IIS, VLSI course lecturer Research focuses on energy-efficient digital circuits, cryptographic hardware security, and open-source processor architectures. Key projects include EU-funded initiatives like European Processor Initiative (EPI), Convolve, and NeuroSoC, along with SNSF grants Tiny Trainer and PEDESITE. Active in teaching VLSI design, embedded systems, and essential engineering skills. Publications emphasize secure cryptographic accelerators, low-power processor clusters, and GALS system design methodologies. Contributions include energy-efficient ASICs for IoT to HPC domains and pioneering work in side-channel attack-resistant hardware.
Dr. Kok Chiang Liang is a Lecturer and Program Coordinator for Electrical and Electronic Engineering at the School of Engineering , part of the College of Engineering, Science and Environment at Newcastle Australia Institute of Higher Education (NAIHE). He previously worked at DSO National Laboratories and SUSS, receiving multiple awards including the Design Innovation Award and Teaching Excellence Gold Awards . He holds a PhD and BEng (Honours) from Nanyang Technological University (NTU). Education PhD, Electrical & Electronic Engineering, NTU (2014) BEng (Honours), Electrical & Electronic Engineering, NTU As a researcher, Dr. Kok focuses on ASIC design for power management , robotics , artificial intelligence , and energy harvesting applications . His work bridges IoT and sustainable engineering, with over 50 publications in Q1/Q2 journals and conferences. Notably, he has pioneered innovations in medical device design, urban sustainability, and educational technology. His recent articles highlight trends in sustainable electronics and AI integration across domains. He has received significant recognition, including two Best Paper Awards and substantial research seed funding (over S$260,000). Dr. Kok also contributes to community service as a District Councillor and Grassroots Volunteer in Singapore, and serves on the STEM Industrial Advisory Board and IEEE committees . Scientific Awards Design Innovation Award (Individual), DSO National Laboratories (2018) Teaching Excellence Gold Award, SUSS (2020, 2025) Best Paper Award, 3rd ICESA (2021) Best Paper Award, 6th ICPEE (2024) Dr. Kok’s leadership extends to research grants as Principal Investigator and Co-PI, and to policy advisory roles for Singapore’s Ministry of Education. His interdisciplinary approach combines technical innovation with societal impact, reflected in his roles at People’s Action Party Meet-the-People Sessions and Ang Mo Kio Town Council .
Stefan Brantschen is a Lecturer at the University of Applied Sciences and Arts Northwestern Switzerland , affiliated with the School of Engineering and Environment . He works at the intersection of digital microelectronics, algorithm development, and hardware verification using VHDL. Role: Research associate and lecturer in digital design Expertise: FPGA/ASIC implementation, architecture development, functional safety standards (DO-254) His research focuses on digital microelectronics , emphasizing practical implementation from concept to real-world deployment. He also contributes to functional safety verification frameworks in industrial applications. Stefan supervises Master projects in digital microelectronics and teaches VHDL programming and digital design methodologies.
