Andreas Schmidt is affiliated with the University of Kassel, Germany, and holds a PhD in Computer Science from the University of Koblenz and Landau (2022). His research spans interdisciplinary domains including artificial intelligence, business management, and neuroscience. He has published extensively in journals like NeuroImage, SIAM Journal on Scientific Computing, and Remote Sensing of Environment, demonstrating expertise in computational methods, neural networks, and applied data science. Key research themes include propagation network modeling, home-office productivity analysis, and autonomous driving safety frameworks. His work integrates technical innovation with practical applications, such as optimizing district heating systems and advancing neurovascular coupling studies in primates. While no formal awards are listed, his contributions reflect impactful interdisciplinary collaboration across computer science, environmental science, and medical imaging.
Nuno Horta is a researcher at Instituto de Telecomunicações specializing in electronic design automation. His work integrates machine learning with analog IC design, developing optimization methodologies for RF circuits and biomedical devices. Recent publications focus on neural network-based placement tools, millimeter-wave power amplifiers, and ultra-low-power wearable sensors. Collaborative projects include automated design flows for radiation-hardened space electronics and ANN-based yield optimization techniques. He co-leads research on AI-driven circuit synthesis and serves as reviewer for IEEE TCAS and Integration journals. Current NSF-funded projects explore physically integrated design concepts for additive manufacturing.
Manoj Singh Gaur is a Professor in the Department of Computer Science and Engineering at Malaviya National Institute of Technology Jaipur (MNIT Jaipur), India. With a publication record spanning over two decades from 2003 to present, he has established himself as a prominent researcher in computer security and architecture. His work primarily focuses on network security, Android security, and Network-on-Chip architectures, with extensive collaborations with researchers from institutions worldwide including University of Padua (Italy), University of Southampton (UK), and other Indian institutions. Dr. Gaur's research interests encompass a broad spectrum of cybersecurity challenges, particularly in mobile and cloud environments. His work addresses critical issues such as Android malware detection, information leakage prevention, DDoS mitigation in cloud environments, and secure deduplication techniques. In computer architecture, he has made significant contributions to Network-on-Chip design, fault tolerance mechanisms, and power-efficient router microarchitectures. His research methodology often combines theoretical analysis with practical implementation, resulting in solutions that address real-world security and performance challenges. Analysis of his recent publications (2020-2023) reveals a continued focus on mobile security, particularly Android application security, with numerous papers on vulnerability detection, permission analysis, and information leakage prevention. Simultaneously, his work in Network-on-Chip architectures demonstrates sustained interest in fault-tolerant routing algorithms and performance optimization for multi-core systems. The interdisciplinary nature of his research, bridging security and architecture concerns, represents a distinctive contribution to the field. Dr. Gaur has mentored numerous students who have co-authored publications with him, indicating an active research group focused on cutting-edge security and architectural challenges. His collaborative approach is evident in the diverse set of co-authors spanning multiple continents, reflecting international recognition of his expertise.
Yunsi Fei is a Professor in the Electrical and Computer Engineering Department at Northeastern University, serving concurrently as Associate Dean of Faculty Affairs. She leads the Northeastern site of the NSF IUCRC Center for Hardware and Embedded System Security and Trust (CHEST). Her research focuses on hardware-oriented security, computer architecture, embedded systems, and IoT security, with significant contributions to mitigating side-channel and fault attacks on neural networks and hardware systems. Fei holds a PhD in Electrical Engineering from Princeton University (2004), and bachelor’s and master’s degrees in Electronic Engineering from Tsinghua University. She joined Northeastern in 2011 after faculty roles at the University of Connecticut. Her research interests span secure computer architecture, energy-efficient embedded systems, and underwater sensor networks. Notable projects include RINGS (a NSF-funded IoT resilience initiative) and secure RISC-V processor design. She has received the NSF CAREER Award and multiple best paper awards at top conferences. Fei’s work integrates hardware-software co-design to address vulnerabilities in AI accelerators and cryptographic systems. She leads the Energy-Efficient and Secure Systems (ENESS) Lab and collaborates with industry and academia through CHEST. Recent grants include $1.5M for cybersecurity in additive manufacturing and $1M for spectrum-agile IoT systems. Her awards include a 2023 Distinguished Paper Award (AsiaCCS) and 2022 Best Paper (Great Lake VLSI). She mentors students like Ruyi Ding, who joined LSU as faculty in 2025. Fei also chairs sessions on hardware security and is an affiliated faculty member with Northeastern’s Institute of Information Assurance.
Vasileios Tenentes is an Associate Professor at the Department of Computer Engineering and Informatics, University of Ioannina, Greece. He has held research positions as a Postdoctoral Researcher at the University of Southampton (2014–2018) and a Research Engineer at ARM Ltd (2017–2018). His work focuses on reliability engineering and energy efficiency in embedded systems, with expertise in hardware/software co-design, fault modeling, and VLSI architectures. Education: B.Sc. in Computer Science, University of Piraeus, 2003 M.Sc. in Computer Science, University of Ioannina, 2007 Ph.D. in Computer Science and Engineering, University of Ioannina, 2013 Research Interests: He investigates design methodologies for testability, dependability (reliability, availability, maintainability, security), and energy efficiency in digital systems. His work addresses challenges in many-core architectures, signal/power reliability characterization, and wear-out effects in IoT applications. He contributed to the PRiME project (collaborating with Imperial College, Manchester, Newcastle, and industry partners like ARM Ltd) to optimize embedded system performance and reliability. Scientific Awards: Best Doctorate (Aristoukhos Didaktes) in Informatics, University of Ioannina (2013) Advising and Grants: Advises students via MS Teams under the 'student advisor' program. His Ph.D. research was funded by the Hercules II program, which accepted only 10% of proposals. He co-developed novel architectures for control systems and participated in the PRiME project, a collaborative effort to reduce energy consumption and improve reliability in multi-core embedded systems. Labs and Teams: Affiliated with the VLSI Systems and Computer Architecture Laboratory (VCAS) at the University of Ioannina, focusing on advanced system design and reliability assessment.
Rajit Manohar is the John C. Malone Professor of Electrical & Computer Engineering at Yale University, with appointments in Applied & Computational Mathematics and Computer Science. He is a core member of the interdisciplinary Computer Systems Lab (CSL), which bridges ECE and CS departments. His research focuses on asynchronous VLSI design, neuromorphic computing, and hardware-software co-design. Education: Manohar holds a B.S., M.S., and Ph.D. from the California Institute of Technology. His academic career spans over two decades, with notable contributions to asynchronous circuit theory and neuromorphic engineering. Research Interests: Manohar's work emphasizes energy-efficient asynchronous architectures, concurrency control, and biologically inspired computing. He explores topics like formal methods for circuit verification, cognitive systems, and dynamic sensor networks. His lab develops tools like Fluid (asynchronous synthesis) and Neurobench (neuromorphic benchmarking). Publications: Recent work includes advancements in asynchronous logic synthesis (Maelstrom), neuromorphic frameworks (Neurobench), and scalable brain-computer interfaces (SCALO). His research often intersects NSF-funded projects in energy-aware computing and neuromorphic systems. Awards: Inaugural Misha Mahowald Prize (2025), MIT TR35 (2000s), IBM Goldberg Award (2023) Grants & Labs: Manohar leads NSF-supported initiatives in carbon-aware networking and neuromorphic hardware. The Computer Systems Lab collaborates across disciplines to advance sustainable computing and neuro-inspired architectures.
Bo Liu is a Professor of Electronic Design Automation at the University of Glasgow, specializing in AI-driven electronic design. He holds a B.Eng. from Tsinghua University (2008) and a Ph.D. from KU Leuven (2012). Previously, he was a Humboldt Research Fellow (2012–2013), Lecturer at Wrexham Glyndŵr University (2013–2020), and promoted to Reader (Associate Professor) in 2016 before joining Glasgow in 2020. Research focuses on AI-driven methodologies for analog ICs, antennas, and microwave systems. Key contributions include pioneering AI-assisted optimization in RF design and first industrial-use AI tools for mm-wave ICs. His work bridges machine learning and domain knowledge, addressing bottlenecks in electromagnetic simulations and antenna design complexity. He leads the AIDAC lab and collaborates with industry on EDA tools. Scientific awards include Fellow of IET and Senior Member of IEEE. He serves as an associate editor for IEEE Transactions on CAD and Complex and Intelligent Systems. Current research explores AI-driven design tools, including funded PhD projects on microwave filters, analog IC optimization, and 5G antennas.
Ileana Buhan is an Assistant Professor at Radboud University Nijmegen's Digital Security Group and a member of the CESCA Lab. Her research focuses on hardware security, particularly advancing tools for secure hardware design and mitigating side-channel vulnerabilities. She previously held roles at Riscure (2011–2020) as a security evaluation manager and product manager, and at Philips Research (2008–2010) as a senior scientist. She earned her Ph.D. in Cryptography with Noisy Data from the University of Twente in 2008, recognized with the 2008 EBF European Biometrics Research Industry Award. Her work emphasizes practical security evaluation methods, automated leakage modeling (e.g., ABBY tool), and hardware-software co-design for resistance against side-channel attacks. She actively contributes to conferences like CHES, FDTC, and CARDIS, often in program committee roles. Recent invited talks include topics such as AI-driven vulnerability prediction, architecture-level simulators for root cause analysis, and automated tools for cryptographic implementation security. Her research spans RISC-V processors, microarchitecture analysis, and the intersection of machine learning with hardware security. Notable contributions include frameworks for leakage detection, fault simulation, and explainable side-channel analysis. She balances academic rigor with industry relevance, aiming to bridge gaps between theoretical security and real-world implementation challenges.
Dr. Saraju P. Mohanty is a Professor in the Department of Computer Science and Engineering at the University of North Texas (UNT), where he leads the Smart Electronic Systems Laboratory (SESL). He holds honorary and adjunct positions at IIIT-Naya Raipur, MNIT Jaipur, and Oriental University, Indore, in India. Education: Ph.D. in Computer Science and Engineering, University of South Florida (USF), 2003 Masters in Systems Science and Automation (AI), Indian Institute of Science (IISc), 1999 B.E. in Electrical Engineering (Honors), College of Engineering and Technology, Bhubaneswar (OUAT), 1995 Dr. Mohanty's research is centered on Smart Electronic Systems, with a strong focus on IoT, VLSI, hardware security, and healthcare applications. His work integrates machine learning, embedded systems, and nanoelectronics to develop secure and efficient solutions for smart cities, agriculture, and medical devices. He has authored over 550 peer-reviewed publications and five books, including a PROSE Award-winning textbook. His recent publications reflect a growing emphasis on AI-driven solutions for synthetic media detection, smart farming, driver monitoring, and personalized health. These works demonstrate a trend toward intelligent, edge-based systems that leverage sensor data and lightweight AI for real-time decision-making. Scientific Awards and Honors: Fulbright Specialist Award (2021) IEEE Consumer Electronics Society Outstanding Service Award (2020) IEEE-CS-TCVLSI Distinguished Leadership Award (2018) PROSE Award for Best Textbook (2016) Top 2% Scientist globally (PLOS Biology, 2019–2022) Multiple Best Paper and Best Poster Awards UNT Toulouse Scholars Award (2016–2017) President’s Scout Award, India (1988) Dr. Mohanty has supervised 3 postdocs, 18 Ph.D. students, 29 M.S. theses, and over 40 undergraduate research projects. Eleven of his advisees have received outstanding student awards. He has received multiple UNT Provost’s Thank a Teacher and Honors Day recognitions. His research has been funded by NSF, SRC, US Air Force, NIDILRR, and Mission Innovation. He has held key editorial roles, including Editor-in-Chief of IEEE Consumer Electronics Magazine and founding EiC of IEEE VLSI Circuits and Systems Letter. He is actively involved in IEEE leadership and conference organization, serving on steering committees for IEEE-iSES, ISVLSI, and OCIT. Laboratories and Teams: He directs the Smart Electronic Systems Laboratory (SESL) at UNT, which focuses on cutting-edge research in IoT, edge computing, hardware security, and smart healthcare. The lab fosters interdisciplinary collaboration and has produced numerous award-winning student projects and publications.
Jason Hibbeler is a Senior Lecturer in the Department of Computer Science at the University of Vermont (UVM), where he teaches courses in software engineering, operating systems, algorithms, computer architecture, and mobile-app development. He joined UVM full-time in 2018 after serving as an adjunct instructor and previously worked at IBM in VLSI design automation. His expertise spans systems development and software engineering. Ph.D. from University of Illinois at Urbana-Champaign Focus on Software Engineering, Systems, and Algorithm Development Teaches core computer science courses including CS 3010 (Operating Systems), CS 3050 (Software Engineering), and CS 3750 (Mobile App Development) Experience in VLSI design automation with IBM
Georgios Dimitrakopoulos is an Associate Professor at Harokopio University's Department of Informatics and Telematics (School of Digital Technology) since 2010. He holds a PhD in Electrical and Computer Engineering from the University of Piraeus (2007) and a degree from the National Technical University of Athens (2002). His research focuses on cognitive networks, intelligent transport systems, and automated driving, with over 200 publications and three authored books. He has participated in EU-funded projects (Horizon 2020, ECSEL, etc.) and worked in industry roles including construction company management and startup ventures. Research interests emphasize communication network optimization algorithms, smart city applications, and AI-driven transportation solutions. His work bridges academic research with practical implementations in ICT and autonomous systems. Publications span vehicular networks, UAV path planning, and parallel computing, reflecting interdisciplinary strengths in both hardware optimization and AI-driven systems. He has been recognized as among the world's top 2% scientists by Stanford University rankings. Grants include extensive EU program participation, complemented by industry collaborations. His advising includes supervision of researchers in autonomous systems and network algorithms. The ICSA research group (icsa.hua.gr) likely represents his active lab/teams.
Prof. Rui Paulo da Silva Martins is a Full Professor and Chair Professor at the University of Macau's Faculty of Science and Technology (FCT), Department of Electrical and Computer Engineering. He has held leadership roles including Vice-Rector (Global Affairs) since 2018, and previously served as Dean of FCT (1994-1997). He leads the China Key Laboratory of Analog and Mixed-Signal VLSI Circuits and directs the Institute of Microelectronics (IME). His research focuses on integrated circuits, semiconductor technology, and microelectronics, with over 1,000 publications (h-index 59). He founded UM spin-offs like Digifluidic and co-founded Chipidea/Silergy. He is an IEEE Life Fellow and Full Member of the Lisbon Academy of Sciences. Educations: BSc, MSc, PhD, and Aggregation in Electrical Engineering from Instituto Superior Técnico, Lisbon (1980-2001) Research interests span VLSI design, analog circuits, semiconductor fabrication, and energy-efficient electronics. His work has led to 71 patents across USA, China, and Taiwan. Recent projects include AI-driven circuit design and IoT applications. Awards: Medal of Merit in Education (2021), IEEE CEDA Award (2016), Order of Engineers (2024) Advised 47 doctoral/master's theses and led over 1,000 publications. Managed UMTEC and incubated tech startups. Current responsibilities include IEEE leadership roles and global academic collaborations through AULP. Labs: China Key Lab of VLSI (Founder/Director 2011-2022), IME Director since 2019
Nuno Cavaco Gomes Horta is an Associate Professor at the Department of Electrical and Computer Engineering, Higher Technical Institute (IST), University of Lisbon. He is a Senior Researcher and Head of the Integrated Circuits Group at the Instituto de Telecomunicações. His academic journey includes Licenciado (1989), MSc (1992), PhD (1997), and Habilitation (Agregação, 2014) degrees in Electrical Engineering from IST. Education: Licenciado, MSc, PhD, and Habilitation in Electrical Engineering from IST, University of Lisbon. Research focuses on data science, computational intelligence, analog IC design automation, computational finance, and intelligent computing. He has supervised over 90 postgraduate theses (MSc/PhD) and authored/co-authored over 150 publications across books, journals, and conferences. He coordinates European and National R&D projects and chairs conferences like AACD 2014, PRIME 2016, and SMACD 2016. Professional roles include Associated Editor of Integration, The VLSI Journal (Elsevier), and reviewer for IEEE journals (e.g., TCAD, TEC, TCAS) and ESWA/ASC. He leads the Integrated Circuits Group at Instituto de Telecomunicações, advancing automation in analog design and computational finance applications.
Vladimir Stojanović is an Adjunct Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research focuses on integrated electronic-photonic systems-on-chip, emerging technologies, and VLSI design. He has held positions at MIT (2005–2013) and Rambus, Inc. (2001–2004). Stojanović leads research initiatives in the Berkeley Deep Drive (BDD), Berkeley Emerging Technologies Research (BETR), and Center for Energy Efficient Electronics Science (E3S). Education: Ph.D. (2005, Stanford), M.S. (2000, Stanford), and Dipl. Ing. (1998, University of Belgrade). Awards include the IEEE Fellow (2024), NSF CAREER Award (2009), and multiple best-paper recognitions. He co-founded Ayar Labs, Numericcal, and MaxLinear (formerly NanoSemi). Key research areas include silicon photonics integration, nanoelectromechanical systems (NEMS), and energy-efficient computing architectures. His work spans optical interconnects, quantum photonics, and biomedical sensors, with emphasis on co-design of electronics and photonics in advanced CMOS processes.
Jens Lienig has been a Professor at Technische Universität Dresden since 2002, where he directs the Chair of Development and Design of Precision Engineering and Electronics. His research spans Electronic Design Automation (EDA), electromigration analysis, 3D IC design, constraint-driven methodologies, and precision device development. He holds memberships in IEEE, VDE/VDI GMM, and technical committees, and has led conferences like ISPD 2021 as General Chair. Research interests focus on: Reliability Engineering : Electromigration-aware IC design, thermal/stress modeling in interconnects. Advanced Design Automation : 3D physical design algorithms, analog layout generators, constraint propagation. Precision Devices : MEMS sensors, peristaltic pumps, SAW motors, pyroelectric detectors. Recent articles (2019–2025) emphasize electromigration robustness, aerosol sensor signal processing, and open-source EDA tools. Over 15 doctoral students have completed under his supervision, including dissertations on electromigration, MEMS, and infrared sensors.
