Find Academic Supervisors

Calin BeltaView profile

Professor

• Control Theory
• Cyber-Physical Systems
• Formal Methods
• +5 more

Calin Belta is the Brendan Iribe Endowed Professor of Electrical and Computer Engineering and Computer Science at the University of Maryland, College Park. He is affiliated with the Institute of Systems Research (ISR) and the Maryland Robotics Center (MRC), and holds a Research Professor position at Boston University's College of Engineering. His work bridges control theory, formal methods, and machine learning to ensure safety in cyber-physical and data-driven systems, with applications in robotics, autonomous driving, and systems biology. Research Interests: Focus on dynamics and control theory, formal methods for verification and control synthesis, robotics, autonomous systems, and synthetic biology. Recent projects include PROGENIC (collaborating with MIT, UChicago, and UDelaware) and safety-critical control for heterogeneous robotic teams. Key Achievements: General Chair of the 2025 MRC Symposium, recipient of AFOSR Young Investigator Award (2008), NSF CAREER Award (2005), and IEEE Fellow. His work on formal methods for autonomous systems has led to impactful tools for safety assurance in robotics and AI. Grants: NSF EFRI PROGENIC grant (2024), multiple industry partnerships. Advising: Mentored students like Wenliang Liu (PhD 2024, now at Amazon), and collaborator Marius Kloetzer (shared HSCC Test of Time Award 2025). Labs/Teams: Maryland Robotics Center, Institute for Systems Research, and Boston University collaborations.

• Emerging memory and storage technologies
• Embedded systems
• Cyber-Physical Systems (CPS)
• +5 more

Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.

Dan MoldovanView profile

Professor

• Natural Language Processing
• Artificial Intelligence
• Question Answering Systems
• +8 more

Dan Moldovan is a Professor in the Department of Computer Science at The University of Texas at Dallas, within the Erik Jonsson School of Engineering and Computer Science. He leads the InterVoice Research Center in the Human Language Technology Research Institute and has played a pivotal role in advancing question answering technologies, achieving top performance in multiple TREC evaluations (TREC-8 to TREC-13). Education: Ph.D. in Electrical Engineering and Computer Science, Columbia University (1978) M.S. in Electrical Engineering and Computer Science, Columbia University (1974) Diploma Engineer in Electrical Engineering, Polytechnic Institute of Bucharest (1969) His research centers on Natural Language Processing and Artificial Intelligence , with major contributions in Question Answering Systems , Knowledge Acquisition from Text (KAT) , Word Sense Disambiguation , and Semantic Indexing and Retrieval . He has developed systems to enrich WordNet with domain knowledge and transform it into a logical knowledge base. His work also explores distributed and parallel processing for scalable NLP algorithms. The recent publications (2005–2007) highlight his focus on semantic reasoning, multilingual QA, validation of answers using logic provers like COGEX, and the semantics of noun compounds. These works reflect a strong trend toward deep semantic understanding, contextual reasoning, and integration of logic in NLP systems. Scientific Awards: Best performance in TREC-8 (1999), TREC-9 (2000), TREC-11 (2002), TREC-12 (2003), and TREC-13 (2004) QA competitions Dan Moldovan has advised numerous research projects and led major initiatives such as Extended WordNet and the development of PowerAnswer. He has secured significant research support through appointments and leadership roles across institutions. His work in distributed NLP and parallel processing of rule-based systems reflects a long-standing interest in scalable AI architectures. He has directed several key research labs: InterVoice Research Center, UTD Parallel and Distributed Computer Systems Laboratory, University of Southern California Parallel Knowledge Processing Laboratory, University of Southern California

Azadeh DavoodiView profile

Professor

• Electronic Design Automation (EDA)
• Integrated Circuit Design
• Machine Learning in Hardware
• +5 more

Azadeh Davoodi is a Vilas Distinguished Achievement Professor and Associate Chair of Undergraduate Studies in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. Her research focuses on Electronic Design Automation (EDA), integrated circuit debug, and machine learning applications in VLSI design. She holds editorial roles in journals like IEEE TCAD and ACM TRETS, and has chaired major conferences such as ISPD 2015 and served on technical program committees for DAC, ICCAD, and others. Education: PhD in Electrical Engineering, University of Maryland-College Park (2006) Research Interests: Machine learning for VLSI chip design VLSI design automation for machine learning IC-CAD for emerging nanotechnologies Hardware security Recent Research Trends: Her work bridges machine learning and hardware design, with publications on neural network optimization, distributed inference, and explainable AI for circuit design. She emphasizes energy-efficient CNNs, latency reduction in edge computing, and security in split manufacturing. Awards: 2025 DATE Best Paper Candidate 2024 Vilas Distinguished Achievement Professor 2015 ACM Best Paper Award 2011 NSF CAREER Award Service and Grants: Leads NSF-funded projects on explainable ML for CAD and holds grants for distributed neural network synthesis. Her service includes roles as IEEE HKN member and editorial board positions. Labs/Teams: Engages in interdisciplinary research teams at UW-Madison, focusing on EDA innovation and hardware-software co-design.

Hafizul AsadView profile

Lecturer

• Formal Verification
• Hybrid Systems
• Intrusion Detection Systems
• +5 more

Dr. Hafizul Asad serves as a Lecturer in Dependability at City St George's, University of London, leveraging his PhD in Electrical Engineering (City University of London, 2016) and MS in Aerospace Engineering (University of Belgrade, 2008) to advance cybersecurity and formal verification research. His expertise bridges critical infrastructure protection and cyber-physical systems security, with significant contributions to IoT/IIoT security frameworks. His educational journey includes: PhD in Electrical Engineering, City, University of London (2012-2016) MS in Aerospace Engineering, University of Belgrade, Serbia (2007-2008) BSc in Electrical and Electronics Engineering, University of Engineering and Technology Peshawar, Pakistan (1999-2003) Asad's research centers on formal verification of hybrid systems and verifiable intrusion detection mechanisms for interconnected environments. He pioneers provably robust security architectures for IoT/IIoT systems, emphasizing mathematical verification to ensure system resilience against cyber threats. His work integrates diversity principles to create defense-in-depth strategies for critical infrastructure, with recent focus on wind turbine cyber-safety and industrial control system protection. Analysis of his 15 most recent publications (2014-2025) reveals an evolution from aerospace applications and analog circuit verification toward cutting-edge cybersecurity for cyber-physical systems. His 2023-2025 work demonstrates increasing specialization in IoT security and formal methods, while maintaining foundational contributions to diversity-based security architectures established in his 2015-2018 research. No scientific awards or prizes are documented in the provided materials, though he maintains professional standing as a British Computer Society member and Higher Education Academy Associate Fellow. Details regarding doctoral student supervision or specific research grants are not disclosed in the source text. His professional trajectory indicates significant project involvement, including the D3S security project at City University of London (2015-2018) and Rolls-Royce-funded Future Systems Simulator development at Cranfield University (2018-2019), though current laboratory affiliations remain unspecified.

• VLSI CAD
• Low-power IC Design
• Mixed-signal IC Design
• +5 more

Riadul Islam serves as an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), maintaining his primary office in room 316 of the Information Technology and Engineering (ITE) Building. His academic appointment focuses on hardware design and verification within the institution's engineering framework. His educational qualifications include: Ph.D. in Computer Engineering from UCSC (2017) M.A.Sc. in Electrical and Computer Engineering from Concordia University, Montreal (2011) B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (2007) Professor Islam's research centers on VLSI CAD tools and low-power digital/mixed-signal IC design , with significant contributions to current-mode clock networks, vehicular security systems, and error-robust circuit architectures. His work increasingly integrates machine learning for design automation while exploring neuromorphic computing applications and secure hardware implementations. This multidisciplinary approach bridges traditional IC design with modern AI-driven optimization techniques. Analysis of his 2023-2025 publications reveals three dominant research thrusts: (1) Machine learning applications in early-stage Design Rule Checking (DRC) prediction and clock network optimization, (2) Graph-based intrusion detection systems for automotive networks (particularly CAN bus security), and (3) Event-based vision systems and neuromorphic computing architectures. These areas demonstrate consistent innovation in merging hardware design with AI/ML methodologies for enhanced system reliability and efficiency. He directs the UMBC VLSI and SoC Research Group , which develops energy-efficient clocking networks, secure vehicular communication protocols, and compute-in-memory architectures. The lab maintains active collaboration with industry partners on hardware security and neuromorphic computing initiatives while supporting graduate student research in cutting-edge IC design methodologies.

Paul FranzonView profile

Professor

• Quantum Information Science
• Machine Learning & AI Hardware
• 3D Integration
• +4 more

Paul Franzon is the Cirrus Logic Distinguished Professor and Associate Department Head for Graduate Affairs at the Department of Electrical and Computer Engineering, North Carolina State University. He holds a PhD and Bachelor's in Electrical Engineering and a Bachelor's in Physics/Mathematics from the University of Adelaide, Australia. His research focuses on quantum information science, machine learning-driven hardware design, 3D integration, and high-speed systems. Education: PhD in Electrical Engineering, University of Adelaide (1988) Bachelor's in Electrical Engineering, University of Adelaide (1984) Bachelor's in Physics and Mathematics, University of Adelaide (1982) Research Interests: Quantum computing and algorithm optimization AI-driven design automation for 3D integrated circuits High-speed communication systems Hardware security and FPGA acceleration Awards & Honors: IEEE Fellow (2006) Alcoa Foundation Distinguished Engineering Research Award (2005) NC State Alumni Distinguished Undergraduate Professor Award (2003) NSW Australia Expatriate Scientist Award (2003) Advising & Grants: Advised PhD student Priyank Kashyap (2023 graduate) Recipient of NSF Young Investigators Award (1993) Labs & Collaborations: Center for Advanced Electronics Through Machine Learning (CAEML) IEEE EPS Society (Associate Editor)

• Software Engineering
• Workflow Management Systems
• Image Analysis
• +2 more

Michał Turek is a Professor at the Department of Applied Informatics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His primary workplace is located in room 303a of building C-2, and he maintains active contact through email (mitu@agh.edu.pl) and phone (+48 12 617 52 03), indicating current academic engagement. His research spans Software Engineering with particular emphasis on Workflow Management Systems integration with industrial applications, Image Analysis for 3D surface inspection, and Agile Methodologies implementation. Turek has pioneered innovations in Scrum adaptation for multi-project environments and software product lines, while developing formal verification frameworks for business processes and service-oriented architectures. His work bridges theoretical computer science with practical industrial solutions, especially in automated damage identification systems and workflow optimization. Analysis of his 15 most recent publications reveals consistent focus on workflow system intelligence (2020-2022), with significant contributions to automatic correction mechanisms and smart procedure integration. Earlier works (2010-2016) demonstrate deep expertise in formal verification methods, Scrum economics, and 3D surface analysis techniques. The publications show interdisciplinary convergence between software engineering, computer vision, and industrial automation, with recurring themes of system resilience and process optimization across both English and Polish scholarly outputs.

• Biomedical Engineering
• Biomedical Signal Processing
• Entropy Analysis
• +7 more

Georgios Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He holds a PhD from the National Technical University of Athens and has been a faculty member at the University of Ioannina since 2002, progressing from Lecturer to Associate Professor in 2018. He has also served as temporary teaching staff at the University of Patras, University of Crete, and University of Ioannina in the late 1990s and early 2000s. Education: B.Sc. in Computer Engineering (Diploma), National Technical University of Athens (NTUA), 1987–1992 MSc in Advanced Methods in Computer Science (Distributed and Parallel Systems), Queen Mary, University of London, 1992–1993 PhD in Computer Engineering, NTUA, School of Electrical and Computer Engineering, 1993–1997 His research interests lie at the intersection of Biomedical Engineering and Computing Systems , with a strong emphasis on Biomedical Signal Processing , Entropy Analysis , and Machine Learning . He has pioneered work in Bubble Entropy —a parameter-free entropy measure—and developed fast algorithms for entropy computation. His work also extends to compiler design and parallel computing, particularly in the automatic parallelization of recursive functions and loops. The trends in his recent publications reflect a dual focus: (1) biomedical applications involving entropy, heart rate analysis, and disease diagnosis using machine learning (especially Random Forests and SVMs), and (2) high-performance computing, including parallelization techniques and compiler optimizations for multi-core and SVP architectures. His research is highly interdisciplinary, combining signal processing, algorithm design, and clinical applications. Scientific Leadership and Recognition: Guest Editor, Special Issue on “Entropy in Biomedical Engineering”, Entropy (MDPI) Member of the IPAN Laboratory, University of Ioannina Active contributor to IEEE, Elsevier, and MDPI journals He has supervised several graduate students and is involved in funded research projects such as Palimpsest and Homore , focusing on smart systems for cultural interaction and elderly monitoring. His advising contributions are evident in co-authored papers with students like Evanthia Tripoliti and Aristeidis Mastoras. He teaches both undergraduate and postgraduate courses, including Compilers I/II and Biomedical Data Analysis . Laboratories and Teams: He is a member of the IPAN lab at the University of Ioannina, which supports interdisciplinary research in informatics and biomedical applications. His collaborative network includes researchers from Greece and abroad, particularly in the fields of biomedical signal analysis and entropy-based methods.

Cesare TinelliView profile

Professor

• Automated Reasoning
• Satisfiability Modulo Theories (SMT)
• Model Checking
• +7 more

Cesare Tinelli is the F. Wendell Miller Professor of Computer Science at the University of Iowa within the College of Liberal Arts and Sciences. He is a co-director of the Computational Logic Center and leads the development of critical tools like the CVC4 and cvc5 SMT solvers, as well as the Kind model checker. His academic credentials include: Ph.D. in Computer Science (1999), University of Illinois at Urbana-Champaign M.S. in Computer Science (1995), University of Illinois at Urbana-Champaign Laurea in Scienze dell'Informazione (1990), University of Bari Research Interests : Tinelli specializes in Automated Reasoning , particularly Satisfiability Modulo Theories (SMT) , Model Checking , Software Verification , and Formal Methods . His recent work explores Inductive Reasoning in SMT , Proof-Certificate Generation , and Logical Frameworks for Proof Systems . His methodologies bridge theoretical advancements with practical implementations, impacting both academia and industry. Scientific Contributions : Tinelli's research drives innovation in SMT solving, model checking, and automated theorem proving. His 15 most recent publications span topics from stateful protocol testing ( Saecred ) to proof certification ( IsaRare ) and generalized optimization ( Generalized OMT ). Awards and Recognition : NSF CAREER Award (2003) Haifa Verification Conference Award (2010) CAV Award (2021) Advising and Collaborations : His former students and postdocs hold positions at leading institutions like NASA, Intel, MIT, and EPFL. He collaborates with organizations such as Amazon, Facebook, General Electric, and Microsoft.

Andreas KrinkeView profile

Researcher

• Analog Circuit Design
• Mixed-Signal Integrated Circuits
• Constraint Propagation
• +3 more

Andreas Krinke is a Researcher at the Institute of Microengineering and Electronic Design, TU Dresden, specializing in constraint-guided design of integrated analog circuits. He actively participates in BMBF-funded projects including HyPerStripes, MANNHEIM-KI4BoardNet, and Technology for Trust, focusing on electronic design automation and reliability engineering. His research centers on analog/mixed-signal IC design with emphasis on constraint propagation, physical design automation, and reliability analysis. Key contributions include methodologies for constraint handling from system-level to tape-out, open-source EDA tool development, and applications in flexible electronics and automotive systems. His work bridges theoretical constraints with practical implementation challenges in nanoscale and automotive electronics. Publication trends since 2011 reveal consistent focus on constraint propagation techniques, evolving toward flexible electronics (2024), open-source layout verification (2024), and automotive mission profile analysis (2021-2022). Recent work integrates AI for trustworthy systems while maintaining core expertise in constraint-driven design flows for analog circuits. Krinke teaches Fundamentals of Electrical Engineering seminars and design automation exercises. His project portfolio includes: HyPerStripes, MANNHEIM-KI4BoardNet, Technology for Trust (BMBF) ELDA-MP (BMWi) autoSWIFT, RESCAR 2.0 (BMBF) These initiatives target automotive electronics, design automation, and trustworthy computing systems. He collaborates within TU Dresden's Institute of Microengineering and Electronic Design, working closely with Prof. J. Lienig's research group on constraint-driven methodologies and open-source EDA ecosystems for next-generation circuit design.

Anastasios GounarisView profile

Professor

• Distributed Databases
• Autonomous data processing
• Big Data Management
• +7 more

Anastasios Gounaris is a Professor at the Department of Informatics, Aristotle University of Thessaloniki, where he has been a faculty member since April 2008. He previously served as a Visiting Lecturer at the University of Cyprus (2007-2008) and held research positions at the University of Manchester and CERTH. His academic journey includes a PhD from the University of Manchester (2005), an MPhil from UMIST (2002), and a degree in Electrical and Computer Engineering from Aristotle University of Thessaloniki (1999). His research spans Distributed Databases, Autonomous Data Processing, Big Data Management, Workflow Optimization, and Data Mining . He has made significant contributions to large-scale data management systems, massive parallelism techniques, and business process analytics. His work bridges theoretical computer science with practical industrial applications, particularly in predictive maintenance and edge computing environments. His recent publications (2024-2025) demonstrate a strong focus on process mining, anomaly detection, predictive maintenance systems, and edge analytics . These works address critical challenges in handling evolving data streams, optimizing task allocation in resource-constrained environments, and developing parameter-free algorithms for real-world applications. His research shows consistent progression from foundational database systems work to cutting-edge applications in industrial IoT and healthcare analytics. Dr. Gounaris has successfully supervised numerous PhD students to completion, including Athanasios Naskos (2017), Georgia Kougka (2017), Christos Bellas (2022), Theodoros Toliopoulos (2022), Anna-Valentini Michailidou (2023), Ioannis Mavroudopoulos (2024), and Konstantinos Varvoutas (2025). His research has been supported by multiple national and European projects including DataflowOpt, PRECognition, NavGreen, CUREX, Rainbow, Lifechamps, and Trineflex. He is an active member of Datalab (formerly Delab) and has contributed to industry applications through collaborations with companies such as Comidor, Gnomon, Istognosis, Atlantis, AFS, Follow-Apps, Sboing, and Upcom. His work demonstrates a strong commitment to transferring research results to real-world applications while maintaining academic rigor.

Tolga AyavView profile

Professor

• Formal Methods for Software Testing
• Hardware Component and On-Chip System Tests
• Real-Time and Fault-Tolerant Embedded Systems
• +5 more

Professor Tolga Ayav is affiliated with the Department of Computer Engineering at Izmir Institute of Technology , where he has served as faculty since 2006. He received his BSc in Electrical and Electronics Engineering (1995) from Dokuz Eylül University, MSc in Computer Engineering (1999) from Izmir Institute of Technology, and PhD in Computer Engineering (2004) from Ege University. He was a researcher at INRIA Rhone-Alpes in 2005. Education BSc: Electrical and Electronics Engineering, Dokuz Eylül University (1995) MSc: Computer Engineering, Izmir Institute of Technology (1999) PhD: Computer Engineering, Ege University (2004) Research Interests include formal methods for software testing, hardware component and on-chip system tests, real-time and fault-tolerant embedded systems, blockchain applications, and machine learning. His work focuses on: Formal verification techniques Real-time system optimization Hardware-software co-design Blockchain-based security solutions Mathematical modeling in testing Recent Publications span topics like: Deep learning for livestock monitoring Blockchain in IoT security Fourier expansion in fault analysis Optimized data replication strategies Finite state machine testing Scientific Awards include: Best Paper Award at IEEE CBDCom 2016 for cloud data replication research Teaching includes courses such as: CENG 312: Computer Networks CENG 523: Advanced Topics in Real-Time Systems CENG 215: Circuits and Electronics Projects he has led include: TÜBİTAK TEYDEB: Spectrally Efficient Small Cell Base Station Design BAP: Dedicated Server for Physical Network Applications Lab Leadership : He leads the DCS Research Group at Izmir Institute of Technology, focusing on distributed computing and real-time systems.

• Economics
• International Trade
• Monetary Policy
• +5 more

Paul Krugman is a Nobel laureate economist and prominent public intellectual, formerly with the New York Times and currently authoring a widely-read Substack newsletter. He maintains an academic affiliation with the Stone Center on Socio-Economic Inequality at the City University of New York's Graduate Center, where he engages with economic research and policy analysis. Professor Krugman's scholarly work spans international trade theory, monetary policy, and political economy, with recent focus on contemporary economic challenges including stagflation risks, AI's energy demands, and the economic impacts of trade policy. His research consistently bridges academic rigor with accessible public commentary, making complex economic concepts understandable for broader audiences while maintaining scholarly precision. His expertise in international economics stems from foundational work that earned him the Nobel Prize. Recent analysis shows Krugman examining nonlinear economic effects of policy decisions, with particular attention to how seemingly incremental changes can trigger disproportionate economic consequences. His writing demonstrates how economic theory applies to real-world political decisions, especially regarding trade wars, immigration policy, and energy transitions. Nobel Prize in Economics As a public intellectual, Krugman actively participates in policy debates through multiple channels, connecting academic economics with current events. His commentary frequently influences economic discourse in media and political circles, and he is known for his incisive analysis of economic policy proposals and their potential consequences. His work with the Stone Center indicates ongoing engagement with academic research despite his primary role as a public commentator.

Bruno FerresView profile

Associate Professor

• Embedded Systems
• Formal Verification
• FPGA Design
• +5 more

Bruno Ferres is an Associate Professor at Université Grenoble Alpes (UGA), affiliated with the Verimag laboratory and the UFR IM²AG school. He holds a PhD in Computer Science from UGA (2022) and an engineering degree from Grenoble INP - Ensimag. His research focuses on formal verification of embedded systems, FPGA design methodologies, hardware security, and compilation techniques. He has led projects such as the ERCTool for transistor-level electrical rule checking and the QECE framework for design space exploration. He teaches courses on hardware architectures, low-level programming, and hardware security. Education: PhD in Computer Science (2018–2022), TIMA Lab, UGA MSc in CyberSecurity (2017–2018), UGA Engineering Degree in Computer Science/Applied Mathematics (2015–2018), Grenoble INP - Ensimag Research Projects: ANR SxC (Shannon meets Cray) ANR Arsène (Hardware/Software Security) ANR CAOTIC (Timing Interference) Labs: Verimag, TIMA, and collaborations with LIP (Lyon) and Aniah (Grenoble). His work bridges formal methods, FPGA optimization, and security, with applications in electrical rule checking and compiler design. He advises PhD and master’s students on topics like fault-injection countermeasures and multi-core interference analysis.