جست‌وجوی استاد و پژوهشگر

Umang Mathurمشاهده پروفایل

استادیار

• Formal Methods
• Concurrency
• Programming Languages
• +۴ مورد دیگر

Umang Mathur is an Assistant Professor at the National University of Singapore's School of Computing, where he leads the FOCS Lab and is affiliated with PLSE@NUS. His research focuses on Formal Methods , Concurrency , and Decidability in Programming Languages and Software Engineering . PhD in Computer Science from the University of Illinois at Urbana-Champaign (advisor: Prof. Mahesh Viswanathan) Former Research Scientist at Facebook Inc. and Research Fellow at the Simons Institute Recipient of Google PhD Fellowship, 2024 CPP Distinguished Paper Award, 2023 ACM SIGPLAN Award, and ASPLOS 2022 Best Paper Award His recent work explores algorithmic techniques for detecting concurrency bugs , decidable program verification , and synthesis , with a focus on weak memory models, predictive monitoring, and automata-theoretic approaches. Articles span topics like causal concurrency, tree clock data structures, and probabilistic counting algorithms, reflecting interdisciplinary intersections of logic and systems research. Scientific Awards Google PhD Fellowship 2024 CPP Distinguished Paper 2023 ACM SIGPLAN Distinguished Paper 2022 ASPLOS Best Paper 2018 ESEC/FSE Distinguished Paper He advises PhD students in Formal Methods and supervises teams in the FOCS Lab. Teaching includes advanced modules on Automata Theory, Logic, and Verification at NUS.

• Computational Linguistics
• Natural Language Processing
• Formal Language Theory
• +۲ مورد دیگر

Giorgio Satta is a Full Professor at the Department of Information Engineering , University of Padua, Italy. He received his Ph.D. in Computer Science from the University of Padua in 1990. His career includes research positions at Fondazione Bruno Kessler (Trento) and the University of Pennsylvania (IRCS). Research Focus : His work centers on computational linguistics and formal language theory , with emphasis on: Parsing algorithms (CCG, TAG, LCFRS) Computational complexity of grammar formalisms Probabilistic language modeling Dependency parsing and synchronization techniques Professional Service : He chaired the European Chapter of the ACL (2009-10), served on editorial boards for Computational Linguistics , Transactions of the ACL , and co-chaired ACL-2001/IWPT-2001. Teaching : Current courses include Automata, Languages, and Computation and Natural Language Processing (2024-25).

• Runtime Verification
• Formal Methods
• Concurrency Theory
• +۷ مورد دیگر

Adrian Francalanza is a Professor in the Department of Computer Science at the Faculty of Information and Communication Technology, University of Malta. His research is centered on formal methods, runtime verification, and concurrency, with a focus on monitorability and distributed systems. His research interests include: Runtime Verification and Monitor Synthesis Session Types and Protocol Safety Concurrency and Actor-Based Systems Branching and Linear-Time Temporal Logics Probabilistic and Decentralized Monitoring Formal Tools for Cyber-Physical and Distributed Systems The recent publications highlight a strong trend in theoretical and practical advances in monitorability, especially for branching-time and probabilistic systems. His work bridges theory with implementation, often resulting in tools like STMonitor and DetectEr. There is a clear emphasis on session types, runtime enforcement, and the verification of communication protocols in real-world systems such as REST APIs and SMTP. Scientific awards include: Distinguished Paper Award at ECOOP 2025 Best Paper Award at DisCoTec 2022 He has been actively involved in advising and organizing major academic events. He served as Program Chair for GandALF 2024 and 2025, FORTE 2024, and VORTEX workshops. He led a three-year project funded by Rannis on Theoretical Foundations for Monitorability in collaboration with Reykjavik University. He has received grants and recognition for developing practical tools such as DetectEr and STMonitor, which support runtime monitoring of Erlang and session-typed systems. He is associated with several research teams and labs, including: Runtime Verification and Monitorability Research Group at University of Malta Collaborators on the DetectEr project Developers of STMonitor and polyLarva tools International collaborators at Reykjavik University and beyond

Anne Remkeمشاهده پروفایل

استاد

• Dependability
• Security
• Critical Infrastructures
• +۵ مورد دیگر

Professor Anne Remke leads the safety-critical systems group at the Faculty of Mathematics and Computer Science at Westfälische Wilhelms-Universität Münster since October 2014. She is also affiliated with the Design and Analysis of Communication Systems group at the University of Twente, where she served as assistant professor from June 2010 and became associate professor in March 2016. Her research focuses on dependability and security in critical infrastructures, particularly electrical power systems and telecommunication networks. Her educational background includes a PhD (2008) and MSc (2004) in Computer Science from the University of Twente and RWTH Aachen respectively. Her doctoral research focused on 'Model Checking Structured Infinite Markov Chains,' for which she publicly defended her thesis in June 2008. Professor Remke's research interests center on cyber-physical systems, with particular focus on evaluation of charging strategies for local energy storage in smart homes and security of control networks (SCADA) in smart grids. Her work bridges theoretical model checking techniques with practical applications in critical infrastructure protection. She has made significant contributions to the analysis of hybrid Petri nets, stochastic models, and the development of tools for dependability evaluation. Her recent publications demonstrate a strong trend toward integrating machine learning with formal verification methods for cyber-physical systems. The research spans stochastic hybrid systems, reachability analysis, and security evaluation of smart grid infrastructures, showing consistent growth in both theoretical foundations and practical applications of dependability analysis. Veni award from Dutch Science foundation (NWO) for 'Counting on a reliable water supply' GI/ITG MMB prize for best diploma thesis in computer and communication systems Best Paper Award at Valuetools 2023 conference Best Repeatability and Artifact Evaluation Award at QEST21 Teaching award from Fachschaft FB10 (2019) Professor Remke has successfully secured multiple research grants including the DFG project 'RealyST: Reachability Analysis for Stochastic Hybrid Systems' in collaboration with RWTH Aachen. She has supervised numerous students including Katharina Sichma, Pauline Blohm, Joanna Delicaris, Verena Menzel, Mathis Niehage, Jonas Stübbe, and Lisa Willemsen. Her research group actively participates in international collaborations and standardization efforts in critical infrastructure security. The safety-critical systems group maintains several research tools including HYPEG (for simulation and analysis of hybrid Petri nets), TimeNET (a GUI for modeling hybrid Petri nets), and a Smart Neighbourhood Simulation Tool for community energy storage and trading. These tools support their research in modeling and evaluating complex critical infrastructures through both analytical methods and simulation techniques.

• Real-time Systems
• Model Checking
• Critical Systems
• +۴ مورد دیگر

Yasmina Abdeddaïm is an Associate Professor at Université Gustave Eiffel and affiliated with ESIEE Paris. She works within the Laboratoire d'Informatique Gaspard-Monge (Softwares, Networks and Real-time team) and serves as Head of the Master in Artificial Intelligence and Cybersecurity (AIC) program. Her research focuses on real-time systems, critical systems, and scheduling algorithms. University: Université Gustave Eiffel Role: Head of Master AIC program Laboratory: Laboratoire d'Informatique Gaspard-Monge Team: Softwares, Networks and Real-time Her research spans real-time systems , mixed-criticality scheduling , energy-harvesting systems , and probabilistic schedulability . Recent publications analyze compilation optimization impacts on timing variability and propose new models for real-time deep neural networks over GPUs. She employs formal methods like timed automata for scheduling verification. Her teaching includes courses on Real-time Systems , Model Checking , Critical Application Development , and Artificial Intelligence . She is based at Cité Descartes, Champs-sur-Marne, France, with office contact details provided.

• Logic-in-memory
• Machine learning
• Nanocomputing
• +۷ مورد دیگر

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

Irène Marcoviciمشاهده پروفایل

استاد

• Probability Theory
• Dynamical Systems
• Cellular Automata
• +۴ مورد دیگر

Irène Marcovici is a Professor in the Department of Mathematics at the University of Rouen Normandy, affiliated with the Raphaël Salem Mathematics Laboratory (LMRS). She leads the Probability and Dynamical Systems team within LMRS and participates in the ALEA and SDA2 working groups of the GDR Informatique Fondamentale et ses Mathématiques. PhD in Mathematics (2013, University of Paris Diderot) Habilitation à Diriger des Recherches (2021, University of Lorraine) Her research focuses on probability theory , dynamical systems , and cellular automata , with significant contributions to percolation theory, self-organization phenomena, and combinatorics on words. She investigates how randomness influences complex systems, particularly through probabilistic cellular automata and their ergodic properties. Analysis of her recent publications (2021-2025) reveals a strong emphasis on percolation dynamics (e.g., corner percolation with directional bias), self-stabilization mechanisms in cellular systems, and combinatorial structures like Kolakoski sequences. Her work bridges theoretical computer science and pure mathematics, often employing stochastic methods to solve problems in symbolic dynamics and discrete geometry. Supervision & Collaborations: Currently supervising Maxence Poutrel (with Jérôme Casse) Previously supervised Pierrick Siest (2021-2024), Jocelyn Begeot (now Associate Professor), and Pierre-Adrien Tahay (now PRAG at Telecom Nancy) Regular collaborations with Régine Marchand, Nazim Fatès, and Pascal Moyal Laboratory Context: As leader of the Probability and Dynamical Systems team at LMRS, she contributes to France's national research infrastructure in fundamental mathematics, with connections to CNRS and international working groups focused on automata theory and discrete probability.

Yassine Lakhnechمشاهده پروفایل

استاد

• Computer Security
• Cryptography
• Formal Verification
• +۵ مورد دیگر

Yassine Lakhnech is a Professor at the University Joseph Fourier (Grenoble 1), leading the 'Distributed and Complex Systems' research team within the VERIMAG laboratory. His work focuses on computer security, cryptography, formal verification, and programming language semantics. He has been actively involved in coordinating major interdisciplinary research initiatives like the PERSYVAL-lab, which addresses cyber-physical systems (CPS) challenges. His research bridges computational and formal approaches, with contributions to cryptographic protocol analysis, information flow control, and automated theorem proving. Key projects include the development of tools like HERMES for cryptographic protocol verification and involvement in ANR-funded projects such as Verso, PROSE, and AVOTE. He has also organized international conferences and workshops, including the Canada-France MITACS Workshop on Foundations & Practice of Security and the Eighth ACM/IEEE International Conference on Formal Methods and Models for Codesign. His publications span over 147 papers, with an h-index of 25 and g-index of 42, reflecting significant contributions to formal methods, security protocols, and hybrid systems. Despite his role as Vice President of Research, he maintains active scientific productivity, emphasizing the integration of theoretical and practical advancements in CPS and security.

Sylvie Putotمشاهده پروفایل

استاد

• Formal Methods
• Static Analysis
• Cyber-Physical Systems
• +۷ مورد دیگر

Sylvie Putot is a Professor of Computer Science at École Polytechnique, where she focuses on formal verification of numerical programs and cyber-physical systems. She leads the Cosynus team at LIX laboratory and organizes the LIX Seminar series. Current affiliation: École Polytechnique (Computer Science Department) Prior affiliation: CEA LIST (developer of FLUCTUAT static analyzer) Her research spans formal methods for cyber-physical systems , emphasizing reachability analysis , invariant synthesis , and probabilistic verification . She combines abstract interpretation with zonotopic domains and constraint programming to address numerical stability and safety in AI-driven control systems. Recent publications highlight work on Safe AI through Formal methods (SAIF project) , including probabilistic guarantees for neural networks and applications in mobile robotics. Her team’s best paper award at EMSOFT 2015 recognized scalable quadratic invariant computation for embedded systems. Scientific awards: Best paper award, ACM SIGBED International Conference on Embedded Software (EMSOFT 2015) She has supervised numerous PhD students in topics like mobile robotics , neural network verification , and numerical error analysis . Active in ANR projects (COVERIF, MALTHY, DEFIS) and currently leads the PEPR IA initiative on AI validation.

Alvaro Torralbaمشاهده پروفایل

دانشیار

• Symbolic Search
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Alvaro Torralba is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with the Technical Faculty of IT and Design. His research focuses on symbolic search, heuristic functions, and planning algorithms within artificial intelligence and machine learning. Notable projects include the ConAn initiative exploring contrastive analysis for state-space exploration. He has contributed extensively to classical planning, probabilistic planning, and automated planning competitions, earning awards such as the First Prize in the Agile Track of the 10th International Planning Competition (IPC’23). His work often bridges theoretical advancements with practical applications, including game-based network update synthesis and believable non-player character development. Research outputs include over 60 publications since 2011, with a focus on optimizing search algorithms and enhancing planning efficiency through techniques like operator-potential heuristics and bidirectional search strategies. His scientific contributions span algorithmic innovation, verification methodologies, and large-scale abstraction evaluation. Collaborations and datasets include foundational work on PDDL generators and pattern databases, with open-access resources available via Zenodo. As a program committee member and award-winning researcher, Torralba actively contributes to advancing the frontiers of AI planning and decision-making systems.

Thomas Grafمشاهده پروفایل

دانشیار

• Theoretical Linguistics
• Computational Linguistics
• Syntax
• +۵ مورد دیگر

Thomas Graf is an Associate Professor in the Department of Linguistics and an Affiliate Professor at the Institute for Advanced Computational Science (IACS) at Stony Brook University. He holds a Ph.D. from UCLA (2013) and an M.A. from the University of Vienna. His research focuses on the intersection of theoretical linguistics and computer science, exploring structural complexity in syntax, morphology, and phonology, and its implications for language processing and acquisition. Graf’s work emphasizes computational constraints on natural language, such as subregular complexity and parsing efficiency, and involves empirical studies across languages like English, Icelandic, and American Sign Language. Education: Ph.D., University of California, Los Angeles (2013) M.A., University of Vienna Research interests include computational syntax and phonology, parsing theory, and the formal characterization of linguistic universals. Key themes involve the computational power of linguistic frameworks (e.g., Minimalist grammars), the subregular hierarchy, and the typological implications of computational constraints. Graf’s recent work investigates how empirical phenomena like syntactic islands arise from complexity limits in natural language. His contributions to computational linguistics include Python tools for Minimalist grammar processing and collaborations in labs like the Computational Linguistics Lab (CompLab) at Stony Brook. He has also received a NSF CAREER grant for research on abstract universals in morphosyntax. Labs/Teams: Active member of the Computational Linguistics Lab (CompLab) at Stony Brook University. Leads the MathLing Reading Group and contributes to NLP research initiatives.

Eugene Starkمشاهده پروفایل

استاد

• Operating Systems
• Programming Language Semantics
• Concurrency Theory
• +۳ مورد دیگر

Eugene Stark is a Professor in the Department of Computer Science at Stony Brook University, affiliated with the College of Engineering and Applied Sciences. His work focuses on theoretical foundations and practical applications in systems and programming languages. Educational Background: He earned his Ph.D. in Computer Science from the Massachusetts Institute of Technology (MIT) in 1984. Research Interests: His primary areas include Operating Systems, Programming Language Semantics, Concurrency Theory, Distributed Algorithms Verification, and Functional Programming Languages. He explores formal methods to ensure correctness and efficiency in complex systems, leveraging category theory for rigorous semantic frameworks. His work often addresses challenges in indeterminate dataflow networks and probabilistic models. Publications Overview: Stark’s recent articles emphasize categorical structures (e.g., residuated transition systems, bicategories) and probabilistic I/O automata. They reflect a trajectory from foundational theory to tool development for concurrent system analysis. Academy of Teaching Scholars award Department Award for Undergraduate Teaching (2000) Advising & Grants: No formal advisees are listed in current records. His research projects include the Probabilistic I/O Automata framework, CARA Infusion Pump specifications, and SAMSON Network Memory Server initiatives. Grants and funding details are not explicitly mentioned. Labs/Teams: He is associated with the Laboratory for 體魯 Institute of (1988), though the lab name’s full English title remains unclear. Collaborations likely extend to interdisciplinary projects involving formal methods and systems engineering.

• Statistical Learning
• Game Theory
• Decision-Making Algorithms
• +۶ مورد دیگر

David Leslie is a Professor of Statistics and Director of Engagement in the Department of Mathematics and Statistics at Lancaster University. He specializes in statistical learning, decision-making algorithms, and game theory, with applications in real-time website optimization through bandit algorithms. Previously, he served as a Senior Lecturer at the University of Bristol and co-directed a cross-disciplinary decision-making research group. He has led significant projects such as the EPSRC/NERC-funded DSNE initiative and contributed to strategic partnerships like ALADDIN (with BAE Systems and EPSRC) and NG-CDI (with BT). His work emphasizes bridging theoretical research with practical industry solutions. Education details are not explicitly provided, but his career trajectory includes prior roles at prestigious institutions. Research interests focus on statistical methodologies, AI-driven decision systems, and environmental data science. He advises multiple PhD students in areas like Statistical AI and Extreme Value Theory. Notable projects include AI Hub, NABS+, and ProbAI, reflecting his engagement with cutting-edge technologies and interdisciplinary collaboration. David actively participates in research groups such as STOR-i Centre for Doctoral Training and the Statistical Artificial Intelligence group. His contact information includes an office at B73 in the PSC building and a direct email address. No specific scientific awards are listed, but his extensive project leadership and contributions to foundational AI research highlight his academic impact.

• Control Systems
• Energy Management
• Functional Electrical Stimulation
• +۱۲ مورد دیگر

William Holderbaum is a Professor at the Department of Electrical Engineering, School of Engineering, University of Reading. His research spans control systems, energy management, functional electrical stimulation, robotics, and wireless power transfer, with over 95 publications since 2002. Research Interests: His work integrates theoretical control theory with practical applications in renewable energy, biomedical engineering, and smart systems. He has made significant contributions to microgrid protection, energy storage control, optimal power management for electric cranes, and FES for paraplegia rehabilitation. His recent work explores soft robotics using electroactive polymers and intelligent sensing for environmental and health monitoring. Publication Trends: His recent articles (2021–2025) reflect a multidisciplinary focus, combining engineering, materials science, and healthcare. Key themes include sustainable energy systems, intelligent control, wearable sensors, and novel computing paradigms using smart materials. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: He has collaborated extensively with researchers such as F. Alasali, T. Yunusov, M. Alkowatly, and V. Becerra, suggesting a strong mentoring role. His work on energy storage, smart grids, and FES implies involvement in funded research projects, though specific grants are not listed. Labs and Teams: He is part of research teams focused on control systems and energy at the University of Reading, collaborating with the group led by B. Potter and V. Becerra. His work with biomedical applications suggests ties to interdisciplinary health-tech initiatives.

Jiong Tangمشاهده پروفایل

استاد

• System Dynamics
• Control
• Sensing and Automation
• +۷ مورد دیگر

Jiong Tang is a Pratt & Whitney Chair Professor in Design and Manufacturing at the University of Connecticut , where he also serves as Co-Director of the Management and Engineering for Manufacturing Program . He received his B.S. and M.S. in Applied Mechanics from Fudan University, China (1989 and 1992), and his Ph.D. in Mechanical Engineering from Pennsylvania State University (2001). Prior to joining UConn, he worked at the GE Research Center as a research engineer. Research Interests : System dynamics, control theory, smart materials, vibration suppression, uncertainty propagation, computational intelligence, and multi-physics system modeling. Current Projects : Digital twin development for aerospace materials, physics-informed machine learning in manufacturing, adaptive metasurface design, and optimization of cooperative robotics. Methodological Focus : Combines Bayesian deep learning , Gaussian process metamodeling , transformer-based architectures , and multi-fidelity data fusion for industrial applications. His work emphasizes smart sensing , electromechanical integration , and uncertainty-robust inverse analysis . Collaboration : Research funded by federal agencies and industrial partners , with particular emphasis on aerospace and manufacturing technologies. His recent publications highlight generative adversarial networks for defect detection , piezoelectric metamaterials , and physics-guided neural network architectures across mechanical, structural, and composite systems.