جست‌وجوی استاد و پژوهشگر

• Theoretical Computer Science
• Theorem Proving
• Automated Reasoning
• +۲۶ مورد دیگر

Jasmin Blanchette is a Professor of Theoretical Computer Science and Theorem Proving at Ludwig-Maximilians-Universität München (LMU), where he also serves as the Dean of Studies for Computer Science since January 22, 2024. He is affiliated with the Institute for Informatics and leads the Theoretische Informatik und Theorembeweisen research unit. Additionally, he is a guest researcher in the VeriDis group at Loria, Nancy. Research Interests: His research centers on strengthening proof automation for general-purpose logics and enhancing the usability of proof assistants. He combines automatic and interactive methods, bridging human and artificial intelligence in formal verification. His work spans higher-order logic, automated and interactive theorem proving, formalization of mathematical results, and foundational mechanisms for (co)datatypes and (co)recursive functions. Key projects include Sledgehammer, Nitpick, Matryoshka, Nekoka, IsaFoL, and Lean Forward. Publication Trends: His recent publications (2023–2025) show a strong focus on higher-order automated reasoning, superposition calculus, proof automation in Isabelle/HOL, and formalization of logical and mathematical concepts. There is a consistent emphasis on verification, efficiency, and integration of SAT/SMT techniques into higher-order provers. Scientific Awards: FroCoS 2023 Best Paper Award (with Visa Nummelin and Sander Dahmen) CADE 2023 Best Paper Award for 'Verified given clause procedures' (with Qi Qiu and Sophie Tourret) IPA Dissertation Award (awarded to student Petar Vukmirović) Dutch Prize for ICT Research 2022 Advising and Grants: He supervises a large team of postdocs and PhD students at LMU and co-supervises students at other institutions. His leadership in major collaborative projects like Matryoshka indicates significant grant funding and collaborative research efforts. He is editor-in-chief of the Journal of Automated Reasoning and serves on numerous steering and program committees, reflecting strong academic leadership and visibility. Labs and Teams: He leads a research group at LMU’s Institute for Informatics, focusing on theorem proving and formal methods. He is also associated with the VeriDis group at Loria, Nancy, and collaborates widely across Europe in the automated reasoning community.

• Formal Methods
• Software Engineering
• Verification and Validation
• +۳ مورد دیگر

Idir Ait-Sadoune serves as a Lecturer in Data Engineering at ISAE-ENSMA, France, where he is an active member of the Data Engineering Team within the LIAS laboratory. His academic position includes temporary teaching and research responsibilities (ATER) focused on formal methods and software engineering applications. He earned his PhD in 2010 from ENSMA with a dissertation titled Modélisation et Vérification Formelles de Compositions de Services. Une Approche Fondée sur le Raffinement et la Preuve , establishing his expertise in formal verification techniques. His educational background centers on computer science with specialization in formal modeling and system validation. Ait-Sadoune's research spans critical domains in computer science, with particular emphasis on: Formal Methods : Pioneering applications of Event-B for system specification and verification Software Engineering : Advancing web services composition and data repository design Human-Computer Interaction : Developing formal models for multimodal interactive systems Verification & Validation : Creating proof-based approaches for system correctness His publication trajectory from 2006-2018 reveals consistent innovation in formal techniques, particularly through Event-B methodology applied to web services and multimodal interfaces. The research demonstrates strong interdisciplinary connections between theoretical formal methods and practical software engineering challenges, with increasing focus on data engineering applications in later works. Within the LIAS laboratory ecosystem, Ait-Sadoune collaborates with Automatic Control and Real Time teams, contributing formal verification expertise to cross-disciplinary projects while maintaining his core focus on data-intensive system engineering.

• Control Theory
• Event-Triggered Control
• Multi-Agent Systems
• +۳ مورد دیگر

Victor S. Dolk serves as an Assistant Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), actively contributing to the Heemels research group. His academic foundation includes a Master's thesis titled Mixing and switching completed in 2013 under M. Lauret's supervision at TU/e. Dolk's research centers on advanced control systems theory, with core expertise in event-triggered and time-triggered communication frameworks for multi-agent systems. His investigations address critical challenges in networked control environments including communication resource optimization, stability analysis under time-varying delays, resilience against denial-of-service attacks, and data-driven predictive control methodologies. Specific domains encompass linear parameter-varying (LPV) systems, complexity reduction in coupled mechanical problems, and certificates for stability analysis. Recent publications (2024-2025) demonstrate concentrated advancements in multi-agent communication resilience, digital implementation frameworks, and theoretical foundations for stability certificates in LPV systems. These works published in IEEE Transactions on Automatic Control and Automatica reveal strong emphasis on practical implementations of event-triggered mechanisms while maintaining analytical rigor. With 37 total research outputs and 1619 Scopus citations, Dolk has supervised 5 research projects or student theses. His ongoing work shows strategic focus on bridging theoretical control frameworks with real-world implementation constraints in resource-limited environments. As a core member of the Heemels research group at TU/e, Dolk collaborates extensively on networked control systems with international partners, contributing to the group's reputation in event-triggered control theory and applications.

George Nikolakopoulosمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Field Robotics
• +۹ مورد دیگر

George Nikolakopoulos is a Professor in Robotics and Automation at the Department of Computer Science, Electrical and Space Engineering at Luleå University of Technology , Sweden. He also holds a Chair in Robotics and Artificial Intelligence and has been affiliated with the NASA Jet Propulsion Laboratory for collaborative research on Aerial Planetary Exploration. Academic Rank: Professor Department: Computer Science, Electrical and Space Engineering Collaborations: NASA JPL, COSTAR Team Research Interests Robotics Artificial Intelligence Field Robotics UAVs (Unmanned Aerial Vehicles) Automatic Control Applications Learning and Reasoning Networked Embedded Systems Cyber-Physical Systems Mechatronics Adaptive Control System Identification Publications and Research Trends His recent publications focus on autonomous aerial robotics, deep mineral exploration, and AI-driven control systems. Key trends include the integration of reinforcement learning for UAV stabilization, path planning in subterranean environments, and cloud/edge-assisted control architectures for collaborative robotic systems. Scientific Awards and Recognitions Team's work included 4 times in a row at the IVA Top 100 list (Royal Academy of Engineers in Sweden) Won the second stage of the DARPA Grand Challenge on Sub-T exploration with the COSTAR team in February 2020 Leadership and Innovation He established the Digital Innovation Hub on Applied AI at Luleå University of Technology and founded two spin-offs, including FieldRobotix , which joined the IVA REACHME Silicon Valley accelerator. His lab, the Robotics Team , actively participates in cutting-edge projects like autonomous mining inspection and aerial additive manufacturing.

Björn Annighöferمشاهده پروفایل

استاد

• Avionics Systems
• Self-Adaptive Systems
• Cybersecurity
• +۵ مورد دیگر

Björn Annighöfer is a Professor at the Institute of Aviation Systems (ILS) at the University of Stuttgart, where he serves as Managing Director. His work focuses on complex, digital, and safety-critical avionics systems, including self-adaptive platforms, cybersecurity, and AI-supported aerospace systems. Research interests include: Self-adaptive avionics platforms Model-based cybersecurity frameworks Integrated Modular Avionics (IMA) development Virtualization and middleware for safety-critical systems AI applications in aerospace Automated development and certification processes Recent publications highlight advancements in PLUG-AND-FLY avionics, security assessment using large language models, and domain-specific modeling tools. He leads a team of ~25 scientists at ILS, which operates modern labs, flight simulators, and research aircraft for testing.

Aurelio Piazziمشاهده پروفایل

استاد

• Control Theory
• Autonomous Robotics
• Mechatronics Systems
• +۷ مورد دیگر

Aurelio Piazzi is a Full Professor of Systems and Control Engineering at the Department of Engineering and Architecture , University of Parma , Italy, where he has been a faculty member since 1992. He holds a Laurea magna cum laude in nuclear engineering and a PhD in Systems Engineering, both from the University of Bologna. He founded the Active Control Laboratory (ACtLab) in 1995 and currently serves as the director of the Polytechnic Library and president of the Laurea Magistrale in Informatics Engineering. Academic Rank: Professor Department: Department of Engineering and Architecture University: University of Parma Email: aurelio.piazzi@unipr.it Office Location: Campus Scienze e Tecnologie - Padiglione 10, Parco Area delle Scienze, 181/A, 43124 Parma, Italy Personal Website: http://www.ce.unipr.it/people/piazzi His research is centered on control theory , with a focus on inversion-based and optimal feedforward control methods , feedforward-feedback control strategies , and autonomous navigation of wheeled robots and vehicles. He also investigates vision-based control systems and mechatronics . His work bridges theoretical advancements with industrial applications, including food ovens and railway pantograph inspection. The recent publications highlight a strong trend in inversion-based control architectures , feedforward regulation , and trajectory planning for autonomous systems. His work frequently employs polynomial interpolation , spline methods (e.g., eta3, eta4) , and dynamic inversion to achieve smooth, optimal, and robust motion control. The research spans from theoretical equivalence proofs to practical implementations in robotics and industrial automation. He has led significant research projects such as: COOKIES: EU-funded project on vision-based control of food industrial ovens. PAVISYS: Vision-based inspection system for railway pantographs, developed in collaboration with RFI Ferrovie dello Stato. PRIN Projects: National research units on automation and control theory funded by MIUR. He has published over 100 scientific papers in top journals like IEEE Transactions on Automatic Control , Automatica , and IEEE Transactions on Robotics . He is a Senior Member of IEEE and a member of SIAM , reflecting his standing in the international control and applied mathematics communities. He teaches core courses including Fundamentals of Automatic Control and Nonlinear Systems at both undergraduate and graduate levels. He has supervised numerous research students and mentored early-career researchers. His laboratory, ACtLab (Active Control Laboratory) , serves as the primary hub for both teaching and research in automation and control systems at the University of Parma, fostering innovation and practical experimentation.

Irène Marcoviciمشاهده پروفایل

استاد

• Probability Theory
• Cellular Automata
• Dynamic Systems
• +۳ مورد دیگر

Irène Marcovici is a Professor at the University of Rouen Normandy, affiliated with the Raphaël Salem Mathematics Laboratory (LMRS) and leading the Probability and Dynamic Systems Team. Her research spans probability theory, cellular automata, stochastic processes, and combinatorics, with a focus on ergodicity, percolation, and self-organization phenomena. She collaborates with institutions like the GDR Fundamental Computer Science and its Mathematics and has contributed to journals such as Probability Theory and Related Fields, Annales Henri Lebesgue, and Theoretical Computer Science. Education: Habilitation à Diriger des Recherches (2021, University of Lorraine), PhD in Mathematics (2013, University of Paris Diderot) Research Focus: Marcovici's work explores probabilistic cellular automata, percolation models, and their applications in physics, computer science, and mathematics. Key projects include analyzing stability regions in queueing systems, developing decentralized diagnostics, and studying self-descriptive sequences. Her articles highlight interdisciplinary connections between discrete mathematics and stochastic dynamics. Notable Collaborations: She has co-authored publications with researchers like Jérôme Casse, Régine Marchand, Nazim Fatès, and Mathieu Sablik. Her team participates in the ALEA and SDA2 working groups under GDR Fundamental Computer Science and its Mathematics.

• Experimental Mathematics
• Artificial Intelligence
• Legal aspects of technology
• +۴ مورد دیگر

Michael Ian Shamos is a Distinguished Career Professor at Carnegie Mellon University's School of Computer Science, with appointments in the Language Technologies Institute and Software and Societal Systems Department. His career spans academia, law, and technology entrepreneurship, with expertise in experimental mathematics, artificial intelligence, and legal aspects of technology. Dr. Shamos earned his educational credentials through an impressive multidisciplinary path: A.B. in Physics from Princeton University (1968) under John Wheeler M.A. in Physics from Vassar College (1970) M.S. in Technology of Management from American University (1972) M.S. and M.Phil. in Computer Science from Yale University (1973-1974) Ph.D. in Computer Science from Yale University (1978) J.D. from Duquesne University (1981) His research interests bridge multiple domains with exceptional depth. In experimental mathematics, he develops computational systems that automatically generate and prove novel mathematical theorems, particularly in number theory, having contributed hundreds of new results to the field. As a leading expert in electronic voting security, he has examined over 120 voting systems for seven states and testified before Congress multiple times. His work uniquely integrates legal expertise with technical knowledge, especially regarding intellectual property in the digital age. He directs the M.S. in Artificial Intelligence and Innovation program at CMU, advising 74 students in this cutting-edge field. His publication trajectory reveals an evolution from foundational computational geometry (co-authoring the seminal "Computational Geometry: An Introduction") to contemporary issues in voting security and experimental mathematics. The consistent thread is applying computational methods to solve real-world problems with careful attention to legal and societal implications. His notable recognitions include: Industry Service Award of the Billiard and Bowling Institute of America (1996) Black and White Scotch Achiever's Award for contributions to bagpipe musicography (1991) As an educator and mentor, Dr. Shamos directs the M.S. in Artificial Intelligence and Innovation program and teaches courses including "AI & Future Markets" and "The Law of Computer Technology." He has served as an expert witness in over 360 legal cases involving computer technology and has been a statutory examiner of computerized voting systems for Pennsylvania since 1980. His extensive industry experience includes founding technology companies and serving as General Counsel for an AI company. Dr. Shamos is actively involved with the Universal Library project, which has scanned over 1.5 million books. He also serves as faculty advisor to the Carnegie Mellon Pool Team and is Curator of The Billiard Archive, reflecting his deep commitment to preserving billiards history alongside his academic pursuits.

Charalampos Psillakisمشاهده پروفایل

استادیار

• Adaptive Control
• Nonlinear Control
• Intelligent Control
• +۷ مورد دیگر

Charalampos (Haris) Psillakis is an Assistant Professor at the Division of Signals, Control, and Robotics within the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). He holds a Ph.D. and Diploma in Electrical & Computer Engineering from the University of Patras. Previously, he served as an Adjunct Lecturer at multiple institutions and worked at Hellenic Electricity Distribution Network Operator (HEDNO) S.A. His research focuses on adaptive control, nonlinear control, robotics, multi-agent systems, power systems, and distributed control. Education: Ph.D., Electrical & Computer Engineering, University of Patras, 2006 Diploma in Electrical Engineering, University of Patras, 2000 Research Interests: Adaptive Control Nonlinear Control Intelligent Control Robotics and Automation Power Systems Control Multi-Agent Systems Stochastic Systems Uncalibrated Visual Servoing Publications: His work emphasizes distributed control algorithms for multi-agent systems, nonlinear control methodologies, and applications in robotics and power systems. Recent trends include consensus protocols under communication delays, adaptive neural network control, and robustness in dynamic network topologies. Teaching: He teaches courses on automatic control, nonlinear control systems, and advanced control methods at both undergraduate and graduate levels. Labs/Teams: His research is associated with the Signals, Control, and Robotics division at NTUA, focusing on robotics, power systems, and distributed control systems.

Steven Xiaotian Daiمشاهده پروفایل

مدرس

• Real-Time Systems
• Cyber-Physical Systems (CPS)
• Robotics
• +۶ مورد دیگر

Dr. Steven Xiaotian Dai is a Lecturer in Cyber-Physical Systems at the Department of Computer Science, University of York, UK. He leads the ReFLEX Lab and is affiliated with the Real-Time and Distributed Systems Group. His research focuses on real-time scheduling, digital twins, and safety assurance in autonomous systems, with applications in aerospace, robotics, and avionics. He holds a PhD from the University of York (2019, Best Thesis Award) and has contributed to prestigious projects like SCHEME (Innovate UK) and MOCHA (Huawei). Dr. Dai’s academic qualifications include a PhD in Real-Time Systems (York), MSc in Control Systems (Sheffield), and BSc in Automatic Control (Nanjing). His research grants include £2.2M from Innovate UK for SCHEME and £985K from Huawei for MOCHA. He actively serves on program committees for leading conferences like RTSS and RTAS. His research interests encompass real-time scheduling on multi-cores, timing assurance for CPS, and hardware-software co-design. Collaborations span industries and academia globally, addressing challenges in safety-critical systems. Dr. Dai supervises multiple PhD and MSc students, emphasizing adaptive scheduling, digital twins, and robotics. He is a member of IEEE CS, IEEE RAS, and ACM SIGBED, and his work has been published in over 30 peer-reviewed articles. The ReFLEX Lab explores cutting-edge topics like routerless network-on-chip optimization and ROS 2 executor timing analysis.

• Formal Verification
• Programming Language Theory
• Category Theory
• +۴ مورد دیگر

Pedro Azevedo de Amorim is a Researcher (Research Associate) in the Department of Computer Science at the University of Oxford. He holds a PhD from Cornell University (Computer Science Department), where he worked under Dexter Kozen. His research focuses on formal verification, programming language theory, and their intersections with category theory, type theory, proof assistants, and logic. He explores applications to probabilistic programming semantics and substructural logics. Key research areas include semantics of probabilistic programming languages, categorical probability, and denotational semantics. His work spans foundational aspects of programming languages, including logical relations, effect systems, and modular hardware design. Notable collaborations include projects like BLAST (Employing Categorical Probability Towards Safe AI). Pedro has published influential papers at top venues such as LICS, PLDI, and OOPSLA. His recent work addresses expected cost analysis, timeline types for hardware design, and dependent type systems for parser verification. He has taught as a Teaching Assistant in courses ranging from compilers to category theory at Cornell University. Current affiliations include the Wolfson Building (Room 309) at Oxford, with active involvement in projects linking category theory to practical programming language challenges. His research emphasizes bridging theoretical foundations with applied systems for safer AI and verified software.

Jasmin Blanchetteمشاهده پروفایل

استاد

• Theorem Proving
• Formal Verification
• Automated Reasoning
• +۴ مورد دیگر

Prof. Dr. Jasmin Blanchette is a faculty member at the Ludwig Maximilian University of Munich, holding the chair in Theoretical Computer Science and Theorem Proving . She serves as Dean of Studies for Computer Science and collaborates with the VeriDis group at Loria, Nancy. Her research focuses on combining automatic and interactive theorem proving to enhance proof automation for critical systems and mathematical research. Key Research Areas: Higher-order logic, formal verification, superposition calculus, proof assistants (Isabelle/HOL, Lean), definitional mechanisms for (co)datatypes. Recent Articles address advanced topics in higher-order reasoning, SMT integration, and algorithm verification. Scientific Recognition: Co-awarded best papers at FroCoS 2023 and CADE 2023. Supervises a team of postdocs and PhD students working on projects like Matryoshka and Nekoka. Her tools (Sledgehammer, Nitpick) are widely used in formal methods.

• Private Law
• Contract Law
• Succession Law
• +۴ مورد دیگر

Ivan Libero Nocera is an Associate Professor of Private Law at the Department of Law, University of Bergamo. He holds a law degree from Weigmann Law Firm in Turin and Milan, and earned his Doctorate in Private Law with honors from Scuola Sant'Anna in Pisa. Previously, he held academic roles at the University of Brescia, University of Valle d'Aosta, and University of Palermo, teaching subjects like Privacy Protection, Communications Law, and Corporate Law. Research Focus: Contracts, succession, business crises, and digital law Publications: Authored three monographs and numerous articles in journals such as Civil Liability and Social Security and Bankruptcy and Other Insolvency Procedures International Collaborations: Visiting researcher at École Normale Supérieure, University of Cambridge, University of Oviedo, and University of Groningen His recent publications analyze intersections of artificial intelligence, medical ethics, and digital markets. He has lectured at universities in South America, including Pontificia Universidad Católica del Perú and Universidad San Marcos. Active in national and international conferences, his work addresses evolving legal frameworks for family dynamics, debt restructuring, and data protection.

Jacob Laurelمشاهده پروفایل

استادیار

• Static Analysis
• Programming Languages
• Probabilistic Programming
• +۳ مورد دیگر

Jacob Laurel is an Assistant Professor in the School of Computer Science at Georgia Institute of Technology. His research focuses on static analysis of programming languages, particularly in probabilistic and differentiable programming. He actively recruits PhD students starting Fall 2025 for work in these areas. Research interests include static analysis techniques for probabilistic/differentiable languages, compiler optimizations, and formal methods for ensuring correctness in AI systems. His work spans topics like abstract interpretation, automatic differentiation, and uncertainty quantification in distributed systems. Notable contributions include the Diamont framework for uncertainty monitoring in distributed programs, the Statheros compiler for low-precision probabilistic inference, and foundational work on higher-order automatic differentiation analysis. He has served on program committees for OOPSLA, SAS, ECCV, and WFVML. Teaching includes a special topics course on probabilistic/differentiable programming in Spring 2025.

• Machine Learning
• Tensor Algorithms
• Symbolic Regression
• +۲ مورد دیگر

Joachim Giesen is Professor of Theoretical Computer Science at the University of Jena, where he leads research on algorithms for machine learning and artificial intelligence. Education: PhD and Habilitation from ETH Zurich His research develops efficient algorithms for tensor computations, symbolic regression, and optimization methods. Current work focuses on tensor network optimizations and techniques for scalable symbolic regression. He has supervised 7 PhD students to completion and leads multiple industry collaborations applying tensor computation methods to real-world problems.