جستجوی استاد راهنمای دانشگاهی

Bettina Könighoferمشاهده پروفایل

استادیار

• Artificial Intelligence
• Reinforcement Learning
• Formal Methods
• +۳ مورد دیگر

Bettina Könighofer is an Assistant Professor at the Technische Universität Graz (TU Graz), affiliated with the Institute of Information Security. Her academic background includes a BSc, Dipl.-Ing. (Diplom-Ingenieur), and Dr.techn. (Technical Doctorate). She specializes in formal methods applied to AI safety, reinforcement learning, and autonomous systems. Her research emphasizes ensuring safety and ethical compliance in decision-making systems through techniques like shield synthesis and formal verification. Research Interests: Safe Reinforcement Learning Algorithmic Fairness and Ethical AI Formal Verification of Learning Systems Autonomous Systems Safety Legal Accountability in Automated Decision-Making Her recent work explores safety shields for real-time decision enforcement, tools for legal accountability (e.g., soid ), and adaptive architectures for safety-critical systems. Notable projects include contributions to QComp verification competitions and Dagstuhl seminars on trustworthy AI. She holds a leadership role in academic conferences, including co-chairing the AISoLA 2023 Track C2. Her research often intersects with practical applications in mobility systems and regulatory compliance.

Sabina Rossiمشاهده پروفایل

استاد

• Formal Methods
• Distributed Systems
• Markovian Models
• +۳ مورد دیگر

Sabina Rossi is a Full Professor in the Department of Environmental Sciences, Informatics and Statistics at Ca' Foscari University of Venice, where she also serves as Rector's Delegate for digital innovation in teaching. Her research develops formal methods for analyzing distributed systems with mobility and concurrency, specializing in process algebraic techniques for performance evaluation, verification, and dependability analysis of complex systems. Recent work extends to Markovian models for wireless networks, blockchain verification, and neural network compression. Her research investigates foundational models of distributed systems, with current emphasis on reversible computation, proportional lumpability in Markov chains, and blockchain security properties. She applies formal methods to analyze information flow security, model checking, and performance evaluation of stochastic systems. Recent publications (2020-2025) address queueing models with job stealing policies, blockchain verifier's dilemma, selfish mining attacks, and neural network compression via formal methods. Teaching responsibilities include 'Formal Methods for System Verification' in the Computer Science graduate program, 'Discrete Structures' for undergraduates, and foundational computer science courses for humanities students. She maintains office Z.B01 at the university's Scientific Campus via Torino in Venice.

• Optical Communications
• Photonics
• Passive Optical Networks (PON)
• +۴ مورد دیگر

Dr. Md Saifuddin Faruk is a Senior Lecturer at the School of Computing and Engineering, Bangor University. His research focuses on advanced optical communication systems, including passive optical networks (PON), fiber-wireless convergence, and machine learning applications in signal processing. He has contributed to high-speed PON solutions, data-driven models for optical amplifiers, and seamless fiber-wireless access networks. His work emphasizes practical implementations over field-deployed infrastructure, such as 200 Gb/s bidirectional coherent PON and tunable photonic mmWave generation. Dr. Faruk frequently collaborates on interdisciplinary projects, publishing in top journals like Optics Express and Journal of Lightwave Technology . He has presented invited talks at conferences like the Asia Communications and Photonics Conference (ACP), highlighting innovations in next-generation PON technologies. Education: Not explicitly stated in texts. Labs/Teams: Engaged in photonics and optical communication research groups at Bangor University. His research trends emphasize hybrid physical-data-driven models, coherent optical systems, and network convergence. Key contributions include improving SNR estimation using Gaussian processes and optimizing power budgets in high-speed PON. Grants and advising details are not specified in the provided texts.

• Sustainable Tourism
• Climate Change Mitigation and Adaptation
• Tourism and Environmental Policy
• +۷ مورد دیگر

Susanne Becken is a Vice Chancellor Research Fellow at the University of Surrey, affiliated with the Faculty of Arts, Business and Social Sciences and the Surrey Hospitality and Tourism Management department. She is also a Professor of Sustainable Tourism at Griffith University in Australia and serves as a Principal Science Investment Advisor for tourism in the Department of Conservation, New Zealand. Her work bridges academic research, policy advising, and practical sustainability initiatives across the Asia-Pacific region. Her research focuses on sustainable tourism, climate change mitigation and adaptation, environmental policy, systems thinking, and the use of AI and big data in monitoring tourism impacts. She leads projects on climate adaptation in Thailand, AI-based aesthetic monitoring of the Great Barrier Reef, and airline carbon reduction strategies. Recent publications reveal a strong trend in analyzing climate policy, public sentiment via social media, and decarbonization technologies such as blockchain. Her work integrates interdisciplinary methods, including systems modeling, sentiment analysis, and experimental design, to address sustainability challenges in tourism. Fellow of the International Academy of the Study of Tourism Member of Air New Zealand Sustainability Advisory Panel Invited expert on Whitsunday Climate Change Innovation Hub Board member of NOW Transforming Travel Advisory Board Susanne Becken advises PhD students such as Jinyan Chen and has led multiple research grants and collaborative projects. Her work emphasizes stakeholder engagement, policy integration, and transformative change in tourism systems. She is actively involved in developing monitoring frameworks and smart technologies for sustainable tourism management. She leads and collaborates with research teams on coral reef monitoring, climate risk perception, and digital tools for tourism sustainability, contributing to both academic knowledge and practical policy solutions.

• Software Engineering
• Formal Methods
• Software Testing
• +۵ مورد دیگر

Milos Gligoric is an Associate Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin. His research focuses on software engineering and formal methods, particularly in software testing (test generation and regression testing), proof engineering, systems-supported software engineering, and software engineering for scientific computing. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2015) and M.Sc./B.Sc. degrees from the University of Belgrade. Research Interests: Improving software quality and developer productivity through automated testing techniques, compiler optimizations, and formal verification methods. Recent work explores applications of large language models in test generation and code evolution. Publication Trends: Recent articles (2023-2025) show strong emphasis on LLM applications for test generation, JIT compiler testing, Python/C++ performance optimization, parallel computing, and innovative testing tools. Work frequently appears at top venues like ICSE, FSE, ISSTA, and OOPSLA. Scientific Awards: ACM SIGSOFT Outstanding Doctoral Dissertation Award David J. Kuck Outstanding PhD Thesis Award Multiple ACM SIGSOFT Distinguished Paper Awards Best Paper Award nominations (ICST 2012, ICS 2021) New Ideas and Emerging Results Distinguished Paper Award Research Support & Advising: Funded by Army Futures Command, Cisco, DOE, Google, Huawei, NSF, Runtime Verification, and Samsung. Mentors 7 PhD students and has graduated 12 PhD/MS students. Maintains industry collaborations with DBT (part-time contractor), Katana Graph, and Samsung. Labs & Tools: Leads UT Austin's software engineering research group. Developed multiple open-source tools including Ekstazi (regression test selection), mCoq (mutation analysis for Coq), Roosterize (lemma suggestion for Coq), and JAttack (JIT compiler testing).

Josef Urbanمشاهده پروفایل

پژوهشگر

• Automated Reasoning
• Machine Learning
• Formal Mathematics
• +۳ مورد دیگر

Josef Urban is a distinguished researcher at the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) , Czech Technical University in Prague. He leads the ERC Consolidator project AI4REASON and has held positions at Radboud University Nijmegen, Charles University, and the University of Miami. His work focuses on combining automated reasoning with machine learning in large formal knowledge bases, particularly in mathematics. Research & Projects Urban develops systems like MaLARea (Machine Learning Connection Prover) and ENIGMA (learning-based inference guiding). He contributed to the MizAR project for Mizar proof automation and created tools like BliStr (Blind Strategymaker) and xsl4mizar (XML API for Mizar). Scientific Contributions ERC Grant : AI4REASON (formal math and AI synergy) Marie-Curie Fellowship : 2011-2013 POPL Committee : 2016-2023 Students & Collaborations Current and former PhD students include Mark Adams , Yutaka Nagashima , and Krystof Hoder . He collaborates with institutions like Radboud University , Charles University , and contributes to projects such as MathWiki and ProofGold .

Yuting Wangمشاهده پروفایل

دانشیار

• Formal Verification
• Programming Languages
• Proof Theory
• +۵ مورد دیگر

Yuting Wang is a Tenure-Track Associate Professor at Shanghai Jiao Tong University , specifically affiliated with the John Hopcroft Center for Computer Science. Their research focuses on Formal Verification , Programming Languages , and Logical Frameworks , with significant contributions to verified compilation of system software. Core developer of the Abella theorem prover for higher-order reasoning Lead developer of Stack-Aware CompCert extensions Committee member for conferences like C++ (CPP), Programming Language Foundations in Software Engineering (PLDI), and Practical Aspects of Declarative Languages (PADL) Current research includes verifying compilers for concurrent systems, designing secure programming languages, and developing compositional verification frameworks. Collaborations with institutions like Yale University and the University of Minnesota under notable advisors Zhong Shao and Gopalan Nadathur have produced 15+ peer-reviewed publications. Their work on CompCertOC demonstrates verified compositional compilation for multi-threaded programs, while their contributions to the Abella system enhance schematic polymorphism and higher-order abstract syntax support. Yuting Wang actively advises a team of 5 current Ph.D. and M.S. students, with alumni placed at organizations like Tencent and AMD. They maintain a public ORCID profile and welcome prospective students interested in formal methods and systems verification.

David Pichardieمشاهده پروفایل

استاد

• Formal Methods
• Programming Languages
• Program Verification
• +۳ مورد دیگر

David Pichardie is a Professor of Computer Science at ENS Rennes (France) and a Researcher at Meta. He holds a part-time teaching position at ENS Rennes while working on sabbatical leave. His research spans formal methods, programming languages, program verification, software security, and static analysis. He specializes in machine-checked proofs using Coq and abstract interpretation, with significant work on the verified C compiler CompCert. He has served on program committees for SAS, OOPSLA, POPL, and other leading conferences. Research Interests: Formal Methods, Static Analysis, Compiler Verification, Security, Abstract Interpretation, Programming Languages Awards: ERC Consolidator Grant (2018-2021) His recent publications focus on verified JIT compilation, constant-time cryptography, SSA-based compiler optimizations, and concurrency verification. He has contributed to the formal verification of garbage collectors, WCET estimation tools, and information-flow architectures. His work often bridges theoretical formal verification with practical compiler design, emphasizing machine-checked proofs and integration into real-world systems like CompCert. He has mentored students and collaborated on formal verification of Java bytecode, defensive copying policies, and static analysis of self-modifying code. His teaching includes courses on static analysis, formal methods, and algorithms at institutions such as University Rennes 1, INSA engineering school, and ENS Cachan.

Gagandeep Singhمشاهده پروفایل

استادیار

• Machine Learning
• Formal Methods
• Systems
• +۲ مورد دیگر

Gagandeep Singh is a tenure-track Assistant Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign. His research focuses on the intersection of Machine Learning, Formal Methods, and Systems, aiming to create intelligent computing systems with formal guarantees about their behavior and safety. Key affiliations include: University of Illinois Urbana-Champaign (College of Engineering) VMware Research Research Interests: Formal certification of neural networks Abstract interpretation and static analysis Automatic differentiation techniques Machine learning safety and robustness Systems integration with formal guarantees Recent Publications Trends: His work emphasizes scalable verification techniques for machine learning models, particularly through abstract interpretation and convex hull approximations. Key themes include neural network certification, relational analysis of deep learning systems, and safety-critical AI verification. Many contributions focus on mathematical frameworks for automatic differentiation and optimization. Scientific Awards: Radhia Cousot Award (2022) Conference Leadership: Steering Committee Member (SAS 2025) Program Committee Member (SAS 2025) OOPSLA Review Committee (SPLASH 2025)

• Information Science and Technology
• Telecommunications Engineering
• Computer Engineering
• +۸ مورد دیگر

Daniel Filipe Sobral Fernandes is an Assistant Professor at Lusófona University - Lisbon University Center and a researcher at COPELABS (Association for Research and Development in Cognition and Human-Centered Computing). He holds a PhD in Information Science and Technology from ISCTE - University Institute of Lisbon, along with Master's and Bachelor's degrees in Telecommunications and Computer Engineering from the same institution. He also completed postgraduate studies in Management and Administration in Civil Protection at Lusófona University. Research Interests: His work centers on telecommunications and network optimization, particularly in 5G and beyond. Key areas include cloud-based network planning, self-organizing networks (SON), massive MIMO, SC-FDE modulation systems, and machine learning applications for mobile traffic forecasting and coverage estimation. His research integrates cloud computing with real-world network deployment challenges, focusing on automation and performance efficiency. Publication Trends: His recent publications (2017–2021) show a strong focus on cloud-based implementations for cellular network planning, optimization of 5G and legacy networks (GSM, UMTS), and hybrid methodologies combining empirical measurements with AI-driven models. There is a clear trend toward scalable, automated solutions for radio resource management and coverage prediction. Scientific Awards: Recipient of seven merit awards during his academic career Research and Advising: Daniel participated in the OptiNET-5G research project focused on 5G network planning and optimization. He has co-authored scientific papers with 31 collaborators. While no formal students are listed, his active research and publications suggest involvement in academic mentorship. He has not disclosed grant funding details. Labs and Teams: He is affiliated with COPELABS, a research unit dedicated to cognition and human-centered computing, where he contributes to projects involving intelligent systems and network automation.

• Cybersecurity
• Industrial Control Systems Security
• Critical Infrastructure Protection
• +۷ مورد دیگر

Dr. Naghmeh Moradpoor is an Associate Professor in Cybersecurity & Networks at Edinburgh Napier University's School of Computing Engineering and the Built Environment. She serves as program leader for MSc Advanced Security and Cybercrime and MSc Cyber Security (GA), and is a core member of the Centre for Distributed Computing, Networking and Cybersecurity. Her research spans Industrial Control System security, Critical Infrastructure Protection, IoT cybersecurity, and autonomous vehicle security. Key areas include: Anomaly detection in ICS/CNI Adversarial machine learning defense Federated learning for security Blockchain for cybersecurity Cyberbullying detection Recent publications demonstrate leadership in next-generation security challenges, particularly in connected autonomous vehicles and critical infrastructure protection. Her work combines cryptographic innovations with practical security implementations across multiple domains. Award highlights: Outstanding Woman in Cyber (Scottish Cyber Awards 2017) Top 2% most cited researcher worldwide (AD Scientific Index 2023) Multiple ENSA teaching/supervision nominations She actively supervises PhD students in cybersecurity domains and serves as Academic Editor for multiple journals including Security and Communication Networks and IET Information Security. Her leadership extends to organizing major conferences including SINCONF and CCNI.

• Multi-agent systems
• Real-Time Systems
• XAI (Explainable Artificial Intelligence)
• +۵ مورد دیگر

Prof. Davide Calvaresi is an Associate Professor at HES-SO Valais-Wallis, affiliated with the School of Engineering and IT and the Department of Computer Science and Communication Systems. His research focuses on Multi-Agent Systems (MAS), Real-Time Systems, Explainable AI (XAI), Blockchain, and their applications in healthcare, cybersecurity, and smart cities. Leading the EXPECTATION project (2021–present), he explores personalized XAI for heterogeneous knowledge integration in decentralized systems. He collaborates with institutions like the University of Bologna and the University of Luxembourg, addressing challenges in MAS timing reliability, ethical AI frameworks, and blockchain-based consent management in clinical trials. Key contributions include the EREBOTS chatbot platform for cancer survivors, real-time MAS simulators (MAXIM-GPRT), and frameworks for nutrition coaching systems with explainable recommendations. His work bridges technical innovation with ethical, legal, and human-centric considerations, emphasizing transparency and trust in AI systems.

Lasha Abzianidzeمشاهده پروفایل

استادیار

• Natural Language Processing (NLP)
• Computational Linguistics (CL)
• Formal Semantics
• +۵ مورد دیگر

Dr. Lasha Abzianidze is an Assistant Professor at Utrecht University's Department of Languages, Literature and Communication (Faculty of Humanities). He is affiliated with the Institute for Language Sciences, contributing to the Logic, Language, Information group and Computational Linguistics group. His research focuses on NLP, computational semantics, and formal reasoning systems like LangPro, a tableau-based theorem prover for NLI. He co-leads the Parallel Meaning Bank (PMB) project for semantically annotated corpora and the NALOMA workshop series. He holds a PhD from Tilburg University (2017), with earlier roles as a postdoc in the PMB and ROCKY projects, and lectureships at the University of Groningen. His expertise includes semantics, NLP, computational linguistics, and human-centered AI. Education: PhD in Linguistics (Tilburg University, 2017); Double MSc in Language & Communication Technologies (Charles University & University of Lorraine); BSc in Pure Mathematics (Tbilisi State University). Research Interests: Natural Language Inference (NLI), formal semantics, theorem proving, cross-lingual semantic annotation, and explainable AI. Current projects include explainable natural language reasoning via the NWO XS grant and developing spatial reasoning datasets like SpaceNLI. His work bridges logic-based methods with deep learning, emphasizing transparent and interpretable systems. Grants & Supervision: Holder of an NWO XS grant (2023) for explainable NLI research. Supervises AI master's theses, favoring students from his courses on formal languages and NLP. Involved in teaching courses like 'Reasoning with Natural Language' and 'Machine Learning for Vision and Language'. Labs/Teams: Leads the NALOMA workshop series and contributes to the PMB project. Active in the Computational Linguistics group at ILS, collaborating on semantic parsing tools like CCGweb and LangPro. His work integrates logic-based reasoning with modern NLP techniques to advance explainable AI systems.

• Software Defined Networking
• Programmable Data Planes
• Machine Learning
• +۳ مورد دیگر

Cristian Bermudez Serna is a researcher at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich (TUM). He holds an M.Sc. in Electrical Engineering from TUM and a Bachelor's in Telecommunications Engineering from Universidad de Antioquia, Colombia. His research focuses on mechanisms for efficient network reconfigurations in mobility scenarios, with emphasis on Software Defined Networking (SDN), programmable data planes, and machine learning applications in networking. Education: Bachelor's in Telecommunications Engineering, Universidad de Antioquia (2016) M.Sc. in Electrical Engineering, Technical University of Munich (2021) Research Interests: Optical access networks planning and robustness Future railway communication systems Survivable multi-domain network routing Post-quantum cryptography in optical networks Publications span topics like infrastructure cost savings in rural PONs, survivable routing mechanisms, and SDN control plane optimization. His work integrates algorithmic approaches with real-world network challenges in telecommunications and transportation systems.

Maximilian Engelمشاهده پروفایل

استادیار

• Random Dynamical Systems
• Multiscale Dynamics
• Stochastic Analysis
• +۵ مورد دیگر

Maximilian Engel is an Assistant Professor (UD1, tenured) at the KdV Institute, University of Amsterdam, and Head of the Junior Research Group at the Department of Mathematics and Computer Science, Freie Universität Berlin. His research focuses on random and multiscale dynamical systems, with applications in mathematical physics, neuroscience, and climate dynamics. He leads the MATH+ Research Group on 'Random and Multiscale Dynamical Systems' and collaborates on projects like the Vidi Project on Transient Random Dynamics and Metastability in Multi-Agent Systems. Engel's academic career includes roles as a member of the Early Career Editorial Board for Physica D: Nonlinear Phenomena and organizer of the One World Dynamics Seminar Series . His work bridges theoretical analysis (e.g., bifurcation theory, stochastic processes) with practical applications in machine learning and fluid dynamics. Upcoming activities include a mini-course at the 2025 Summer School on Random Dynamical Systems and the 2026 International Conference on Random Dynamical Systems and Related Fields in Brazil. Research highlights include studies on fast-slow PDEs, noise-induced instabilities, and synchronization in biochemical oscillators. His interdisciplinary approach integrates geometric analysis, numerical methods, and data-driven techniques to understand complex systems' behavior.