جست‌وجوی استاد و پژوهشگر

• Formal Verification
• Model Checking
• Sensor Systems
• +۳ مورد دیگر

Ivaylo Valkov is a Lecturer in the School of Computing Science at the University of Glasgow, having joined the academic staff in June 2024. He completed his PhD in Computing Science at the University of Glasgow in 2024 under Prof. Alice Miller, focusing on formal analysis of wireless sensor systems. Prior to this, he earned a Master's degree in Computing Science and Mathematics from the same university in 2018. His research emphasizes rigorous mathematical analysis of software and hardware systems, particularly through model checking techniques. Key areas include system verification, sensor networks, combinatorial problems, and probabilistic model checking. Valkov has contributed to advancements in overtaking planning algorithms, symmetry reduction methods, and optimization of scheduling problems like the social golfer problem. His publications (6 items) span peer-reviewed journals like Science of Computer Programming and Symmetry , as well as conferences such as SPIN 2024 and FMAS 2021. While no specific awards are listed, his work reflects sustained engagement with formal methods and their applications in real-world systems. Valkov teaches Algorithms and Data Structures at the Master's level and co-teaches Software Engineering and Research Methods courses. His teaching aligns with his research focus on logical problem-solving and systematic analysis.

Ulrik Nymanمشاهده پروفایل

دانشیار

• Computer Science
• Formal Verification
• Real-Time Systems
• +۵ مورد دیگر

Ulrik Nyman is an Associate Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. His research focuses on formal verification, real-time systems, embedded software, and cyber-physical systems. He is affiliated with the CISS - Center for Embedded Software Systems and has contributed to projects like Digital Technologies for Industry 4.0 and compositional verification of real-time systems. Research Interests: Formal Methods and Verification Real-Time and Embedded Systems Cyber-Physical Systems Power Electronics Control Modal Transition Systems Interface Theories Projects: Digital Technologies for Industry 4.0 (2019–2021): Focused on industrial automation and predictive models. Compositional Verification of Real-Time Multi-Core Safety-Critical Systems (2017–2021): Addressed safety-critical avionics and multicore schedulability. CRAFTERS: Framework for Tailoring Embedded Real-Time Systems (2012–2015): Developed application-driven middleware. Publications: Nyman’s recent work explores statistical model checking in power electronics, falsification testing for cyber-physical systems, and formal verification of OS-based software. His research bridges theoretical formal methods with practical applications in embedded systems. Labs/Teams: Active in the CISS Center, collaborating on embedded software systems and real-time frameworks.

• Neurosymbolic AI
• Explainable AI
• Machine Learning
• +۴ مورد دیگر

Professor d'Avila Garcez at City University London's Department of Computing is a leading researcher in Neurosymbolic AI , combining symbolic reasoning with neural learning. His work addresses explainability, knowledge extraction, and hybrid architectures. Key Contributions : 3rd-wave Neurosymbolic AI, semantic frameworks for knowledge encoding, and interactive medical imaging systems. Affiliations : Department of Computing, City University London; collaborations with institutions in healthcare, finance, and neuroscience. Research Interests : Formalizing neurosymbolic computation Explainable AI for clinical decision-making Knowledge distillation from CNNs Time-series interpretability Relational learning with hypergraphs Consistency/coherence in representation learning Article Trends : Focus on AI transparency , medical applications (stroke recovery, radiology), and symbolic-numeric integration . Techniques include logic tensor networks, counterfactual explanations, and modular architectures. Grants & Collaborations : Extensive international collaborations in healthcare, finance, and AI ethics. Key projects involve stroke recovery prediction, medical imaging, and neurosymbolic frameworks.

Jiri Wiedermannمشاهده پروفایل

استاد

• Theoretical computer science
• Computational complexity
• Models of sequential and parallel computational systems
• +۷ مورد دیگر

Jiri Wiedermann is a Professor of Computer Science at Charles University and has served as Director of the Institute of Computer Science at the Academy of Sciences of the Czech Republic since 2000. His academic journey includes an Assoc. Prof. position at Charles University (2000) and degrees from Comenius University (RNDr., M.Sc.) and Czechoslovak Academy of Sciences (CSc., DrSc.). Education : DrSc. in Computer Science (Comenius University, Bratislava, 1993) CSc. (equiv. to PhD) in Computer Science (Czechoslovak Academy of Sciences, Prague, 1980) RNDr. and M.Sc. in Computer Science (Comenius University, Bratislava, 1974) His research spans Theoretical Computer Science , focusing on computational complexity, neurocomputing, and non-standard computing. He explores embodied cognition, mirror neurons, and autopoietic automata, bridging neural models with algorithmic frameworks. The 15 most recent publications highlight his work on interactive computation, fuzzy Turing machines, evolving artificial living systems, and cognitive architectures. Key trends include machine learning inspired by biological systems , computational limits of cognition , and formal models of neural processes . Scientific Awards : Member of Academia Europaea (since 2006) Member of the Czech Learned Society (since 2003) Board of Directors, ERCIM (since 1997) Leadership roles in EATCS (Vicepresident 1997-2002)

• Formal Verification
• Theorem Proving
• Approximate Computing
• +۵ مورد دیگر

Sofiène Tahar is a Professor at Concordia University's Department of Electrical and Computer Engineering, affiliated with the Faculty of Engineering and Computer Science. His research focuses on formal verification, theorem proving, and their applications in cyber-physical systems, circuit design, and reliability engineering. He has authored over 300 publications in top-tier conferences and journals, including DATE, ICFEM, and FMCAD. Key research areas include formal methods for analog/digital circuits, approximate computing, stochastic systems, and safety-critical systems. His work bridges theoretical foundations (e.g., theorem proving in HOL) with practical engineering problems like circuit reliability and autonomous systems verification. Recent projects involve formal analysis of vehicular systems, energy-efficient approximators, and machine learning integration with formal verification frameworks. Tahar collaborates extensively with industry partners and holds leadership roles in international conferences, including co-chairing ICFEM 2023.

• Intelligent Transport Systems (ITS)
• Road Safety
• Human Factors Engineering
• +۴ مورد دیگر

Professor Andry Rakotonirainy is a renowned expert in road safety and Intelligent Transport Systems (ITS) at QUT's Faculty of Health, School of Psychology & Counselling. He holds a PhD in Computer Science from Sorbonne University and INRIA, France. His research focuses on human factors in ITS, leveraging computer science, engineering, and psychology to improve road safety. He leads the ITS human factors program at CARRS-Q and the Centre for Future Mobility, with over $76M in research grants. Key roles include ARC College of Experts membership and EU project advisory roles. Research Interests: Connected and Automated Vehicles (CAVs) Eco-safe driving systems Human-Machine Interaction Driver Behavior Analysis Transportation Policy Projects: EU-funded LEVITATE (€6.4M) studying societal impacts of CAVs Queensland CAVI-iMOVE CRC initiative ARC grants on AI explainability and AV safety Achievements: Over 300 publications, h-index 45, and 14 ARC grants. Established ICCAM with Université Gustave Eiffel. Advising & Grants: Supervised 6 doctoral and 2 master's students. Active in government/industry committees and grant reviews. Labs/Teams: CARRS-Q, Centre for Future Mobility, and ICCAM collaboration.

• Geophysics
• Seismic Monitoring
• Carbon Capture and Storage
• +۵ مورد دیگر

Roman Isaenkov serves as a Research Fellow at Curtin University's School of Earth and Planetary Sciences within the Faculty of Science and Engineering. His work focuses on advanced geophysical monitoring techniques for carbon capture and storage projects. His research interests center on seismic monitoring , distributed acoustic sensing (DAS) , and CO2 geosequestration verification . Key areas include fiber-optic sensing applications, 4D seismic imaging for reservoir characterization, and multiwell monitoring systems for carbon storage projects. His technical expertise spans data processing workflows for DAS VSP (Vertical Seismic Profiling), source positioning accuracy, and time-lapse monitoring of CO2 plumes. Isaenkov's publication record demonstrates consistent contributions to carbon storage monitoring through the CO2CRC Otway Project. His work shows a clear progression from methodological development (source positioning effects, wavefield decomposition) to field implementation (Gorgon CCS case study, Pilbara mineral exploration). Key collaborations include researchers from CO2CRC, with frequent co-authorship with R. Pevzner, K. Tertyshnikov, and A. Yurikov. His technical focus includes: Permanent reservoir monitoring systems using fiber-optic technology Automated processing of continuous DAS data streams CO2 plume evolution tracking through multiwell seismic arrays Repurposing abandoned wells for geophysical surveillance Isaenkov has contributed significantly to the Stage 3 Otway Project, developing monitoring systems for small-scale CO2 injections and investigating nonlinear seismic effects in subsurface environments. His work bridges theoretical geophysics with practical field applications in carbon management.

• Autonomous Systems
• Robotics
• Computer Vision
• +۳ مورد دیگر

Daniel Duberg is a Researcher and PhD candidate at the Division of Robotics, Perception and Learning (RPL) within the School of Electrical Engineering and Computer Science at Kungliga Tekniska Högskolan (KTH). His research focuses on autonomous exploration and real-time 3D mapping using unmanned aerial vehicles (UAVs), emphasizing onboard processing for indoor environments. He has contributed to frameworks like UFOMap, which address dynamic environments and efficient data structures. His work integrates probabilistic modeling, sensor fusion, and real-time algorithms to enhance UAV navigation and decision-making. Notable projects include dynamic-aware mapping (DUFOMap) and exploration strategies guided by formal methods like Signal Temporal Logic. Duberg teaches engineering courses in robotics and collaborates on open-source tools for autonomous systems. His research trends emphasize scalability, robustness in uncertain conditions, and adaptive planning for long-term autonomy. He has published widely on exploration algorithms, volumetric mapping, and UAV navigation challenges, with applications in both static and dynamic environments. Duberg’s academic contributions span over a decade, with early work on tele-operation safety and recent advancements in semantic mapping and multi-sensor fusion. His research bridges theoretical foundations with practical implementations for deployable robotic systems.

Riccardo Sistoمشاهده پروفایل

استاد

• Formal Methods
• Cybersecurity
• Network Security
• +۱۳ مورد دیگر

Riccardo Sisto is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he also leads the NetGroup research group and is a member of the SmartData@PoliTO and Cybersecurity National Laboratory. He has held academic positions continuously since 1991, progressing from Assistant to Full Professor by 2004. Education: PhD in Computer and Systems Engineering, Politecnico di Torino (1992) Graduate in Electronic Engineering, Politecnico di Torino (1987) Riccardo Sisto’s research focuses on formal methods applied to cybersecurity, particularly in formal verification of cryptographic protocols, security automation in cloud and virtualized networks, and secure code generation. His work bridges theoretical formal methods with practical network security applications in SDN/NFV and Kubernetes environments. The recent publications highlight a strong trend toward security automation , formal verification of network and cryptographic protocols , and policy management in virtualized infrastructures . His team develops frameworks like VEREFOO and VERIGRAPH to automate firewall and security function configuration, particularly in cloud-native and multi-cluster environments. Scientific Awards and Honors: ICICS Best Demo Award (2022) IEEE HPSR Best Paper Award Finalist (2014) High Honor Paper Award at IEEE AINA (2004) Fellow of the ACM (2010) Senior Member of the ACM Riccardo Sisto has supervised numerous PhD students and leads multiple competitive research projects funded by the EU (e.g., MIRANDA, VeTeSS) and industry. He serves on editorial boards such as ELECTRONICS and has held leadership roles in international conferences. His research includes both fundamental contributions in formal methods and applied work in industrial collaborations through commercial research projects. He is actively involved in advising PhD students and post-doctoral researchers such as Daniele Bringhenti, Simone Bussa, Francesco Pizzato, and Fulvio Valenza. His lab, NetGroup, focuses on building dependable and secure distributed systems using model-driven and formally verified approaches.

• Formal Methods
• Safety-Critical Systems
• Hybrid Systems
• +۷ مورد دیگر

Zhenya Zhang is an Assistant Professor at the Intelligent Software Engineering Laboratory, Faculty of Information Science and Electrical Engineering, Kyushu University, Japan. He also serves as a Project Researcher at the National Institute of Informatics, Tokyo. His research focuses on formal methods for safety-critical complex systems , including hybrid systems (cyber-physical systems) and AI-based systems like autonomous vehicles. PhD in Informatics (2020), National Institute of Informatics/SOKENDAI Master in Computer Science (2017), Institute of Software Chinese Academy of Sciences/University of Chinese Academy of Sciences Bachelor in Software Engineering (2014), Northwestern Polytechnical University Research Interests : Quality assurance of safety-critical systems through formal methods. Specializes in verification, testing, and monitoring of hybrid systems and AI-controlled cyber-physical systems, with applications in autonomous driving validation. Key contributions include optimization-based falsification techniques and confidence measures for robustness analysis. Article Trends : Recent work emphasizes neural network verification, Monte Carlo Tree Search for falsification, and signal temporal logic monitoring. Collaborations span institutions in Japan, Singapore, and Italy, with tools like FalStar and Tumb developed for CPS testing. Scientific Awards : ACM SIGSOFT Distinguished Paper Award (ASE'24) 2nd rank in UAV Testing Competition (SBFT'24@ICSE'24) Best Paper Award nominee (EMSOFT 2018) National Scholarship, China (2011, 2012) Grants : Principal Investigator for JST BOOST (2025-2030) and multiple JSPS/Japan Society for the Promotion of Science grants. Current projects focus on neural network verification and fine-grained monitoring of temporal logic specifications. Labs & Collaborations : Works with the ERATO Metamathematics for Systems Design Project and contributes to ARCH-COMP competitions. Tools under development include FalStar-MCTS and ForeSee for hybrid system falsification.

• Formal Methods
• Model-Based Testing
• Cyber-Physical Systems
• +۵ مورد دیگر

Paolo Arcaini is a Project Associate Professor at the National Institute of Informatics (2019–present) and previously held academic positions at Charles University (Assistant Professor, 2015–2018) and the University of Bergamo (Postdoctoral Fellow). His research spans formal methods, model-based testing, and quantum software engineering, with a focus on cyber-physical systems, autonomous vehicles, and machine learning validation. He has received multiple best paper awards, including at SSBSE (2021), AITest (2020), and Mutation (2017). Educational Background: PhD in Computer Science, University of Milan (2010–2012, advisor: Elvinia Riccobene) Postdoctoral Fellow, CNR-IDPA (2013, advisor: Gloria Bordogna) Research Interests: Dr. Arcaini's work bridges abstract state machine modeling, hybrid system falsification, and quantum program testing. His recent projects address robustness in neural networks, search-based scenario generation for autonomous systems, and quantum annealing applications to test case optimization. Article Trends: His publications demonstrate expertise in hybrid system falsification using Monte Carlo tree search mutation analysis for regular expressions and neural networks quantum software testing via combinatorial and search-based methods tool development for NuSMV/Yices integration and quantum noise mitigation multi-objective optimization for autonomous delivery systems formal methods in medical software validation Scientific Recognition: Distinguished Paper Award, SSBSE 2021 Best Paper Award, AITest 2020 Best Paper Award, Mutation 2017 Teaching: He has taught courses on Formal Methods for Cyber-Physical Systems (NII 2019) Model-Based Testing (Charles University 2015–2018) Java programming labs and advanced topics Tool Development: Dr. Arcaini has created several tools including MutRex/TearRex for regular expression testing NuSeen (Eclipse-based NuSMV environment) ATGT Boolean for SAT-based testing CRAG for combinatorial road geometry generation QUIET for quantum noise mitigation BQTmizer for quantum test case optimization

Ernest Bonnahمشاهده پروفایل

استادیار

• Formal Verification
• Cyber-Physical Systems
• Security of Internet of Autonomous Things (IoAT)
• +۷ مورد دیگر

Ernest Bonnah is an Assistant Professor in the Department of Electrical and Computer Engineering at Baylor University, Waco, Texas. He leads the Secured and Dependable Intelligent Systems (SeDIS) Laboratory, conducting cutting-edge research in formal verification, security, and reliability of cyber-physical and autonomous systems. Education: Ph.D., Electrical and Computer Engineering, University of Missouri-Columbia M.S., Computer Science, University of Missouri-Columbia M.S., Telecommunications Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Ghana B.Sc., Computer Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Ghana His research lies at the intersection of formal methods, machine learning, and cybersecurity, with a focus on ensuring safety and trustworthiness in intelligent autonomous systems. He investigates techniques for formal verification of cyber-physical systems, explainable AI for robotic failures, and security in Internet of Autonomous Things (IoAT) and edge networks. His application domains include robotics, edge computing, and safety-critical health systems. The recent publication trends reflect a strong emphasis on formal verification using SMT-based model checking, particularly for temporal logic specifications in complex systems. His work integrates theoretical rigor with practical implementations to address real-world security and reliability challenges. Scientific Awards: Dr. Bonnah actively mentors graduate students and leads a funded research lab (SeDIS) at the Baylor Research and Innovation Collaborative (BRIC). He is currently recruiting Ph.D. students for fully funded positions, indicating active grant support and research supervision. His team explores novel security, blockchain, and machine learning techniques to enhance quality of service and safety in intelligent systems. The SeDIS Laboratory conducts interdisciplinary research in formal verification, explainable AI, and security for autonomous and cyber-physical systems. Located in the BRIC building, the lab provides a collaborative environment for advancing dependable intelligent computing.

• Model-Driven Engineering
• Computer Science
• Artificial Intelligence
• +۷ مورد دیگر

Moussa Amrani is a researcher with expertise in Model-Driven Engineering , Artificial Intelligence , and Database Performance Testing . His work contributes to the United Nations Sustainable Development Goals, particularly in advancing technological innovation and systems modeling. He collaborates with scholars like P.-Y. Schobbens and participates in projects such as CoTu: Erasmus+ICM for Higher Education Mobility and THCS: Testing Highly-configurable Systems . His research interests span Model Federation , UAV Coordination , and Machine Learning Applications in Databases . Recent publications highlight trends in federative model management, autonomous drone control in dynamic environments, and enhancing reproducibility in database testing. These works reflect interdisciplinary efforts bridging Computer Science , Cyber-Physical Systems , and Software Engineering . Collaborations : Active in international research groups (e.g., VeriLearn, MPM4CPS) with focus on AI verification and model-driven approaches. Research Themes : Model transformations, configurability in systems, and real-time coordination mechanisms.

Eduard Paul Enoiuمشاهده پروفایل

دانشیار

• Software Engineering
• Empirical Research
• Automated Test Generation
• +۷ مورد دیگر

Eduard Paul Enoiu is an Associate Professor at Mälardalen University's Department of Networked and Embedded Systems, affiliated with the Software Testing Laboratory and Formal Modelling and Analysis groups. He holds a PhD from Mälardalen University (2016) and an Engineer's degree from Polytechnic University of Bucharest (2009). His research focuses on software engineering, empirical studies in testing, automated test generation, and model-based verification. He teaches automated testing at master’s/PhD levels and industrial practitioners. Current research includes cognitive aspects of testing, ethical considerations, and applying AI in DevOps security. He advises theses in software testing and embedded systems development. **Education:** PhD in Software Engineering (2016), Mälardalen University Engineer's degree (2009), Polytechnic University of Bucharest **Research Interests:** Automated test generation and optimization Formal verification of embedded systems Cognitive psychology in software testing Requirements engineering and reuse Security validation in DevOps Ethical and human factors in testing **Labs/Teams:** Software Testing Laboratory Formal Modelling and Analysis of Embedded Systems group

Hans Hanssonمشاهده پروفایل

استاد

• Real-Time Systems
• Cybersecurity
• Industrial Control Systems
• +۶ مورد دیگر

Hans Hansson is a Professor at Mälardalen University since 1997, leading the Mälardalen Real-Time Research Centre (MRTC) and the strategic profile area Trusted Smart Systems (TSS). He holds multiple degrees from Uppsala University, including an MSc in Engineering Physics and a Doctor of Technology in Computer Systems. His research focuses on real-time systems, cybersecurity, industrial control systems, and safety-critical systems. He has advised over 20 PhD students, five of whom became university professors. Hans has secured over 500 MSEK in external funding from national and European grants. His work spans fault-tolerant systems, embedded software verification, and compositional safety analysis in complex systems. Key projects include the development of the Pkl language for operational design domains, security frameworks for industrial IoT systems (e.g., ICSSIM testbeds), and real-time storage solutions for fog computing. He also chairs the PROGRESS Centre for Predictable Embedded Software Systems. Publications emphasize cybersecurity in industrial systems, safety-critical software design, and real-time scheduling in time-triggered networks. His research bridges theory and practice, addressing challenges in autonomous systems, mining automation, and Industry 4.0.