Find Academic Supervisors

• Machine Learning
• Computer Vision
• Safety-Critical Systems
• +7 more

Ran Wei is a researcher at the University of Science and Technology of China, Department of Chemistry, with extensive contributions across interdisciplinary domains. His work bridges Computer Science , Biomedical Imaging , and Transportation Systems , focusing on active inference models, digital twins, and multimodal learning. Academic Affiliation : University of Science and Technology of China, Department of Chemistry Research Themes : Ran Wei's research explores active inference for adaptive systems, multimodal fusion in computer vision, and domain-specific knowledge graphs for engineering applications. He also investigates federated learning on heterogeneous networks and automated safety analysis for cyber-physical systems. Recent Article Trends : His publications from 2025–2021 span AI-driven engineering (e.g., construction project management), biomedical imaging (lesion detection, radiomics), and transportation systems (driver behavior modeling). Methodologically, he integrates transformers , Bayesian inference , and active learning frameworks. Scientific Collaborations : Ran Wei collaborates with experts in autonomous vehicles (Alfredo García, Anthony D. McDonald), biomedical engineering (Qiaolin Ye, Yifan Cai), and safety-critical systems (Tim Kelly, Simon Foster).

Tichakorn WongpiromsarnView profile

Assistant Professor

• Formal Methods
• Autonomous Systems
• Robotics
• +5 more

Tichakorn Wongpiromsarn is an Assistant Professor in the Department of Computer Science at Iowa State University, where he directs the Autonomous Systems Laboratory. He also holds a Visiting Academic position at Amazon Robotics. He earned his Ph.D. in Mechanical Engineering from the California Institute of Technology (2010), focusing on formal methods and robotics. His research emphasizes formal methods, motion planning, and decision-making for autonomous systems, with applications in robotics and transportation. Affiliations: Iowa State University, Amazon Robotics Education: Ph.D. (Caltech, 2010), M.S. (Caltech, 2006), B.S. (Cornell, 2005) Research interests include formal specification and verification of autonomous systems, distributed control, and safety-critical applications. He led planning teams at nuTonomy and contributed to the 2007 DARPA Urban Challenge. Current projects address perception inconsistency in autonomous vehicles, specification formalisms for conflicting requirements, and runtime verification. Teaching includes courses on autonomous systems, motion algorithms, and algorithms design. He has secured NSF grants and industry collaborations, focusing on safe learning-enabled systems and mobility solutions.

Sebastian PeitzView profile

Professor

• Multiobjective Optimization
• Optimal Control
• Machine Learning
• +3 more

Sebastian Peitz is Professor (previously Assistant Professor) at Paderborn University's Department of Computer Science, leading the Data Science for Engineering group. He obtained his PhD in Multiobjective Optimization from Paderborn University and MSc in Mechanical Engineering from RWTH Aachen. His research develops computational methods for multiobjective optimization, optimal control, and machine learning with applications in fluid dynamics, autonomous systems, and industrial processes. He leads the BMBF-funded Multicriteria Machine Learning group. Research trends show consistent focus on Koopman operator theory, reinforcement learning applications in control systems, and physics-informed machine learning across publications. Achievements include the 2019 PRECEDE Best Paper Award and leadership in international optimization conferences.

Jim WoodcockView profile

Professor

• Software Engineering
• Formal Methods
• Theorem Proving
• +3 more

Jim Woodcock is Professor and Head of the Department of Computer Science at the University of York. With a distinguished career spanning GEC Hirst Research Centre, University of Surrey, University of Oxford, and University of Kent, he specializes in formal methods for software and system development. His research focuses on unifying theories of programming, hybrid systems, theorem proving, and robotic software verification. His research interests include: Formal semantics and verification techniques Theorem proving and model checking Robotic control software and hybrid systems Probabilistic system modeling Cyber-physical systems engineering Woodcock's publications demonstrate consistent focus on practical applications of formal methods, particularly in robotics and safety-critical systems. Recent work emphasizes probabilistic modeling, digital twins, and neural network verification. Scientific Awards: Fellow of the Royal Academy of Engineering (2011) Queen's Award for Technological Achievement (1996) He leads multiple research projects including the EPSRC-funded RoboTest and Trustworthy Autonomous Systems Verifiability Node. His team develops tools like RoboChart and RoboTool for formal specification and verification of robotic systems.

• Machine Learning
• Artificial Intelligence
• Vehicular Communication
• +4 more

Cristofer Englund is the Dean of the School of Information Technology at Halmstad University and holds a professorship in Information Technology. He earned his PhD in Electrical Engineering in 2007. His teaching focuses on supervising bachelor and master’s theses in machine learning and artificial intelligence (AI), with students receiving awards such as Wimanska priset (2019) and the SAIS Master Thesis Award (2017, 2021). His research spans machine learning applications in emotion/posture recognition, behavior prediction, anonymization, and vehicular communication for traffic safety and automated driving. He currently supervises Felix Rosberg (Engage Studios) on image/video anonymization and Maytheewat Aramrattana (VTI) on connected transportation safety analysis. Research interests include AI ethics, safety-critical systems, and smart city technologies. Recent work emphasizes de-identification systems, drone detection, and federated learning in automotive ecosystems. His articles analyze AI applications in urban infrastructure, cybersecurity for anonymization, and real-time drone surveillance. Notable student awards include grants for Felix Rosberg’s work on anonymization defense mechanisms and Maytheewat’s contributions to traffic safety modeling. Englund collaborates with industry partners like Engage Studios and VTI, integrating academic research with real-world challenges. His work bridges theoretical advancements in machine learning with practical implementations in transportation, cybersecurity, and urban planning.

Saman ZonouzView profile

Associate Professor

• Cyber-Physical Systems Security
• Critical Infrastructure Protection
• Embedded Systems Security
• +7 more

Saman Zonouz is an Associate Professor at Georgia Institute of Technology with joint appointments in the School of Electrical and Computer Engineering and the School of Cybersecurity and Privacy. He joined Georgia Tech in 2022 after prior roles at Rutgers University and the University of Miami. His research focuses on cybersecurity and privacy in cyber-physical systems, particularly critical infrastructures such as power grids and industrial control systems. Zonouz holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (2011) and a B.Sc. from Sharif Institute of Technology (2006). His work bridges theoretical computer science with practical engineering challenges, emphasizing resilience, attack detection, and physical-layer security. His research interests include attack detection in cyber-physical systems, embedded systems security, side-channel attacks, and resilient distributed control strategies. Recent trends in his publications highlight advancements in hardware implant detection, stealthy supply chain attacks, and cross-domain resilience frameworks for modern power systems. Zonouz has received prestigious awards including the Presidential Early Career Award for Scientists and Engineers (PECASE), NSF CAREER Award, and NSA Significant Research Recognition. His work often involves collaborations with industry and government agencies to address real-world cybersecurity challenges. He has led projects funded by NSF, AFOSR, and Google, focusing on topics like trustworthy additive manufacturing, privacy-preserving IoT systems, and cyber-informed engineering education. His lab develops tools such as OpenConduit for power system simulation and Guide-Guard for bioengineering applications.

Cyrus NearyView profile

Assistant Professor

• Artificial Intelligence
• Robotics
• Reinforcement Learning
• +5 more

Cyrus Neary is an incoming tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), where he will direct the Artificial Intelligence in Robotics & Engineering (AIRE) Lab. Previously, he was a postdoctoral researcher at Mila (Québec AI Institute) and l’Université de Montréal. His research bridges AI system engineering and engineering applications, focusing on compositional design, physics-informed learning, and reliable autonomous systems. He holds a Ph.D. and M.Sc. in Computational Science from The University of Texas at Austin’s Oden Institute, and a Bachelors of Applied Science in Engineering Physics from UBC. Education : Ph.D. in Computational Science (2024), University of Texas at Austin M.Sc. in Computational Science (2021), University of Texas at Austin B.A.Sc. in Engineering Physics (Honors Mathematics minor), University of British Columbia (2019) Research Focus : Developing AI systems that integrate engineering principles and physics-based knowledge for control, robotics, and autonomy. Key areas include multiagent reinforcement learning, physics-informed neural networks, and compositional system design. His work emphasizes reliability, certification, and efficient data utilization in high-stakes applications. Lab & Opportunities : The AIRE Lab at UBC seeks students (MASc/PhD) to explore AI-robotics intersections. Application deadlines are Jan 15, 2025, with priority given to early submissions (Dec 31, 2024).

Sergiy BogomolovView profile

Associate Professor

• Cyber-Physical Systems
• Formal Verification
• Artificial Intelligence
• +4 more

Sergiy Bogomolov is an Associate Professor in Cyber-Physical Systems at the School of Computing, Newcastle University, UK. His research focuses on developing algorithms and tools for modeling and analyzing complex systems, with a particular emphasis on formal verification, control theory, and artificial intelligence applications in cyber-physical systems. He has over 40 publications in top venues such as EMSOFT, HSCC, AAAI, and IJCAI, and has won multiple awards including Best Paper awards at HSCC'16 and HVC'14. His work emphasizes scalable solutions for hybrid systems analysis and has been supported by agencies like the US Air Force and the Australian Defence Science and Technology Group. Education: PhD and M.Sc. from the University of Freiburg, Germany. He previously held positions at ANU (Australia) and IST Austria as a postdoc. Research interests include hybrid systems reachability analysis, safety verification, and the integration of AI techniques with formal methods. His software contributions include SpaceEx extensions and the JuliaReach toolbox. Scientific awards include Best Repeatability Evaluation Package Award (HSCC'16), Best Tool Award (ARCH'16), and Best Paper Award (HVC'14). He advises PhD students Kostiantyn Potomkin and Abdelrahman Hekal, and collaborates on projects like parameter synthesis and autonomous systems safety.

Derek RaysideView profile

Associate Professor

• Autonomous Systems
• Software Engineering
• Formal Methods
• +3 more

Derek Rayside is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, and serves as Associate Dean for Co-operative Education and Professional Affairs. His research spans autonomous systems, software engineering, formal methods, and construction project management. He holds a faculty position in a top-tier engineering program with affiliations to both academic and administrative roles at the university. Research interests include advancing autonomous vehicle decision-making through reinforcement learning and computer vision techniques, improving software development methodologies via formal verification and collaborative platforms, and enhancing project management practices in complex construction environments. His work integrates interdisciplinary approaches combining control theory, machine learning, and social network analysis. Recent publications focus on autonomous driving challenges (action recognition, intersection navigation), software engineering education (game-based learning), and formal methods for system validation. His contributions bridge theoretical advancements with practical applications in safety-critical systems and industrial workflows. Teaching responsibilities include the ECE351 course on signals and systems. He has led curriculum development efforts and maintains a personal research website at the University of Waterloo's ECE department.

Doğan UlusView profile

Assistant Professor

• Runtime Verification
• Cyber-Physical Systems
• Autonomous Systems
• +3 more

Doğan Ulus is an Assistant Professor at the Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey. He holds a PhD in Computer Science from Université Grenoble Alpes (2018) and BSc/MSc degrees in Electrical Engineering from Boğaziçi University (2011, 2013). His research focuses on developing testing, verification, and validation tools for complex cyber-physical systems, particularly automated driving systems and autonomous robots. Education: PhD, Université Grenoble Alpes (2018) MS, Boğaziçi University (2013) BS, Boğaziçi University (2011) His primary research interests include runtime verification , simulation-based testing , formal methods , and automata theory , with applications in safety validation of autonomous systems. He previously worked as a postdoctoral researcher at Boston University Robotics Lab and as a Senior Verification Engineer at Samsung Semiconductor, Inc., in San Jose, CA, USA. Doğan contributes to academic committees such as the Systems and Networks Committee and Web Committee at Boğaziçi University. His work emphasizes the integration of formal methods with practical software development practices for robust system validation.

• Blockchain Technology
• Cyber-Physical Systems
• Building Information Modeling (BIM)
• +3 more

Thomas Preindl is a Researcher at the Automation Systems department of TU Wien's Faculty of Mechanical and Automotive Engineering and Transportation. His work focuses on blockchain technology, BIM integration, and cyber-physical systems, with applications in construction, energy systems, and Industry 4.0. He holds a BSc and a diploma in engineering from TU Wien. Education : BSc in Engineering, TU Wien (year not specified); Diploma in Automation Engineering, TU Wien (2019). Research : Preindl’s research explores blockchain applications in process automation, decentralized systems, and circular economy. Notable projects include DiCYCLE (2022–2026), exploring blockchain for sustainable construction, and FORA (2017–2021) on facility management frameworks. His work often bridges BIM with smart contracts to enhance transparency and efficiency in construction workflows. Articles : His recent publications address confidential process execution on blockchain, storage optimization for containerized systems, and BIM-integrated blockchain tools. Key themes include decentralized frameworks, fault detection, and energy system dependability. Grants & Projects : Funded by the Austrian Research Promotion Agency (FFG), his projects span 2015–2027, focusing on circular economy, energy data spaces, and IoT integration in industrial systems. Advising : Supervised 6 diploma theses on topics like zero-knowledge proofs in BPM, decentralized storage systems, and BIM data management via smart contracts. Labs/Teams : Active in TU Wien’s Automation Systems group, contributing to interdisciplinary projects in industrial automation and digital transformation.

• Programming Languages
• Formal Verification
• Privacy Risk Analysis
• +2 more

Willard Rafnsson is an Associate Professor in Programming Logic and Semantics at IT University of Copenhagen. His research develops formal methods for security and privacy, particularly probabilistic programming approaches for quantifying privacy risks. Research investigates privacy risk assessment methodologies, attacker knowledge modeling, and formal verification techniques. Recent work examines privacy vulnerabilities in genetic data and develops tools for leakage quantification. Rafnsson leads projects on practical static analysis and reliable AI for autonomous systems, focusing on security foundations.

Pantelis FrangoudisView profile

Researcher

• Mobile/Wireless Networking
• Edge Computing
• Network Softwarization
• +4 more

Pantelis Frangoudis is a PostDoctoral Researcher at the Distributed Systems Group of the Vienna University of Technology since 2019. His academic journey includes a Ph.D. in Computer Science (2012), M.Sc. (2005), and B.Sc. (2003) from the Department of Informatics, Athens University of Economics and Business (AUEB) , Greece. His research spans Edge Computing , IoT , Network Softwarization , Federated Learning , and Wireless Networking , focusing on adaptive systems and security. Education B.Sc. in Computer Science (2003), AUEB M.Sc. in Computer Science (2005), AUEB Ph.D. in Computer Science (2012), AUEB His research explores Edge Computing Continuum systems, with emphasis on QoS-aware orchestration , serverless edge deployment , and self-adaptive IoT services . Recent work addresses federated learning for 6G , WebAssembly for edge serverless , and dynamic resource allocation in heterogeneous environments. Key projects include AloTwin (2023–2025), INTEND (2024–2026), and EDENSPACE (2019–2022). His publications (2025–2020) cover machine learning for 5G/6G , MEC application orchestration , and IoT security , with a focus on distributed systems and edge-cloud collaboration . Scientific Awards ERCIM Alain Bensoussan Post-Doctoral Fellowship He has supervised multiple diploma theses at TU Vienna, including topics like serverless edge computing , traffic light AI optimization , and vertical farming IoT systems . His collaborations with institutions like EURECOM (France) and IRISA/INRIA (France) reflect a global academic footprint.

Fikret ÇalışkanView profile

Professor

• Control Systems
• Fault Detection and Isolation
• Kalman Filtering
• +5 more

Fikret Çalışkan serves as a Professor in the Department of Control and Automation Engineering at Istanbul Technical University. With an h-index of 15 and 55 research outputs documented through Scopus, his academic career spans multiple decades of contributions to control systems engineering. His research profile shows consistent publication activity from 1995 through projected 2025 works, with significant output in recent years. Professor Çalışkan's research focuses on advanced control systems with particular expertise in Kalman filtering techniques , fault detection and isolation , and autonomous aircraft systems . His fingerprint analysis reveals strong specialization in actuator systems (80%), Kalman filters (100%), and multiple fault detection methodologies (47-53%). His work bridges theoretical control engineering with practical applications in UAV technology, indoor positioning systems, and aircraft propulsion. Analysis of his recent publications shows a clear trajectory toward increasingly complex autonomous systems, with growing integration of machine learning techniques (particularly reinforcement learning) with traditional control methodologies. His work demonstrates strong interdisciplinary connections between aerospace engineering, robotics, and signal processing, with applications spanning from indoor navigation to hybrid-electric aircraft propulsion. Professor Çalışkan has supervised 15 research projects throughout his career, securing funding for significant research initiatives including AI-based visual inspection systems for aircraft surfaces (2020-2022) and nonlinear multirotor modeling, fault detection, and implementation (2018-2021). His research demonstrates strong industry relevance with practical applications in aviation safety, autonomous systems, and energy-efficient control solutions.

Antonis PapachristodoulouView profile

Professor

• Control Engineering
• Nonlinear Systems
• Synthetic Biology
• +5 more

Professor Antonis Papachristodoulou is a faculty member at the University of Oxford , serving as the Professor of Control Engineering and an Official Fellow at Kellogg College . He previously held roles as a Tutorial Fellow at Worcester College (2010-2024), EPSRC Fellow (2015-2021), and Director of the EPSRC & BBSRC Centre for Doctoral Training in Synthetic Biology (2014-2023). His academic journey includes an MA/MEng in Electrical and Information Sciences from the University of Cambridge (2000) and a PhD in Control and Dynamical Systems at the California Institute of Technology (2005) with a minor in Aeronautics. His research spans Control Engineering , Systems Biology , and Synthetic Biology , focusing on robust analysis of nonlinear networked systems, Sum of Squares optimization, and applications in biological systems, fluid mechanics, and smart grids. His recent publications highlight advancements in Distributed Control , Neural ODE-based Controllers , and Safe Reinforcement Learning . Scientific Awards: European Control Award (2015) O. Hugo Schuck Best Paper Award IEEE Fellow He leads the SYSOS (System of Systems) Group , collaborating with Oxford Biochemistry, Engineering Science, and international institutions. His grants include the EPSRC Programme Grant EEBio and co-I roles in bioengineering and autonomous systems initiatives.