Find Academic Supervisors

• Maritime Risk Analysis
• Autonomous Ship Systems
• Safety Verification
• +3 more

Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on maritime systems, autonomous vessel control, and safety verification. He actively supervises Master's students and contributes to research on risk-informed control systems, hybrid power systems, and systems-theoretic process analysis (STPA). Research Interests: Rokseth's research spans autonomous ship systems, dynamic risk assessment, and safety verification. He explores risk-based decision-making for maritime autonomy, hazard identification in hybrid propulsion systems, and control function allocation in dynamic positioning. His work integrates systems theory, machine learning, and regulatory compliance (e.g., COLREGS) to enhance safety and environmental performance in marine operations. Publications: His recent work includes probabilistic trajectory prediction frameworks for autonomous ships, STPA-based safety analyses, and studies on decarbonization barriers in the maritime industry. These publications emphasize risk modeling, systems-theoretic approaches, and simulation-based verification. Teaching: Rokseth teaches courses such as TTK4130 - Modelling and Simulation, contributing to the education of future engineers and researchers in cybernetics and maritime systems.

Christian HilbesView profile

Lecturer

• Safety-Critical Systems
• Systems Engineering
• STPA (Systems-Theoretic Process Analysis)
• +3 more

Christian Hilbes is a Lecturer at the School of Engineering of Zurich University of Applied Sciences (ZHAW). He serves as Deputy Head of the Institute for Applied Mathematics and Physics (IAMP) and co-leads the research focus on Safety-Critical Systems. Active projects include leadership roles in Autonomous Predictive Interlock Systems , Personnel Safety Systems , and Triggering Conditions for Autonomous Cars . He specializes in STPA (Systems-Theoretic Process Analysis) , UML-based modeling , and Dynamic Flowgraph Modeling for safety-critical applications. Email: christian.hilbes@zhaw.ch His research integrates safety analysis with emerging technologies like autonomous systems and nuclear facilities, contributing to publications at MIT STAMP Workshops and in journals like Nuclear Engineering and Design . He actively collaborates on European Spallation Source (ESS) safety frameworks and develops domain-specific languages for STPA.

• Maritime Risk Analysis
• Autonomous Ship Systems
• Safety Engineering
• +3 more

Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics , Norwegian University of Science and Technology (NTNU). His work focuses on integrating advanced methodologies for safety and risk control in autonomous maritime systems. He has held academic positions since at least 2014, with a consistent record of research collaboration and publication. Research Areas: Maritime risk analysis, autonomous ship systems, safety engineering, dynamic positioning systems, systems-theoretic process analysis (STPA) Key Publications: 15 most recent articles cover topics like trajectory prediction for autonomous vessels, hybrid power systems safety, machine learning in risk assessment, and dynamic positioning system reliability His publications (2014-2025) emphasize safety-critical systems in marine environments. Common themes include: Application of STPA for hazard analysis in autonomous shipping Development of risk-informed control systems Integration of machine learning with engineering risk assessment Comparative studies of different ship autonomy levels As a supervisor, Rokseth has guided master's students including Ane Joramo Stokke and Ludvig Vik Løite. His work has been presented at international conferences such as the European STAMP Workshop, International Conference on Conceptual Modeling, and the International Seminar on Safety and Security of Autonomous Vessels.

• Bayesian Statistics
• Reliability Engineering
• Risk Analysis
• +4 more

Ahmad BahooToroody is an Academy Research Fellow at Aalto University’s Department of Energy and Mechanical Engineering, specializing in Bayesian statistics, reliability engineering, and risk analysis for autonomous maritime systems. He is actively involved with the Marine and Arctic Technology research group and leads projects that integrate machine learning with safety-critical applications in the maritime and offshore sectors. Research Interests Bayesian statistical methods for reliability and risk modeling Machine learning and deep learning for anomaly detection in autonomous systems Safety assessment of offshore installations and maritime operations Prognostic health management of marine renewable energy systems Human factors and expert judgment in sociotechnical maritime systems His work often incorporates advanced techniques such as Gaussian processes, LSTM-based neural networks, and dynamic Bayesian networks to address uncertainties in complex engineering systems operating in harsh marine environments. Publication Trends Across 2022–2025, BahooToroody’s publications reveal a strong trajectory toward integrating data-driven models with physics-based simulations. Dominant themes include real-time risk monitoring of autonomous ships, failure prognosis for unattended machinery, and safety assessment frameworks for offshore structures. His collaborative outputs span high-impact journals such as Reliability Engineering & System Safety and Safety Science , underscoring his leadership in maritime safety analytics. Research Groups & Labs Marine and Arctic Technology Research Group, Aalto University Academy Research Fellow network within the Department of Energy and Mechanical Engineering Doctoral Supervision & Grants While specific grant details are not listed, his role as Doctoral Candidate Supervisor since 2020 indicates active mentorship of PhD researchers. He is also the Principal Investigator on projects funded under the Academy of Finland Fellowship scheme, supporting next-generation maritime risk analytics.

• Maritime Safety
• Autonomous Systems
• Risk Assessment
• +3 more

Meriam Chaal is a Visiting Professor at the Department of Energy and Mechanical Engineering and affiliated with the Marine and Arctic Technology school at Aalto University . She holds a Doctor of Technology (Tekn. toht.) in Mechanical Engineering awarded on 25 March 2024. Her research focuses on maritime safety, autonomous systems, risk assessment, and navigation engineering , with a particular emphasis on systemic hazard analysis and safety frameworks for autonomous ships. Recent work includes developing machine learning models for maritime accident prediction, frameworks for risk control options, and participatory design of automated maritime solutions. She collaborates internationally on projects addressing maritime practitioners' skill adaptations and educational needs for autonomous systems. Her research activity spans 17 publications from 2019–2025, including peer-reviewed articles, conference proceedings, and a doctoral thesis. Key themes include STPA-based safety methodologies, Bayesian network integration, and bibliometric reviews of autonomous shipping literature. Chaal’s work aligns with UN Sustainable Development Goals, particularly in advancing safe and sustainable maritime technologies. Notable contributions include a 2023 thesis on system-theoretic approaches to shipping safety and a 2025 article on autonomous navigation risk assessment. Her interdisciplinary collaborations span human factors, machine learning, and systems engineering, reflecting a commitment to bridging theoretical research with practical maritime challenges.

• Autonomous Driving Systems
• Scenario-Based Testing
• System-Theoretic Process Analysis (STPA)
• +4 more

Pavel Nedvedicky is a researcher at the Chair of Software Engineering (Prof. Stefan Wagner) within the Technical University of Munich's Informatics faculty. He focuses on enhancing safety in autonomous driving systems through scenario-based testing methodologies, system-theoretic analysis, and virtual simulation techniques. His work bridges academic research with industrial practice, particularly in addressing validation challenges for autonomous systems. Research Interests: Safety of ADAS/ADS systems Scenario-based testing frameworks and critical scenario identification System-Theoretic Process Analysis (STPA) DevOps integration in continuous testing He actively supervises student theses in these areas, emphasizing collaboration with industry partners. Current open topics include a survey on industrial adoption of scenario-based testing for autonomous driving systems. His research contributes to closing gaps between theoretical advancements and real-world deployment challenges in autonomous vehicle validation.

• Functional Safety
• Safety Instrumented Systems (SIS)
• Cybersecurity in Industrial Systems
• +5 more

Mary Ann Lundteigen is a Professor in instrumentation systems and safety at NTNU’s Department of Engineering Cybernetics, part of the Faculty of Information Technology and Electrical Engineering. She holds an MSc (1993) and PhD (2009) in Engineering Cybernetics from NTNU, with 15+ years of industry experience across Phillips Petroleum, Nidar AS, DNV, and SINTEF. She has led major research initiatives including SFI SUBPRO (2014–2023) and SFI Autoship (2019–2022), focusing on subsea production, autonomous ships, and cybersecurity for safety-critical systems. Her research emphasizes functional safety of industrial control systems, cybersecurity compliance with standards like IEC 62443, and the integration of AI in safety-critical environments. She leads projects such as APOS 2.0 (digital lifecycle management) and CyberBarrier Management, while supervising multiple PhD students and postdocs. Lundteigen co-authored over 100 publications and received the ExxonMobil Doctoral Prize (2009) for her thesis on SIS reliability. Professional roles include: Co-director of SFI SUBPRO Director of SFI Autoship’s initial phase Adjunct Professor at NTNU (2013) Member of IEC 61511 maintenance team and PDS forum organizing committee Current research focuses on: Cybersecurity threats to SIS AI applications in safety systems Digital twins for safety demonstration Industry 4.0 frameworks like OPC UA Her work bridges academia and industry, with active projects funded by the Norwegian Research Council and industrial partners like Equinor and DNV.

Manuel MaarekView profile

Associate Professor

• Cybersecurity
• Computer Security
• Secure Programming
• +6 more

Manuel Maarek is an Associate Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University, specializing in Computer Science. His research focuses on cybersecurity, secure programming, and educational technologies, particularly leveraging serious games and collaborative methodologies for enhancing security awareness. His work integrates formal methods with practical applications, addressing topics like Bitcoin transaction analysis, developer-centric security training, and blockchain privacy. He has co-authored over 29 peer-reviewed publications and received awards including the 2018 Teaching Excellence Award and the 2022 EICC Best Paper Award. Key Research Themes: Cybersecurity Education, Secure Programming Practices, Cryptocurrency Analysis, Game-Based Learning Collaborations: Active in international collaborations, particularly in cybersecurity co-design and blockchain forensics Maarek’s recent projects include the 'Serious Slow Game Jam' methodology for cybersecurity education and investigations into large language models for student feedback. He actively contributes to improving software engineering education through integrated learning platforms like Canvas and GitLab.

Karim HardyView profile

Associate Professor

• Public Health
• Health Engineering
• Risk Analysis
• +10 more

Karim Hardy is an Associate Professor in the Department of Mathematics, Science, and Technology at the College of Arts and Sciences, Embry-Riddle Aeronautical University Worldwide. His academic and professional work bridges safety engineering, public health, emergency management, and risk analysis. Ph.D. in Sciences and Engineering of Risk Activities – Mines ParisTech, France M.S. in Health Technologies and Sciences (Public Health) – University Cote d'Azur Master in Law and Political Science – University of Nice Sophia Antipolis Master in Euro-Mediterranean Legal Areas – University of Toulon Dr. Hardy’s research focuses on public health, system safety, resilience engineering, and crisis management within complex socio-technical systems. His work integrates system dynamics, accident modeling, and organizational behavior to enhance safety protocols across aviation, health, and industrial sectors. His recent publications highlight a growing trend in merging public health strategies with risk management, particularly in pandemic preparedness and international crisis coordination. He applies systemic approaches like STAMP to diverse domains—from airport resilience to environmental treatment processes—demonstrating interdisciplinary innovation. Dr. Hardy has presented at academic forums, including a 2023 presentation on global health crisis management. His scholarly contributions include peer-reviewed articles, book chapters, preprints, and theses, reflecting sustained engagement with high-reliability systems and emergency response frameworks. He has served as a visiting researcher at the Massachusetts Institute of Technology (MIT) in system safety and dynamics and as a Postdoctoral Fellow at UC Berkeley’s Haas Business School, focusing on High-Reliability Organizations. His prior industry experience as a safety engineer and risk manager enriches his academic perspective with practical insights. Dr. Hardy is actively involved in professional organizations and holds certifications in safety and emergency management, though specific awards are not listed in the text. He mentors future professionals, contributing to education in safety, health, and risk disciplines.

Victor BolbotView profile

Researcher

• Autonomous ships
• Marine systems safety
• Ship propulsion systems
• +3 more

Victor Bolbot serves as a Postdoctoral Researcher in the Department of Energy and Mechanical Engineering at Aalto University, Finland, affiliated with the Marine and Arctic Technology research group. His work focuses on advancing safety, reliability, and cybersecurity frameworks for autonomous maritime systems through rigorous systems engineering approaches and data-driven methodologies. He maintains active collaborations with international researchers and institutions, evidenced by extensive co-authorship across high-impact publications. Dr. Bolbot's research centers on autonomous ships, marine systems safety, ship propulsion cybersecurity, and risk modeling. He employs systems-theoretic process analysis (STPA), Bayesian networks, and association rule mining to address critical challenges including maritime accident causation, cybersecurity vulnerabilities in dual-fuel engines, safety acceptance criteria for autonomous vessels, and socio-technical implications of maritime automation. His methodological innovations bridge theoretical safety engineering with practical applications in Arctic navigation, inland waterways, and regulatory compliance, emphasizing the integration of cyber-physical risk assessment. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Development of cyber-physical risk frameworks like STPA-Cyber for maritime cybersecurity; (2) Real-time Bayesian modeling for dynamic operations including remote pilotage and ice navigation; and (3) Socio-technical investigations into regulatory frameworks, educational needs, and workforce skill transformations for autonomous shipping. His work consistently addresses the interplay between technological innovation and safety assurance, with growing emphasis on cybersecurity as a critical maritime safety component. As an active member of Aalto University's Marine and Arctic Technology research group, Dr. Bolbot contributes to interdisciplinary projects tackling complex challenges in marine safety engineering, Arctic operations, and sustainable maritime technologies. The group's collaborative environment supports the development of safer, more efficient, and environmentally conscious maritime systems through experimental validation, computational modeling, and industry partnerships.

• System Safety Engineering
• Maritime Risk Management
• AI in Risk Analysis
• +3 more

Sunil Basnet is a Visiting Professor in the Department of Energy and Mechanical Engineering at Aalto University, affiliated with the Marine and Arctic Technology school. His work focuses on system safety, maritime risk management, and AI applications in safety-critical systems. He holds a Doctor of Technology (2023) and a Diploma in Mechanical Engineering (2018) from Aalto University. Research interests include system dynamics modeling for maritime operations, Bayesian risk modeling, cybersecurity frameworks for autonomous ships, and the ethical integration of AI in human resources. His work contributes to UN Sustainable Development Goals related to industry innovation and infrastructure safety. Recent research trends show a focus on: real-time risk monitoring systems using Bayesian networks, cybersecurity frameworks for remote pilotage, and AI-driven predictive analytics in HR management. Collaborations span international maritime safety projects and bibliometric reviews of autonomous ship research. No awards or grants are explicitly listed, though his doctoral thesis (2023) on formal safety assessment in maritime pilotage highlights significant contributions to the field. Advising activities are not detailed in the provided materials.

• Safety Engineering
• Systems Theory
• Industrial Engineering
• +7 more

Prof. Gravio Giulio is a Full Professor at the Sapienza University of Rome within the Department of Industrial and Management Engineering . His work focuses on systemic safety, cyber-physical systems, and resilience engineering. He specializes in risk assessment methodologies like STAMP/STPA and FRAM, with applications in aviation, industrial automation, and healthcare. Research interests include Functional Resonance Analysis (FRAM) Cyber-socio-technical systems Emergency management systems Human reliability analysis Safety-critical systems design His recent work explores STAMP-based simulations for eVTOL safety, knowledge graphs in industrial near-miss reporting, and cyber resilience in critical infrastructure. He has pioneered tools like myFRAM for functional resonance analysis. Key projects include: - Systemic risk management for Advanced Air Mobility - Resilience engineering in anesthesia practices - Safety analysis of medical gas pipelines - STPA-Sec for security-critical systems Prof. Giulio collaborates with ANSPs (Air Navigation Service Providers) and industry partners, focusing on bridging theoretical frameworks with practical safety implementations.

• Autonomous Driving
• Automotive Safety
• System Theoretic Process Analysis (STPA)
• +2 more

Eva Zimmermann is affiliated with the Chair of Software Engineering at the Technical University of Munich (TUM), led by Prof. Stefan Wagner. Her primary role involves research and teaching within the Informatics Heilbronn department. She focuses on Autonomous Driving, Automotive Safety (particularly STPA methodologies), and DevOps practices with an emphasis on Continuous Monitoring. Research interests include advancing safety frameworks for autonomous systems and integrating DevOps principles into software engineering workflows. She expresses openness to supervise bachelor's and master's theses in alignment with her research areas, including industry collaborations. Affiliated with the Bildungscampus 2 location in Heilbronn, her contact details are publicly available via e.zimmermann@tum.de.

Glen MasonView profile

Lecturer

• Functional Safety (Automotive)
• Safety of the Intended Functionality (SOTIF)
• Machine Learning
• +6 more

Glen Mason is a Lecturer in the Faculty of Creative and Digital Arts and Sciences at Anglia Ruskin University (ARU), specializing in computer science and data science education while concurrently conducting PhD research at the University of Surrey's Connected and Autonomous Vehicles Laboratory (CAV Lab). His academic credentials include: PhD in Automotive Engineering, University of Surrey MSc Reliable Embedded Systems, University of Leicester PGCE, University of Northampton BEng (Hons) Electrical and Electronic Engineering Research spans automotive safety-critical systems with emphasis on Machine Learning applications for connected vehicles , Functional Safety (SOTIF) , and Robust Control Systems . His work integrates Systems Theoretic Process Analysis (STPA) with Reliable Embedded Systems design to address safety challenges in autonomous transportation and power electronics. Professional recognition includes: Chartered Engineer status with the Institution of Engineering and Technology (IET) Senior Fellowship of the Higher Education Academy As an active academic contributor, Glen serves as Senior External Examiner and consultant for BTEC engineering qualifications (levels 4-7), provides journal reviews, and supervises research in Machine Learning and Safety Critical Systems. His industry-academic bridge is reinforced by 12 years of pre-education engineering experience in electronics and power systems, complemented by leadership roles as Course Leader and Head of Faculty during his 19-year HE career. He operates within the Connected and Autonomous Vehicles Laboratory (CAV Lab) ecosystem at Surrey while maintaining teaching responsibilities for ARU's BSc Applied Computer Science and Data and Analytical Science programs.

Karl Reiner LermerView profile

Researcher

• Safety-Critical Systems
• Software Engineering
• Systems Engineering
• +1 more

Dr. Karl Reiner Lermer is a researcher at the Zurich University of Applied Sciences, affiliated with the School of Engineering. His work focuses on safety-critical systems and software reliability, with significant contributions to formal accident analysis and dynamic flowgraph modeling. His research projects include: Formal Analysis of Accidents Application of STPA (Systems-Theoretic Process Analysis) to digital control and reactor protection technology Software reliability and Dynamic Flowgraph Modeling These projects highlight his expertise in ensuring safety and robustness in complex technical systems.