Find Academic Supervisors

Atrisha SarkarView profile

Assistant Professor

• Human-centric multiagent systems
• Human-AI interaction
• Human-robot interaction
• +4 more

Atrisha Sarkar is an Assistant Professor in the Department of Electrical and Computer Engineering at Western University , Canada, and heads the Humans and Autonomous Agents Lab . She is also a faculty member of the Rotman Institute of Philosophy and a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society . Her research integrates empirical and behavioral game theory with software engineering to design human-centric AI systems that prioritize safety and societal well-being. Education: Atrisha holds a PhD and has previously served as a postdoctoral fellow at the Schwartz Reisman Institute for Technology and Society at the University of Toronto under the supervision of Prof. Gillian Hadfield. Research Focus: Her work centers on human-centric multiagent systems , combining methods from: Behavioral and empirical game theory Software engineering Human-AI and human-robot interaction AI safety and reliability She applies these to domains such as autonomous driving, cooperative AI, and social media dynamics, aiming to ensure AI systems align with human values and societal norms. Publications and Impact: Atrisha has published extensively in top-tier venues including AAAI , AAMAS , ICRA , NeurIPS , and EC . Her work spans from theoretical models of strategic behavior to practical frameworks for validating autonomous systems, with a strong emphasis on real-world applicability. Labs and Teams: She leads the Humans and Autonomous Agents Lab at Western University, where her team focuses on designing AI agents that can cooperate effectively with humans in complex, dynamic environments.

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.

Michael SkinniderView profile

Assistant Professor

• Computational Biology
• Machine Learning
• Metabolomics
• +4 more

Michael Skinnider serves as Assistant Professor at Princeton University's Lewis-Sigler Institute for Integrative Genomics and Assistant Member of the Ludwig Princeton Branch. His research develops AI-driven computational methods to identify unknown small molecules in mass spectrometry data, with applications in cancer biology and forensic drug detection. His educational background includes: BArtsSc from McMaster University (2015) PhD from University of British Columbia (2021) MD from University of British Columbia (2023) Skinnider's work centers on illuminating the "metabolomic dark matter" —unidentified chemical entities in mass spectrometry data. His lab pioneers machine learning approaches for metabolite identification, focusing on connections between unknown metabolites, cancer risk, and the microbiome. Recent innovations include chemical language models that transform mass spectrometry outputs into chemical structures, with applications spanning cancer diagnostics to forensic analysis of designer drugs. His research bridges computational biology, chemistry, and clinical medicine through low-data learning techniques. Publication trends reveal three dominant themes: (1) AI-driven metabolite identification (25% of recent work), (2) single-cell/spatial data analysis (40%), and (3) molecular interaction networks (35%). His 2024 Nature Machine Intelligence paper demonstrated that invalid SMILES strings enhance chemical language models , overturning previous assumptions. Articles consistently apply computational methods to biological discovery, with growing emphasis on cancer metabolism and translational applications. Major recognitions include: Forbes 30 Under 30 (2022) International Birnstiel Award (2022) Dan David Prize Borealis AI Fellowship NIH Award C&EN's Talented Twelve (2023) Young Explorer Award Grand Prize Skinnider leads the Skinnider Research Lab at Princeton's Carl Icahn Laboratory, which collaborates with forensic laboratories and Ludwig cancer researchers. The lab specializes in transforming mass spectrometry data into biological insights through innovative algorithms. During his undergraduate studies, he co-founded Adapsyn Bioscience to translate natural product discovery research into commercial applications. Current projects include developing metabolome-wide identification tools and exploring diet-derived metabolites that modulate cancer progression.

Morteza Haghir ChehreghaniView profile

Professor

• Machine Learning
• Decision Making
• Reinforcement Learning
• +17 more

Morteza Haghir Chehreghani is a Professor of Artificial Intelligence and Machine Learning at the Data Science and AI Division of Chalmers University of Technology , Sweden. He leads the Machine Learning and Decision Making Lab and is affiliated with WASP , CHAIR , and ELLIS . Education : PhD in Computer Science (2014) from ETH Zurich under Prof. Dr. Joachim M. Buhmann Prior Roles : Staff Research Scientist at Naver Labs Europe (2014-2018) Research spans Interactive Machine Learning , Sequential Decision Making , Federated Learning , Efficient Deep Learning , and Graph-Based Learning . Key application areas include Transport , Autonomous Systems , Energy , Drug Discovery , and Computational Biology . Selected Publications (2020-2025) demonstrate expertise in Reinforcement Learning for drug design, Minimax Distance Measures for clustering, and Graph Neural Networks for trajectory analysis. Current work focuses on Combinatorial Bandits and Human-in-the-loop AI . Teaching includes graduate courses like Advanced Topics in Machine Learning (DAT441/DIT41), Algorithms for Machine Learning (TDA233/DIT382), and PhD-level Advanced Reinforcement Learning . He has also taught Statistical Methods for Data Science and Theoretical Foundations of ML . Patents include systems for Autonomous Vehicle Motion Control , K-NN Search via Minimax Distances , and Trip Prediction Algorithms . Collaborative projects involve Nature Communications (2022) and multiple ICML / CVPR publications.

Jonathan GratchView profile

Research Professor

• Affective Computing
• Cognitive Modeling
• Human-Computer Interaction
• +6 more

Jonathan Gratch is a Research Professor at the University of Southern California (USC) with joint appointments in Computer Science , Psychology , and Media Arts and Practice . He serves as Director for Virtual Human Research at USC's Institute for Creative Technologies and leads the USC Affective Computing Group . His work focuses on computational models of human cognitive and social processes, particularly emotions, and their applications to virtual environments. Education: Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (1995) Gratch's research spans Affective Computing , Cognitive Modeling , and Human-Computer Interaction , with a focus on creating emotionally intelligent virtual agents. His projects include the development of computational emotion models (e.g., EMA) and virtual human systems for training, healthcare, and social interaction studies. Key applications include the Mission Rehearsal Exercise and Stability and Support Operations prototypes. Recent publications (2023) highlight his exploration of LLM-based emotion modeling , social influence dynamics in human-agent interactions, and ethical implications of AI assistants . Earlier work (2014-2015) established foundational frameworks for automated negotiation and rapport-building virtual agents . His methodological contributions include parasocial consensus sampling and appraisal theory-based emotion architectures. Scientific honors include Fellowships from AAAI, AAAC, and the Cognitive Science Society, the SIGART Autonomous Agents Award , and Senior Membership in IEEE . As founding Editor-in-Chief of IEEE Transactions on Affective Computing , he has significantly shaped the field's academic discourse. Gratch's virtual humans leverage immersive audio-visual environments (8'x30' screens, 10.2-channel audio) to study socio-emotional dynamics. His team's work demonstrates that anthropomorphism in machines can enhance interaction but may produce unintended consequences, informing design principles for effective human-machine collaboration.

• Software Metrics
• Model Driven Software Development
• Empirical Software Engineering
• +5 more

Miroslaw Staron is a Professor of Interaction Design and Software Engineering at Chalmers University of Technology. He maintains a unique 50/50 work arrangement, spending half his time on field research at Ericsson while holding his academic position. His research bridges academic theory with industrial practice through collaborations with major companies including Volvo Car Corporation and Volvo Information Technology. His research spans several key areas in software engineering: Software metrics and measurement systems in industry Model driven software development and empirical studies Defect prediction in software projects Requirements engineering in model-based development Applications of AI and machine learning in software engineering Automotive software development and security Staron's recent work demonstrates a strategic shift toward integrating AI technologies into software engineering processes, with particular focus on automotive applications. His publications from 2024-2025 reveal expertise in generative AI applications for code review automation, testing methodologies, and requirements engineering, showing how these technologies can transform traditional software development practices while addressing domain-specific challenges in automotive systems. Current research projects include: Kvantdatorer för framtidens mobilitetslösningar (2025-2027) Automatiserad och designoptimerad programvarukonstruktion/kodgenerering (2025-2029) Förvandla fordonsarkitektur med hjälp från AI (2021-2023) Arkitektonisk design och verifiering/validering av system med maskininlärning komponenter (2020-2024) With 78 publications documented in Chalmers' research database, Staron has established himself as a significant contributor to evidence-based software engineering research with strong industrial relevance.

Brenna ArgallView profile

Associate Professor

• Robotics
• Machine Learning
• Human-Robot Interaction
• +7 more

Brenna Argall is an Associate Professor at Northwestern University with joint appointments in the Departments of Computer Science, Mechanical Engineering, and Physical Medicine & Rehabilitation . She is also a Faculty Research Scientist at the Shirley Ryan AbilityLab , the nation’s premier rehabilitation hospital. Her research focuses on robotics autonomy, machine learning, and human rehabilitation , particularly in developing assistive and rehabilitation robotics that utilize shared control and interface-aware intelligence to enhance user autonomy. Education: Ph.D. in Robotics (2009), Carnegie Mellon University M.S. in Robotics (2006), Carnegie Mellon University B.S. in Mathematics (2002), Carnegie Mellon University Research Interests: Argall's work sits at the intersection of robotics, artificial intelligence, and rehabilitation . Key themes include trust-based control systems, dynamic autonomy allocation, and human-in-the-loop machine learning . Her lab, the Assistive & Rehabilitation Robotics Laboratory (argallab) , develops semi-autonomous wheelchairs, robotic arms, and adaptive control systems tailored to users’ physical and cognitive abilities. Projects emphasize customizable shared control, intent inference, and human-robot collaboration . Article Trends: Recent publications highlight advancements in shared autonomy, interface-aware robotics, and human-robot co-adaptation . Key areas include 7-DoF robot arm teleoperation, eye gaze tracking for control, high-dimensional body-machine interfaces, and trust-based dynamic control allocation , reflecting her lab’s focus on user-centric AI and rehabilitation technology . Scientific Awards: NSF CAREER Award (2016) Crain's Chicago Business 40 under 40 (2016) NSF Convergence Accelerator Phase 1 & 2 Awards (2022, 2024) AIMBE College of Fellows (2023) Office of Naval Research (ONR) Grant Advising & Grants: Argall advises students in the Masters of Science in Robotics program and has secured significant funding from NSF, NIH, and ONR for projects on self-driving wheelchairs, intent disambiguation, and trust-aware autonomy . Labs & Teams: As founder and director of the argallab , she leads a multidisciplinary team at the Shirley Ryan AbilityLab . The lab’s mission is to advance human ability through robotics autonomy , focusing on motor-impaired users and human-robot co-adaptation .

Luis SentisView profile

Professor

• Robotics
• Humanoid Robotics
• Autonomous Systems
• +7 more

Luis Sentis is a Professor in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin and holds the Frank and Kay Reese Endowed Professorship in Engineering . He leads the Human Centered Robotics Laboratory, focusing on control systems, human-robot interaction, and exoskeleton robotics. His affiliations include UT Austin's Good Systems initiative and Apptronik Systems as an innovation advisor. Ph.D. , Electrical Engineering, Stanford University B.S. , Telecommunications and Electronics Engineering, Polytechnic University of Catalonia His research spans humanoid robotics , agile manipulation , autonomous systems , and human-robot teaming . Recent work emphasizes FAIR datasets , EEG monitoring , and collision detection for legged robots, with applications in industrial automation and ethical AI. Scientific awards include the NASA Elite Team Award and La Caixa Foundation Fellowship . Funding sources include DARPA , NSF , NASA , and ONR .

• Software Engineering
• Model-Driven Engineering
• Automotive Embedded Systems
• +3 more

Vera Pantelic is an Adjunct Assistant Professor in the Department of Computing and Software at McMaster University. Her research focuses on software engineering practices for model-based development in automotive systems, particularly centralized Electrical/Electronic (E/E) architectures, Simulink modeling, and supervisory control of probabilistic discrete event systems. Education: Not explicitly mentioned in the text. Her scholarly activity includes extensive contributions to conferences and journals in automotive software engineering, model transformation, and real-time systems. Her work addresses challenges in modularity, documentation, and compliance within automotive embedded systems. Her recent publications emphasize advancements in centralized E/E architectures, model-driven testing, and assurance cases for automotive safety. She collaborates on topics integrating software engineering principles with automotive domain requirements. Scientific Awards: No specific awards mentioned in the text. She serves as an advisor in software engineering, though specific student names are not listed. Her projects involve simulation-based testing, model refactoring, and compliance frameworks, supported by industry partnerships and academic grants. Her work contributes to labs and teams focused on automotive software reliability and model-driven engineering. No explicit lab or team affiliations are detailed in the provided text.

Anne Elisabeth HaxthausenView profile

Associate Professor

• Formal methods
• Specification languages
• Semantics
• +6 more

Anne Elisabeth Haxthausen is an Associate Professor at the Software Systems Engineering section within DTU Compute , Technical University of Denmark . Her work focuses on formal methods, railway control systems, and safety-critical software engineering. Founder and leader of the DTU Railway Verification Group Member of European Technical Working Group on Formal Methods in Railway Control Editorial board member for Springer Formal Aspects of Computing Journal Active in the Overture Language Board Her research emphasizes formal verification of railway interlocking systems, particularly through compositional approaches and automated tools. She has contributed to projects like RobustRailS, Overture, and RAISE, focusing on model-based development and verification. She serves as a tutor for bachelor students and contributes to the advisory committee for DTU's Computer Science and Engineering MSc program. Her recent publications explore challenges in verifying autonomous and AI-driven railway technologies.

Markus ChristenView profile

Researcher

• empirical ethics
• neuroethics
• ICT ethics
• +5 more

Markus Christen is a researcher and Managing Director of the Digital Society Initiative at the University of Zurich, where he leads the Digital Ethics Lab within the Institute of Biomedical Ethics and History of Medicine. His work bridges empirical ethics, neuroethics, and ICT ethics with a focus on data analysis methodologies. Affiliation: University of Zurich (Faculty of Medicine) Role: Managing Director of the Digital Society Initiative Lab: Digital Ethics Lab Christen’s research explores ethical challenges in AI, cybersecurity, and digital health. He investigates value conflicts in technology design, moral sensitivity training through serious games, and human-AI accountability frameworks . His recent publications address digital twins in medicine , AI accessibility for disabled students , and cross-cultural responsibility gaps in AI systems. Key trends in his work include: Empirical ethics applied to AI and cybersecurity Neuroethical dimensions of technology Responsible AI integration in education and healthcare Data privacy and fairness in insurance Cross-cultural ethical assessments Christen’s lab develops frameworks for value-sensitive design and human-AI collaboration , with projects like "Responsible AI in practice" and "DSI AI-WEEK."

Liane ColonnaView profile

Assistant Professor

• AI Ethics
• Data Protection Law
• Algorithmic Regulation
• +2 more

Liane Colonna is an Assistant Professor in Law and Information Technology at the Department of Law, Stockholm University , where she investigates ethical and legal challenges arising from AI-driven practices in higher education. She also engages in methodologically oriented research at the intersection of AI and Law, contributing to the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society. Additionally, Liane serves as the director of the Swedish Law and Informatics Research Institute (IRI) and is a member of the New York Bar since 2008. Primary Affiliation: Department of Law, Stockholm University Institute Leadership: Director, Swedish Law and Informatics Research Institute (IRI) Professional Status: Member of the New York Bar Research Interests: Ethical and legal challenges of AI in higher education Methodological approaches in AI and Law Data protection and privacy by design Regulatory frameworks for AI and emerging technologies Privacy implications of lifelogging and health IoT International data governance and surveillance law Publications demonstrate expertise in AI regulation, GDPR compliance, and privacy-preserving technologies, particularly for assisted living and educational contexts. Her work bridges technical implementation with legal accountability, emphasizing human oversight and ethical design.

• Bio-inspired robotics
• Soft robotics
• Magnetic micro-robotics
• +1 more

Hamidreza Marvi is an Associate Professor in the School for Engineering of Matter, Transport and Energy at Arizona State University , with additional affiliations as a Senior Global Futures Scientist . His work bridges bio-inspired robotics , soft robotics , and mechanics of animal locomotion . Education : Ph.D. in Mechanical Engineering (Georgia Tech, 2013), M.S. in Biomedical Engineering (Sharif University, 2007), M.S. in Mechanical Engineering (Clemson, 2009), B.S. in Mechanical Engineering (Iran University of Science and Technology, 2004). Marvi’s research focuses on biological systems interacting with solid, granular, and fluidic environments , translating these insights into bio-inspired robotic systems for search-and-rescue, medical, and planetary exploration. His work has been featured in Science , PNAS , and popular media like the New York Times and BBC . Recent publications highlight trends in magnetic microrobotics , soft robot control , and locomotion in granular media , with applications in medical devices, underwater inspection, and space exploration. His BIRTH Lab develops programmable interfacial structures and adaptive locomotion systems. Scientific Awards : KEEN Professorship (2017), Peebles Award (2015), Sigma Xi Best Ph.D. Thesis (2014), TechSTAR Award (2012), Emerald Publishing Literati Network Award (2011). Marvi has supervised teams for NASA competitions, co-organized robotics workshops, and served as a reviewer for journals like Nature-Scientific Reports and conferences including IEEE-IROS. His teaching portfolio includes courses in system dynamics, robotic control, and applied projects .

• Control Systems
• Electric Vehicles
• Hybrid Electric Vehicles
• +4 more

Nikolce Murgovski is an Assistant Professor at Chalmers University of Technology, specializing in Mechatronics . He focuses on electric and hybrid vehicle energy management , autonomous driving systems , and optimization algorithms for powertrain design. His work bridges control theory , battery technology , and transport electrification . Current projects include CHARGE (2023–2026) for charging and trip planning , and EcoPilot (2022–2026) for energy-efficient autopilot development. Collaborates with institutions like Volvo Cars , Swedish Electromobility Centre , and VINNOVA on autonomous vehicle control and thermal energy systems . His recent publications emphasize convex optimization , eco-driving strategies , and collision avoidance in complex environments. He has contributed to tools like CONES for electromobility studies and has led research on hybrid powertrains and predictive energy management .

Pavel V. TsvetkovView profile

Professor

• Nuclear Engineering
• System Analysis & Optimization Methods
• Complex Engineered Systems
• +6 more

Professor Pavel V. Tsvetkov is a faculty member at Texas A&M University , holding the rank of Professor of Nuclear Engineering and serving as the Director of the Graduate Program in Nuclear Engineering . He is also an Affiliated Faculty member of the Multidisciplinary Engineering program . His office is located in the AIEN M205B building, and he can be contacted at tsvetkov@tamu.edu . Educational Background: Ph.D. in Nuclear Engineering, Texas A&M University (2002) M.S. in Theoretical & Experimental Reactor Physics, Moscow State Engineering Physics Institute (1995) Research Interests: Professor Tsvetkov's research spans a wide range of advanced nuclear engineering topics. His primary focus includes system analysis and optimization methods , complex engineered systems , and symbiotic nuclear energy systems . He is deeply involved in waste minimization and sustainability , particularly through the development of high-temperature gas-cooled reactors (HTGRs) and molten salt reactors (MSRs) . His work also explores direct nuclear energy conversion systems and the integration of AI and deep learning into nuclear reactor control and monitoring systems. Research Trends in Publications: Over the past few years, Professor Tsvetkov has published extensively on the application of machine learning and deep learning in nuclear engineering. His recent works focus on autonomous reactor control , reactor dynamics simulation , and remote monitoring systems using satellite data and AI. He has also contributed to the design and analysis of microreactors for space applications and molten salt reactor dynamics . Scientific Awards: George Armistead, Jr ’23 Faculty Excellence Teaching Award Advising and Grants: As Director of the Graduate Program in Nuclear Engineering, Professor Tsvetkov plays a key role in mentoring and advising graduate students. While specific student names are not listed, his leadership in the program and extensive research output suggest active involvement in student research and training. Labs and Teams: Professor Tsvetkov is associated with the Nuclear Power Engineering group at Texas A&M University, contributing to both academic and applied research in nuclear systems design and safety.