Find Academic Supervisors

• Machine Learning
• Artificial Intelligence
• Data Science
• +7 more

Pan Xu is a tenure-track assistant professor with joint appointments in the Department of Biostatistics & Bioinformatics, Department of Computer Science, and Department of Electrical & Computer Engineering at Duke University. Previously, Xu was a Postdoctoral Scholar Research Associate at Caltech's Department of Computing and Mathematical Science and earned a Ph.D. in Computer Science from UCLA. Xu's research focuses on developing computationally- and data-efficient machine learning algorithms with strong empirical performance and theoretical guarantees. Xu's research interests center around Machine Learning with broad applications in Artificial Intelligence, Data Science, Optimization, Reinforcement Learning, and High Dimensional Statistics. The research specifically targets real-world problems in Bioinformatics and Healthcare, with recent work emphasizing distributionally robust decision making, efficient exploration strategies, and multi-agent systems. Xu has developed novel algorithms that address the challenges of exploration in sequential decision making and robustness to distributional shifts between training and deployment environments. Xu's recent publications demonstrate a strong trend toward developing theoretically grounded yet practical algorithms for reinforcement learning and bandit problems, with particular emphasis on distributionally robust methods, efficient exploration techniques, and applications to healthcare. The work spans both theoretical analysis (providing minimax optimal regret bounds) and practical implementations (validated on benchmarks like Atari games and real healthcare datasets). Whitehead Scholar award from Duke University School of Medicine (2023) Best Paper Award at ACM FAccT 2023 for Queer In AI paper PIMCO Postdoctoral Fellowship in Data Science (2022) TMLR Featured Certification (2023) NSF award on approximate sampling based exploration (2023) Xu actively mentors multiple Ph.D. students across Duke's Biostatistics & Bioinformatics, Computer Science, and Electrical & Computer Engineering programs, with several alumni now pursuing doctoral studies at top institutions. The research group has secured competitive funding including an NSF award for approximate sampling based exploration for sequential decision making. Xu serves as an action editor for TMLR and as an area chair for major conferences including ICML, NeurIPS, AAAI, ICLR, and AISTATS. Xu leads a dynamic research group focused on sequential decision making, with projects spanning theoretical algorithm development, implementation of practical systems, and applications to healthcare and bioinformatics. The group maintains active collaborations across Duke's medical and engineering schools, with recent work applying machine learning to epidemic forecasting during the pandemic.

Saurabh AminView profile

Professor

• Infrastructure Resilience
• Cyber-Physical Systems Security
• Game Theory Applications
• +7 more

Saurabh Amin is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he also serves as the Edmund K. Turner Professor and Undergraduate Officer. He is a Principal Investigator at the Laboratory of Information and Decision Systems and holds affiliations with the Operations Research Center and the Center for Computational Science and Engineering. His educational background includes: B.Tech. 2002, Indian Institute of Technology (IIT) Roorkee M.S. 2004, University of Texas (UT) Austin Ph.D. 2011, University of California (UC) Berkeley Saurabh Amin's research focuses on the design and control of infrastructure systems using game theory and optimization in networks. His work spans three main areas: resilient network control, information systems and incentive design, and optimal resource allocation in large-scale infrastructure systems. By concentrating on critical infrastructure domains including highway transportation, electric power distribution, and urban water networks, his research develops innovative theory and tools to enhance system performance against both stochastic and adversarial disruptions. His approach involves modeling cyber-physical interactions in infrastructures to assess vulnerabilities, developing detection and response tools for failures at various scales, and designing economic incentive schemes that improve aggregate public good while accounting for dependencies and private information among strategic entities. Amin's work bridges mathematical systems theory with practical civil engineering applications, creating a rigorous theoretical foundation for infrastructure resilience that addresses diverse failure mechanisms from natural disasters to deliberate malicious actions. His recent publications demonstrate a strong focus on decarbonization of energy systems, resilient infrastructure planning under climate uncertainty, optimization methods for complex networked systems, and game-theoretic approaches to sustainable infrastructure management. His work increasingly integrates artificial intelligence and machine learning techniques with traditional control theory to address contemporary challenges in infrastructure resilience and sustainability. The research shows a clear trajectory toward addressing climate change impacts on infrastructure systems while maintaining economic efficiency and operational reliability. Professor Amin has received numerous prestigious awards and honors: Common Ground Excellence in Teaching Award, 2025 HSCC Test-of-Time Award, 2024 MIT CEE, Distinguished Service and Leadership Award, 2023 Samuel M. Seegal Prize (SoE) – inspiring students in pursuing and achieving excellence, 2022 Earll M. Murman for Excellence in Undergraduate Advising, 2022 C3.ai Digital Transformation Institute Research Award, 2020 MIT, Ole Madsen Mentoring Award, 2020 MIT, Energy Initiative Research Award, 2020 National Academy of Engineering, China-America Frontiers of Engineering Symposium speaker, 2019 MIT, Robert N. Noyce Career Development Professor, 2015-2018 Google Faculty Research Award, 2015 National Science Foundation CAREER Award, 2015 Siebel Energy Institute Research Award, 2015 MIT, Solomon Buchsbaum AT&T Research Fund Award, 2012 Professor Amin has been actively involved in significant research projects including the C3.ai DTI project on Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems and another on Learning in Routing Games for Sustainable Electromobility. He serves as the chief scientist on multi-institutional NSF grants, including the $9 million Foundations of Resilient Cyber-Physical Systems (CPS) project. His teaching portfolio includes courses such as 1.008 Engineering for a Sustainable World, 1.104 Sensing and Intelligent Systems, 1.020 Engineering Sustainability: Analysis and Design, and 1.208 Resilient Networks. As Undergraduate Officer, he plays a key role in shaping the educational experience for civil and environmental engineering students at MIT. Professor Amin leads the Resilient Infrastructure Networks Lab at MIT, where his team develops theoretical foundations and practical tools for infrastructure resilience. The lab focuses on the intersection of control theory, game theory, and optimization applied to cyber-physical infrastructure systems. Current research directions include pandemic-resilient urban mobility and hurricane-resilient smart grid operations, reflecting the lab's commitment to addressing pressing societal challenges through rigorous systems engineering approaches.

Robert ÖstlingView profile

Professor

• Applied Microeconomics
• Behavioral Economics
• Political Economy
• +4 more

Robert Östling is a Professor of Economics at the Stockholm School of Economics (SSE), affiliated with the Department of Economics and the Karl-Adam Bonnier Center for Governance within the House of Governance and Public Policy. He holds a PhD from SSE (2008) and previously worked at Stockholm University's Institute for International Economic Studies until 2018. His research focuses on applied microeconomics and behavioral economics, particularly examining how wealth impacts attitudes, behavior, and life outcomes using Swedish lottery data. He teaches econometrics, behavioral economics, and economics for MBA students, and serves as program director for SSE's MSc in Economics. Key roles include board membership of the Swedish Economics Association and the Expert Group on Public Economics (ESO), and membership in the scientific advisory board of the Swedish Consumer Protection Agency. He co-founded the popular economics blog Ekonomistas , recognized as 'Swede of the Year' in 2017. Awards include the Assar Lindbeck Medal (2021) and the Arnberg Prize (2009). His research spans wealth effects on labor supply, health, child development, and political behavior. Notable projects include studying lottery winners' long-term well-being and portfolio decisions. Teaching innovations include using animated GIFs for econometrics instruction. He has contributed to policy debates on economic reforms, consumer protection, and pandemic responses. Outreach activities include public writing and policy advisory roles. His research has been featured in outlets like the New York Times and Swedish media. He remains active in academic networks, including the Network for Evidence-Based Policy.

Peter FredrikssonView profile

Professor

• Labor Economics
• Economics of Education
• Policy Evaluation
• +3 more

Peter Fredriksson is a Professor at the Department of Economics, Uppsala University. He serves on the Nobel Committee for the Prize in Economic Sciences (Chair 2019-2021) and is affiliated with institutions like the Rockwool Foundation, IZA, CESifo, UCLS, and IFAU. His work spans labor economics, education economics, and policy evaluation. Research Focus : Labor economics, education economics, and policy evaluation Affiliations : Uppsala University, Rockwool Foundation, IZA, CESifo, UCLS, IFAU Research Interests center on labor economics, particularly unemployment insurance, class size effects, peer influences, and policy impacts. His work connects wage dynamics, educational outcomes, and public program evaluations. He explores non-cognitive skills' rising importance and gender pay disparities. Recent Publications (2025-2013) address topics like job mobility, layoff policies, child development, and global poverty. Key journals include Quarterly Journal of Economics , American Economic Review , and Journal of Human Resources . Scientific Awards & Roles : Member of the Royal Swedish Academy of Science Chair of the Nobel Committee for Economic Sciences (2019-2021) Research Fellow at IZA and CESifo Affiliated with Uppsala Center for Labor Studies and IFAU Associate Editor at Scandinavian Journal of Economics Collaborations include the Rockwool Foundation's program committees and extensive work with Björn Öckert, Per-Anders Edin, and Hessel Oosterbeek.

Sven BölteView profile

Professor

• Autism Spectrum Disorder
• ADHD
• Neurodevelopmental Disorders
• +6 more

Sven Bölte is a Professor at Karolinska Institutet where he leads the research group focused on Autism, ADHD and other developmental neurological conditions as part of the Center for Neurodevelopmental Disorders (KIND). His work bridges clinical research, education, and practical implementation of evidence-based approaches for neurodevelopmental conditions. Professor Bölte's research spans multiple domains within neurodevelopmental disorders, with particular emphasis on implementing the International Classification of Functioning, Disability and Health (ICF) Core Sets for autism and ADHD using digital solutions. His group has developed and evaluated social skills training programs (KONTAKT, SKOLKONTAKT, iKONTAKT) for autistic children and adolescents, conducted twin research through the Roots of Autism and ADHD Twin Study in Sweden (RATSS), and advanced diagnostic instruments for autism, ADHD, social cognition, and adaptive behavior. His recent publications reveal a strong focus on translating research into practice, with significant work on strengths-based approaches, social inclusion, neurodiversity-affirmative assessment, and the development of practical tools for clinicians and educators. The research demonstrates increasing attention to adult experiences of autism, cross-cultural validation of interventions, and the integration of digital technology in assessment and intervention. Bölte's group also delivers extensive educational components for professionals through KI-Utbildning (Assignment Education), making it one of the largest providers of training on diagnosis and support for individuals with developmental neurological conditions within Karolinska Institutet. His work frequently addresses policy implications, as evidenced by participation in Swedish parliamentary discussions about autism and ADHD.

• Control Technology
• Distributed Optimization
• Machine Learning
• +4 more

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

Nir PitermanView profile

Professor

• formal verification
• automata theory
• model checking
• +4 more

Nir Piterman is a Professor in Computer Science at the University of Gothenburg's Department of Computer Science and Engineering. Previously, he was a Lecturer and later Reader (Associate Professor) at the University of Leicester (2010-2019), following postdoctoral research at EPFL (2005-2007) and a Research Fellowship at Imperial College London (2007-2010). PhD from Weizmann Institute of Science (2005), supervised by Amir Pnueli Postdoc at EPFL with Tom Henzinger (2005-2007) Research Fellow at Imperial College London (2007-2010) Lecturer at University of Leicester (2010-2019), promoted to Reader in 2012 Universitets Lektor (Associate Professor) at University of Gothenburg (2019-2021), promoted to Professor in 2021 His research focuses on formal verification, automata theory, and synthesis from temporal specifications. Current work under the ERC Consolidator Project dSynMA extends reactive synthesis to multi-agent systems, exploring frameworks combining message passing and variable sharing, algorithmic analysis of games with partial information, and logic extensions for agent interaction. He has supervised eight PhD students, including Prabhat Kumar Jha (path planning in game solving), David Lidell (automata constructions for LTL with past), and Claudia Cauli (cloud infrastructure security reasoning, 2022), with theses covering program verification, temporal logic, and game algorithms. ERC Consolidator Grant (2021-?, dSynMA) Editor-in-Chief, Formal Methods in System Design Editor, Acta Informatica Nir has taught courses such as Principles of Concurrent Programming (Chalmers, 2019-2025), Advanced C++ Programming (University of Leicester, 2012-2017), and Synthesis from Temporal Specifications (University of Buenos Aires, 2010). He actively recruits PhD candidates and has hosted postdoctoral researchers at multiple institutions.

Anna GautierView profile

Assistant Professor

• Multi-Agent Systems
• Robotics
• Artificial Intelligence
• +3 more

Anna Gautier is an Assistant Professor in the Department of Computer Science at Chalmers University of Technology, affiliated with the Division of Data Science and AI. Previously, she was a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology (2023–2025), focusing on mechanism design for multi-robot systems. Her research emphasizes planning under uncertainty, multi-agent systems, and human-robot interaction. She holds a PhD from the University of Oxford (2023), an MSc from the London School of Economics, and dual undergraduate degrees from Washington University in St. Louis. Education Background: PhD in Computer Science, University of Oxford (2023) MSc in Applied Mathematics, London School of Economics BA in Mathematics and BS in Computer Science, Washington University in St. Louis Research Interests: Dr. Gautier explores planning algorithms for multi-agent systems, particularly in uncertain environments. She designs mechanisms to coordinate robots and humans, leveraging game theory and formal methods. Her work addresses challenges like resource allocation, risk-aware decision-making, and trust in autonomous systems. Recent projects include contingency planning for autonomous vehicles and auction-based resource distribution. Professional Activities: She co-chairs the ECAI 2025 Demonstration Track and teaches the course Safe Robot Planning and Control at KTH. Her projects include collaborations with WASP-Nest (PerCorSo) and TECoSA on trustworthy autonomy. She actively publishes in top venues like AAMAS and AAAI. Labs and Teams: Affiliated with Chalmers' Data Science and AI division, she leads research in multi-agent systems and human-AI collaboration.

• Control Theory
• Distributed Control
• Networked Systems
• +12 more

Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University, Sweden. She joined the department in January 2021 and holds a prestigious WASP (Wallenberg AI, Autonomous Systems and Software Program) professorship. Her research focuses on the analysis and control of large-scale networked systems, with applications in distributed electric power networks and socio-epidemiological networks. She is actively involved in multiple research projects, supervises several PhD students, and contributes to major academic events in control theory. Education: Ph.D. in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013) B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2011) Emma Tegling's research centers on the fundamental limitations of distributed control, particularly in large-scale and non-normal network systems. Her work addresses critical challenges in vehicular formations, power grids, and social networks. She develops scalable control designs, consensus protocols, and optimal control strategies for complex networked environments. Her recent publications highlight breakthroughs in string stability, transient performance, and distributed optimization. The trend in her articles shows a strong focus on mathematical control theory, network dynamics, and real-world applications in socio-technical systems. Scientific Awards: WASP professorship (Wallenberg AI, Autonomous Systems and Software Program) Emma Tegling leads and co-leads several significant research grants, including WASP NEST: Learning in Networks and Dynamics of Complex Socio-Technological Network Systems. She actively supervises PhD students such as Jonas Hansson and David Ohlin, whose work has led to novel consensus protocols and optimal control formulations. Her academic leadership extends to organizing the European Control Conference and co-organizing interdisciplinary workshops on power and democracy in modern societies. She is also involved in public engagement and academic service through supervision and project coordination. Emma Tegling is a key member of the Department of Automatic Control at Lund University, contributing to research teams focused on networked systems, control theory, and AI integration. She collaborates extensively within ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and participates in cross-disciplinary labs working on AI, digitalization, and natural/artificial cognition. Her work is aligned with UN Sustainable Development Goals related to sustainable energy and resilient infrastructure.

• AI
• Digitalisation
• Higher education
• +9 more

Jimmy Jaldemark is a Professor at the Department of Education, Mid Sweden University, Sundsvall, Sweden. He serves as Research Leader of HEEL (Higher Education and E-Learning) and Head of Subject for the Discipline of Education. His roles include membership in the Faculty Board of Humanities and representation in the university-wide Education Council. He co-founded GRADE, a national graduate school in digital education, and leads the EARLI Centre for Excellence in AI in Learning and Instruction (AILI). His research focuses on AI, digitalization, lifelong learning, and networked learning. He co-edited *Networked Professional Learning* (2019) and guest-edited special issues in the *British Journal of Educational Technology*. He is an editor for that journal and serves on editorial boards for *Educational Research Review*, *Postdigital Science and Education*, and others. He supervises doctoral students and teaches in Behavioral Science and Education programs. Current projects include HEaD (Higher Education and Digitization) and BLAD (Need-based Learning through Adapted Participation). He collaborates internationally, notably in the AILI network exploring AI's educational impacts. His work spans educational development, organizational learning, and policy frameworks for lifelong learning in the digital era.

• Information Theory
• Privacy (Data Disclosure)
• Statistical Signal Processing
• +4 more

Tobias Oechtering is a Professor at the Division of Information Science and Engineering within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. His research focuses on information theory, privacy-preserving technologies, statistical signal processing, machine learning, and smart grid systems. He has held academic positions at KTH since 2008, advancing from Post-Doctoral Researcher to Assistant Professor (2010–2013), Associate Professor (2013–2018), and Professor (2018-present). He has supervised over 20 PhD students and contributed to numerous postdoctoral programs. Research Interests: - Network information theory and physical-layer security - Privacy mechanisms with provable guarantees - Distributed statistical inference and sensor calibration - Reinforcement learning and privacy-aware machine learning - Smart grid privacy and energy management - Wireless communication algorithms and signal processing - Networked control systems and stability analysis He currently supervises 7 PhD students and hosts 3 postdocs. His work has led to over 150 peer-reviewed publications, with recent contributions in privacy-preserving smart grid strategies, adversarial inference control, and information-theoretic security. He has served as editor for IEEE Transactions on Information Forensics and Security and held leadership roles in KTH's Digitalisation Research Platform.

Dilian GurovView profile

Professor

• Software Specification and Verification
• Multi-Agent Strategic Planning
• Formal Methods
• +3 more

Dilian Gurov is a Professor in Computer Science at KTH Royal Institute of Technology, associated with the Digital Futures Faculty and the Division of Theoretical Computer Science. He also coordinates the Doctoral Programme in Computer Science at the CSC school. Before joining KTH in 2002, he earned a Ph.D. from the University of Victoria, Canada (1998), and worked at the Swedish Institute of Computer Science (1997-2002). His research focuses on software specification and verification, including contracts, program models, logics, and tools, as well as multi-agent strategic planning involving knowledge-based strategies in imperfect information settings. Key contributions include the CAV Distinguished Paper Award 2023 for 'Automatic Program Instrumentation for Automatic Verification' and an EASST award for 'Checking Absence of Illicit Applet Interactions: A Case Study' (2004). He leads projects funded by VR (SEFROS, ContraST) and Vinnova (AVerT2) and collaborates with industries like Scania on formal verification of C programs. His service roles span over 30 conference committees and organization roles, including PC memberships for iFM, TAP, and ISoLA. Teaching responsibilities include courses such as 'Formal Methods,' 'Program Semantics and Analysis,' and 'Knowledge in Games with Imperfect Information.' His work emphasizes practical applications of formal methods, bridging academic research with industry needs through collaborations and tool development (e.g., CVPP, ProMoVer, TriCo).

Gerardo SchneiderView profile

Professor

• Formal Specification and Analysis of Contracts
• Formalization of Privacy Policies
• Model Checking
• +5 more

Gerardo Schneider is a Full Professor in Computer Science at the University of Gothenburg, Sweden, and holds a joint appointment at Chalmers University of Technology. He serves as Head of the Data Science and Artificial Intelligence (DSAI) Division and has previously led the Formal Methods Division and acted as Director of Graduate Studies. University of Gothenburg: 2009–present Chalmers University of Technology: 2009–present Uppsala University: 2002–2003 University of Oslo: 2005–2009 His research focuses on formal methods for software engineering, including contract specification and analysis , privacy policy formalization , model checking , and runtime verification . He works on verification of real-time systems, embedded systems (e.g., smart Java cards), and blockchain-based smart contracts. Key projects include: X-LEGAL (2020–2023): Smart Legal Contracts (Swedish Research Council) PolUser (2016–2019): User-Controlled Privacy Policies (Swedish Research Council) ARVI (2014–2018): Runtime Verification Beyond Monitoring (ICT COST Action) ReMU (2013–2017): Reliable Multilingual Digital Communication (Swedish Research Council) He has supervised numerous PhD and Master’s students in formal methods, blockchain security, and privacy compliance. His tools include SPeeDI (Polygonal Hybrid Systems Verification), CLAN (Contract Normative Conflict Detection), and AnaCon (Controlled Natural Language Analysis).

Ulf MellströmView profile

Professor

• Gender Studies
• Science and Technology Studies (STS)
• Masculinity Studies
• +4 more

Ulf Mellström is a Professor in Gender Studies at Karlstad University, Sweden. He holds a PhD from Linköping University (1995) and has held academic positions at Linköping University (1995-2009), Luleå University of Technology (2005-2011), and Karlstad University since 2011. His research focuses on gender and technology studies, masculinity studies, globalization, and higher education. Key areas include the political economy of global knowledge production, gendered professions in STEM, and the intersection of technology, risk, and security. Education: PhD in Technology and Social Change (1995), Linköping University. Major research projects include investigations into globalized eduscapes, corporate universities in Dubai/India/Brazil, and gender mainstreaming in Swedish rescue services. He collaborates internationally, serving on boards such as MSB's Scientific Board and the Norwegian Research Council's gender studies program. Research interests span ethnographically grounded studies of gendered knowledge production, global comparative perspectives on STEM fields (e.g., Malaysia's female-dominated computer science), and the cultural embeddedness of technology use. He has supervised multiple PhD students and teaches courses in gender studies, ethnographic methodology, and STS. Publications include influential works like Masculinity, Power and Technology: A Malaysian Ethnography (2003), and articles in journals such as Science, Technology & Human Values and International Journal of Gender, Science, and Technology . His recent work explores posthumanist masculinity, autonomous vehicles, and transnational bachelorhood.

• Game Theory
• Control Theory
• Cybersecurity
• +5 more

Kim Hammar is a postdoctoral researcher at KTH Royal Institute of Technology, with affiliations at the University of Melbourne (2025-2028) and Imperial College London. He works under Prof. Tansu Alpcan and Prof. Emil Lupu, focusing on the intersection of game theory, control theory, and large-scale systems for networking and security applications. Previously, he completed his Ph.D. at KTH under Prof. Rolf Stadler and Prof. Pontus Johnson. His research spans cybersecurity, networked systems, and adaptive control mechanisms. Key contributions include applying optimal stopping reinforcement learning conjectural online learning causal modeling to intrusion response and network security. His 2025-2024 publications highlight advancements in automated security through game-theoretic and control-theoretic approaches, with a focus on dynamic environments. Kim received the VR International Postdoctoral Fellowship in 2025. He has served as an assistant for Computer Networks (EP111U) Computer Systems (EP121U) at KTH.