Find Academic Supervisors

• Renewable Energy
• Energy Storage Systems
• Thermal Power Generation
• +3 more

Rafael Guedez Mata is a Researcher at the Energy Department of KTH Royal Institute of Technology , specializing in techno-economic modeling for energy conversion and storage technologies. He holds a PhD from KTH and completed an executive program in Management and Leadership at MIT Sloan. His research focuses on optimizing solar power plants, thermal energy storage, and supercritical CO₂ systems, with projects funded by the EU, Swedish Energy Agency, and industry partners. As a Principal Investigator (PI), he leads high-impact projects such as SOLARSCO2OL and SHARP-sCO₂, advancing hybrid solar and supercritical CO₂ technologies. He has supervised over 60 MSc theses and received the PhD Supervisor of the Year 2021 award. He teaches courses like Large Scale Solar Power (MJ2500) and Energy Storage Technology (MJ2386) , and is Deputy Director of the Sustainable Energy Engineering MSc program. His professional roles extend beyond academia: he co-founded Europe Power Solutions , advises firms like Naventus Corporate Finance and Odqa Renewable Energy Technologies , and previously worked at SolarReserve and Total’s Solar Energy division. His work bridges academia and industry, emphasizing sustainable energy solutions. Key technical contributions include optimizing hybrid solar-PV plants, power-to-ammonia systems, and thermal storage integration. His publications (80+ papers) address system design, economic modeling, and climate resilience. Current projects include decarbonizing industrial sectors via power-to-heat systems and assessing environmental impacts of stationary batteries.

• Wireless Communications
• Mobile Communication Systems
• mm-wave/sub-THz Communication
• +6 more

Tommy Svensson is a Professor of Communication Systems at Chalmers University of Technology, where he leads research on wireless systems on air interface and wireless backhaul network technologies. He received his Ph.D. in information theory from Chalmers in 2003 and has extensive industry experience from Ericsson AB, working with core, radio access and microwave networks. His primary research interests include: Design and analysis of mobile communication systems Physical storage algorithms Multi-user access and resource allocation Cooperative/context-aware/secure communication mm-wave/sub-THz communication C-V2X and JCAS Satellite networks Sustainable design and comprehensive architecture Professor Svensson has been actively involved in numerous European research projects including WINNER I/II/+, ARTIST4G (contributing to 3GPP LTE standards), METIS, mmMAGIC, and 5GCar (towards 5G), and Hexa-X, RISE-6G, SEMANTIC, ROBUST-6G, and ECO-eNET (towards 6G). He also contributes to the Chase/ChaseOn and WiTECH antenna systems center of excellence at Chalmers, focusing on mm-wave and (sub)-THz solutions for various wireless scenarios. His publication record is extensive, with 6 books, 111 journal papers, 151 conference papers, and 80 public EU project deliverables to his name. Professionally, he serves as: Founding member/editor of the IEEE JSAC Series on Machine Learning in Communications and Networks Chair of the award-winning IEEE Sweden Vehicular Technology/Communications/Information Theory Societies chapter Editor of IEEE Transactions on Wireless Communications and IEEE Wireless Communications Letters Lead local organizer of EuCNC & 6G Summit 2023 Coordinator of the Communication Engineering Master's Program at Chalmers

• Ergonomics
• Digital Human Modeling
• Manufacturing Systems
• +5 more

Lars Hanson is a Professor of Product Design Engineering at the University of Skövde's School of Engineering Science. His research focuses on ergonomics, digital human modeling, and optimizing manufacturing systems with a strong emphasis on human well-being and sustainable production. He leads projects like LITMUS (Industry 4.0 to 5.0 transition) and has contributed to developing tools such as IPS IMMA for ergonomic simulations. Active in virtual verification of human-robot collaboration and smart textile systems for workplace safety Published extensively in journals like International Journal of Human Factors Modelling and Simulation and IEEE Access Editor of conference proceedings and contributor to industry standards in automotive and healthcare sectors Research interests include multi-objective optimization of factory layouts, musculoskeletal risk assessment, and integrating ergonomic evaluations into product design processes. Current projects address Industry 5.0 sustainability challenges through digital twin technologies and smart manufacturing solutions.

Alexander HollbergView profile

Associate Professor

• Sustainable Design
• Optimization Processes
• Stakeholder Interaction
• +4 more

Alexander Hollberg is an Associate Professor in the Division of Building Technology at Chalmers University of Technology, within the School of Architecture and Civil Engineering. His academic role focuses on Computational Sustainable Design, emphasizing the development of digital tools for sustainable building and urban design. He holds a PhD in Parametric Life Cycle Assessment (2016) from Bauhaus University Weimar, an MSc in Architectural Engineering (2011), and a BSc in Civil Engineering (2008) from Technical University of Munich (TUM). His research interests include Sustainable Design Optimization, Stakeholder Interaction, Artificial Intelligence, and Life Cycle Assessment (LCA). He co-founded CAALA, a software and consulting startup in Munich, Germany, advancing tools for real-time environmental performance evaluation in early design stages. Recent work includes studies on digital twins for urban planning, robust renovation strategies, and AI-driven facade optimization. Hollberg was promoted to Docent (Associate Professor) in Computational Sustainable Design in 2022, focusing on bridging computational methods with sustainable environmental transitions. His collaborative projects address tool development for stakeholder engagement, BIM integration, and circular economy frameworks in construction. Key Projects: Development of Bombyx and Twinable tools for real-time LCA and urban simulation Leading the Nordic Build-LCA PhD forum and BIM-based LCSA applications Contributions to IEA EBC Annex 72 guidelines on life cycle environmental impacts Education Background: PhD in Parametric Life Cycle Assessment, Bauhaus University Weimar, 2016 MSc in Architectural Engineering, Bauhaus University Weimar, 2011 BSc in Civil Engineering, Technical University of Munich, 2008 His research outputs prioritize early design-stage decision support through parametric modeling and AI, with a focus on carbon neutrality and material circularity in construction.

• 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.

Gurjot SinghView profile

Research Fellow

• Cybersecurity
• Aviation Network Security
• Secure Communications
• +3 more

Gurjot Singh is a Research Fellow at the Department of Computer and Information Science (IDA) at Linköping University, Sweden. His research focuses on cybersecurity in aviation systems, next-generation communication networks, and industrial IoT security. He collaborates with prominent researchers like Andrei Gurtov and Suleman Khan, contributing to projects such as SEC-AIRSPACE and Post Quantum Secure Handover Mechanisms. His work spans vulnerability assessments, secure protocol design, and post-quantum cryptography applications. Education details are not explicitly stated, but his research aligns with advanced cybersecurity and network engineering domains. Key research interests include aviation cyber risk assessment, secure data link communications, and privacy-preserving authentication mechanisms for IoT and industrial environments. Publications emphasize cybersecurity challenges in aviation, industrial networks, and IoT, with recent work addressing quantum-resistant protocols and drone remote identification security. Collaborations include contributions to conferences like NordSec and AIAA DATC. He is affiliated with the cybersecurity lab at LiU, supporting educational programs like Digital4Business, which integrates AI and cybersecurity expertise. His role in the Database and Information Techniques (ADIT) division highlights involvement in interdisciplinary research groups.

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.

David T. RobinsonView profile

Professor

• Private Equity
• Venture Capital
• Entrepreneurial Finance
• +6 more

David T. Robinson is the James and Gail Vander Weide Distinguished Professor at Duke University’s Fuqua School of Business, serving as Research Director of Duke's Innovation and Entrepreneurship Initiative. He holds an honorary doctorate from the Stockholm School of Economics and is a Research Associate at the National Bureau of Economic Research (NBER). His academic journey includes a PhD and MBA from the University of Chicago, an M.S. from the London School of Economics, and a B.A. from the University of North Carolina at Chapel Hill. His research focuses on private equity, venture capital, entrepreneurial finance, and the intersections of innovation, climate policy, and financial literacy. Key contributions include analyses of racial disparities in entrepreneurship financing, the environmental impacts of credit policies, and the governance of strategic alliances. Robinson has advised entities like the Swedish House of Finance and the Private Equity Research Council. Education: PhD & MBA, University of Chicago (2001) MSc, London School of Economics (1993) BA, University of North Carolina at Chapel Hill (1992) Honorary Doctorate, Stockholm School of Economics Professional Roles: Current: Core Faculty in Innovation & Entrepreneurship at Duke Past: Professor of Finance at Columbia University Visiting Professorships at SSE (Stockholm School of Economics) His recent publications explore topics such as minority entrepreneurship barriers, liquidity dynamics in private equity, and the environmental costs of easy credit. He has secured grants from institutions like the National Science Foundation and the Ewing Marion Kauffman Foundation.

• Wireless Communications
• Signal Processing
• Massive MIMO
• +3 more

Nikolaos Kolomvakis is a researcher in the Division of Communication Systems at KTH Royal Institute of Technology in Sweden. He is also a visiting researcher at Ericsson AB in Stockholm. Previously, from 2017 to 2023, he held positions as Systems Engineer and Senior Researcher at Ericsson. His research focuses on wireless communications and signal processing, particularly on developing baseband physical-layer algorithms for distributed/cell-free massive MIMO, holographic MIMO, and large intelligent surfaces. Education: Ph.D. in wireless communications from Chalmers University of Technology , supervised by Prof. Mats Viberg with co-supervision from Prof. Thomas Eriksson and Prof. Michail Matthaiou M.Sc. in information technology & electrical engineering from ETH Zurich (2012) Research Interests: Wireless communications Signal processing Distributed/cell-free massive MIMO Holographic MIMO Large intelligent surfaces Publications: Recent work includes analyzing nonlinear distortion in large arrays and active reconfigurable intelligent surfaces (2025) Exploring spatial frequencies in near-field communications (2025) Investigating 6G performance through gigantic MIMO (2025)

• Thermodynamics
• Diffusion
• Phase Transformations
• +3 more

Powder Metallurgy (MH2100) and has expertise in computational materials science. His research emphasizes predictive modeling of material behavior, including precipitation kinetics, sintering processes, and coating interactions. Notable areas include phase field modeling of discontinuous precipitation, spinodal decomposition in Fe-Cr alloys, and high-entropy alloy design. His studies bridge experimental data with computational tools like the YAPFI phase-field framework. Key themes in his publications span cemented carbides, Co-based entropic alloys, and tool wear mechanisms. He combines CALPHAD thermodynamic modeling with first-principles calculations to address challenges in materials processing and corrosion resistance. His work often addresses industrial applications, such as optimizing machining tools and additive-manufactured superalloys.

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.

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.

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +3 more

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

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.