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Per KrusellView profile

Professor

• Macroeconomics
• Inequality
• Climate Economics
• +5 more

Per Krusell is Professor of Economics at Stockholm University and holds the Torsten and Ragnar Söderberg Chair at the Institute for International Economic Studies (IIES). He is a Fellow of the Econometric Society and served as President of the European Economic Association in 2020. He is currently the Secretary of the Prize Committee for the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. Education: PhD in Economics, University of Minnesota Research Interests: Per Krusell’s research spans macroeconomics , inequality , climate economics , labor markets , and political economy . He has made foundational contributions to understanding incomplete markets, wealth distribution, optimal taxation, and the macroeconomic effects of climate change. His work often integrates dynamic stochastic general equilibrium (DSGE) models with heterogeneous agents to study long-run outcomes and policy impacts. Publications Trend: His recent publications (2022–2025) reflect a strong focus on climate policy , integrated assessment modeling , and macro-labor dynamics . Key themes include carbon taxation, labor supply responses to productivity growth, fiscal multipliers in heterogeneous-agent settings, and the macroeconomic consequences of vaccination and epidemic control. Awards & Honors: Fellow of the Econometric Society Torsten and Ragnar Söderberg Chair in Economics President, European Economic Association (2020) Secretary, Nobel Prize Committee in Economic Sciences Advising & Grants: While specific student names are not listed, his leadership roles in global economic associations and policy committees indicate extensive academic advising and grant involvement in macroeconomic policy and climate economics. Labs & Teams: He is affiliated with the Institute for International Economic Studies (IIES) at Stockholm University, a leading research institute in macroeconomics and international economics.

Lisbeth AggestamView profile

Associate Professor

• Foreign Policy Analysis
• International Politics
• Political Leadership
• +4 more

Lisbeth Aggestam is an associate professor at the Department of Political Science and an associate researcher at the Center for European Research (CERGU) at the University of Gothenburg. She serves as the editor-in-chief of the international journal Foreign Policy Analysis , published by the International Studies Association (ISA) and Oxford University Press. Aggestam's research focuses on several interconnected areas: Political leadership and foreign policy Diaspora and foreign policy Foreign policy role theory The European Union as a global actor Her scholarly work demonstrates a consistent focus on leadership dynamics within European foreign policy, particularly examining how the EU navigates its role as a global actor amid shifting geopolitical landscapes. She has developed significant theoretical contributions to role theory in foreign policy analysis, creating frameworks for understanding how states and international organizations perform specific roles on the global stage. Aggestam's publication record reveals several important trends in contemporary foreign policy studies. Her work increasingly examines the intersection of domestic politics and international relations, particularly how diaspora communities influence state foreign policies. Her recent research addresses European strategic autonomy in the context of US foreign policy shifts and the implications of Sweden's NATO membership decision, reflecting her ability to connect theoretical frameworks with pressing real-world issues. As an educator, Aggestam serves as course manager and instructor for several key programs: EU2215: Europe in the World (MA, 15 hec) SK1136: Foreign Policy Analysis (BA, 7.5 hec) EU1145: The European Union in International Affairs (BA, 7.5 hec) Through her leadership of the Swedish Research Council project 'Transnational civil society and foreign policy' (2022-2025) and her editorial role at Foreign Policy Analysis , Aggestam plays a significant role in shaping contemporary discourse on international relations and European foreign policy.

• Phonetics
• Conversation Analysis
• Prosody
• +5 more

Mattias Heldner is Professor of Phonetics and Head of Department at the Department of Linguistics, Stockholm University. He also serves as Director of the Phonetics Laboratory where he has developed advanced recording facilities for breathing movements and voice quality dynamics in conversation. Dr. Heldner received his PhD in Phonetics from Umeå University in 2002, completed a postdoc at TeliaSonera Sweden in 2005, became Docent in Speech Communication at KTH Royal Institute of Technology in 2007, and was appointed Professor in Phonetics at Stockholm University in 2011. His research focuses on communicative behavior relevant for turn-taking in conversation and signaling of prosodic functions such as prominence and boundaries. His work spans multiple dimensions of speech communication, including: Respiratory patterns and their role in conversation flow Voice quality dynamics as turn-taking cues Prosodic functions in spontaneous speech Physiological constraints in verbal communication Acoustic properties of child speech development Neural correlates of lexical stress Dr. Heldner's recent publications demonstrate how respiratory signals provide crucial information for predicting speech activity and managing turn-taking. His research combines physiological measurements with acoustic analysis to uncover hidden aspects of conversational organization, particularly the relationship between breathing patterns and speech timing. As an educator, Dr. Heldner has taught phonetics courses for Speech and Language Pathology students at Karolinska Institutet, University of Gothenburg, and Umeå University. He currently supervises one PhD student and has successfully supervised two PhD theses to completion. Dr. Heldner has held several Swedish research grants and served as one of the Technical Program Chairs for Interspeech 2017 in Stockholm. His Phonetics Laboratory has developed innovative systems like RespTrack for measuring respiratory movements during speech with high experimental control.

Pierre FlenerView profile

Professor

• Artificial Intelligence
• Constraint Programming
• Discrete Optimization
• +5 more

Pierre Flener is a Professor at the Department of Information Technology, Division of Computing Science at Uppsala University. He leads the Optimisation Group and is a member of the Centre for Interdisciplinary Mathematics. His work focuses on constraint programming and discrete optimization, addressing complex scheduling, routing, and resource allocation challenges. Flener is an Officer of the Order of Merit of Luxembourg and co-founder of NordConsNet, the Nordic Network for Constraint Programming researchers. Research Interests: Flener’s research spans constraint programming, combinatorial optimization, and algorithm design. He develops models and tools for automated decision-making in domains like air traffic management, sensor networks, and industrial robotics. His work emphasizes practical applications, leveraging constraint satisfaction techniques to solve real-world puzzles such as vehicle routing and personnel allocation. Key Contributions: Flener has authored over 100 publications on constraint solving, symmetry breaking, and CP-based approaches to industrial problems. Notable projects include airspace sectorization optimization, energy-efficient sensor networks, and financial portfolio design. He has led initiatives like Auto-Tabling for MiniZinc and collaborated on CP applications in bioinformatics and image processing. Labs & Teams: He heads the Optimisation Group at Uppsala, fostering research in CP and its applications. NordConsNet, co-founded by Flener, connects Nordic researchers and practitioners in constraint technology.

• 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.

• Mathematical Finance
• Probability Theory
• Stochastic Analysis
• +5 more

Sigrid Källblad Nordin is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Department of Mathematics (Division of Probability, Mathematical Physics, and Statistics). Her research focuses on Mathematical Finance, Probability Theory, and Stochastic Analysis, with an emphasis on measure-valued processes, martingale optimal transport, and model uncertainty. She holds a DPhil from the University of Oxford (2014). Her work bridges theoretical advancements in stochastic control, optimization, and financial applications. Recent research includes Bayesian optimal adaptive control, robust option pricing, and dynamically consistent investment strategies under uncertainty. She teaches courses such as Financial Mathematics and Financial Derivatives, and supervises PhD students Linn Engström and Chaorui Wang. Publications span journals like Annals of Applied Probability , Finance and Stochastics , and SIAM Journal on Control and Optimization , reflecting contributions to optimal transport, stochastic processes, and financial modeling. She is currently hiring a new PhD student and welcomes inquiries about master thesis supervision.

Elina RönnbergView profile

Professor

• Discrete Optimisation
• Mathematical Optimisation
• Scheduling
• +18 more

Elina Rönnberg is a Professor and Deputy Head of Department at the Department of Mathematics, Linköping University, where she leads research in discrete optimisation and intelligent decision-making. Her work bridges theoretical method development and real-world applications in sectors such as healthcare, aviation, mining, and transportation. She is actively involved in the Wallenberg AI, Autonomous Systems and Software Program (WASP) and has collaborated with industry leaders like Saab and Scania. Her research focuses on advanced optimisation techniques including Dantzig-Wolfe decomposition, Lagrangian relaxation, column generation, branch-and-price, and logic-based Benders decomposition. She also explores hybrid methods combining mathematical programming with constraint programming and machine learning. Applications span nurse rostering, electric vehicle routing, aircraft arrival scheduling, and underground mine planning. Recent publications highlight a strong trend toward integrating AI and machine learning—particularly graph neural networks—with classical optimisation frameworks to accelerate solution methods. Her work emphasizes practical impact, robustness, and scalability in solving complex scheduling and resource allocation problems. Nurse Rostering with Strategic Planning of Skills for Sick-Leave Robustness (2024) Pricing for the EVRPTW with Piecewise Linear Charging (2024) Speeding Up Logic-Based Benders Decomposition with Graph Neural Networks (2024) Elina supervises several PhD students and has co-supervised doctoral research at international institutions including Makarere University (Uganda) and the University of Exeter (UK). She has contributed to applied projects through student theses in collaboration with Scania and Saab, focusing on electric vehicle routing and search-and-rescue optimisation. She previously served as a Specialist in Optimisation at Saab Aeronautics (2014–2020) and co-founded Schemagi, a scheduling tool aimed at improving quality in healthcare. She teaches courses such as Introduction to Optimization (TAOP07) and Project - Applied Mathematics (TATA62). Her research group, 'Mathematics and algorithms for intelligent decision-making,' operates within the Division of Applied Mathematics (TIMA) at the Department of Mathematics. The team develops decision support tools that enhance efficiency and sustainability in complex systems, particularly under the growing demands of electrification and digitalisation in transport and logistics.

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

Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.

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 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 .

Panagiotis PapapetrouView profile

Professor

• Data Science
• Machine Learning
• Time Series Analysis
• +5 more

Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science , Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS) , he contributes to shaping AI research directions in Sweden. Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021) His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction. Recent scientific contributions include: CounterFair (2024): Group fairness analysis via counterfactual burden metrics M-ClustEHR (2024): Multimodal clustering for electronic health records COMET (2024): Constraint-based glucose forecasting explanations Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition Z-Time (2024): Interpretable multivariate time series classification His editorial leadership includes: Action Editor at Machine Learning Journal (since 2024) Action Editor at Data Mining and Knowledge Discovery (since 2018) Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)

Kathrin Glüer-PaginView profile

Professor

• Philosophy of Mind
• Philosophy of Language
• Epistemology
• +7 more

Kathrin Glüer-Pagin is a Professor of Theoretical Philosophy at Stockholm University's Department of Philosophy. Her academic work spans philosophy of mind, language, epistemology, and action theory, with a particular focus on meaning, content, normativity, and perception. She is recognized as a leading scholar of Donald Davidson's philosophical contributions. Glüer-Pagin's research interests center on the theory of meaning and content, including foundational and formal semantics, the normativity of meaning, content, belief, and reasons, as well as philosophy of perception and knowledge resistance. Her distinctive approach to perceptual experience, known as 'phenomenal intentionalism,' contends that experiences are a kind of belief with 'phenomenal' or 'looks-content' that ascribes properties to objects in a way that can account for both veridical and non-veridical experiences. She has made significant contributions to debates about meaning normativity, belief formation, and the relationship between language and thought. Her publication record reveals a consistent trajectory of influential work at the intersection of philosophy of language and philosophy of mind. The most recent fifteen publications demonstrate her sustained engagement with questions about perceptual experience, meaning determination, and normativity. Notably, she has developed a distinctive account of 'looks' as relational properties that has implications for understanding visual experience and perceptual justification. Her collaborative work with Peter Pagin on 'switcher semantics' for proper names has provided an alternative framework that accommodates Kripkean intuitions without requiring names to be rigid designators. Glüer-Pagin currently leads the cross-disciplinary research program 'Knowledge Resistance: Causes, Consequences and Cures,' which investigates the nature and causes of knowledge resistance—the tendency not to accept available knowledge. This ambitious program represents a concerted effort to provide a unified framework for investigating knowledge resistance beyond the current state of the art.

Ahmed HemaniView profile

Professor

• Computer Engineering
• Embedded Systems
• Hardware Acceleration
• +5 more

Professor Ahmed Hemani is a faculty member at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He holds the role of PI for the project 'New Chip Architectures for Industrial Vision' and leads research in reconfigurable computing, memristor-based systems, and hardware acceleration for AI and edge computing. His work bridges theoretical computer science with practical VLSI design and embedded systems development. He actively contributes to cross-disciplinary initiatives at Digital Futures, a joint center with Stockholm University and RISE Research Institutes of Sweden focused on digital innovation. His research emphasizes scalable FPGA/HPC architectures, low-power neuromorphic systems, and optimization techniques for custom silicon solutions. Current projects include a Lego-inspired edge AI framework and memristor-driven MIMO acceleration. Teaching responsibilities span advanced courses in SOC design, digital system verification, and embedded systems. He supervises advanced-level degree projects across computer engineering and ICT innovation specializations, emphasizing hands-on hardware-software co-design methodologies. Recent publications highlight innovations in memristor applications, FPGA-based acceleration, and reconfigurable architectures for neural networks and bioinformatics. His work addresses challenges in dark silicon utilization, energy-efficient computation, and high-performance embedded systems.

Monowar BhuyanView profile

Associate Professor

• Machine Learning
• Anomaly Detection
• Systems and AI Security
• +6 more

Monowar Bhuyan is an Associate Professor in the Department of Computing Science at Umeå University, Sweden, leading the Cyber Analytics and Learning Group within ADSLab. He holds a Ph.D. in Computer Science from Tezpur University and has held academic positions at Assam Kaziranga University and Umeå University. His research focuses on machine learning, anomaly detection, edge AI, and distributed systems security. He has secured over 35 MSEK in grants from WASP, STINT, and EU Horizon programs. Education Ph.D. in Computer Science and Engineering, Tezpur University (2014) M.Tech. in Information Technology, Tezpur University (2009) B.E. in Computer Science and Engineering, IETE (2007) Research Interests Distributed/Federated/Responsible Machine Learning Cybersecurity and Anomaly Detection in Edge Clouds AI for DDoS Defense and Cyber Resilience Edge AI and Serverless Computing Recent Contributions His recent work addresses secure federated learning, DDoS attack detection in cloud-edge systems, and responsible AI. Key publications include novel frameworks for VSI-DDoS detection and federated learning optimizations. Awards & Grants Best Paper Awards at ICONIP 2023 and ACM ICACCI 2012 WASP NEST Grant (AIR2 Project, 5 MSEK) EU Horizon Europe Grant (SovereignEdge.Cognit, 8.27 MSEK) Lab & Collaborations He leads the Cyber Analytics and Learning Group (ADSlab), collaborating with institutions like KTH, Linköping University, and Nara Institute of Science and Technology (NAIST). The lab focuses on AI-driven security solutions for distributed systems.

Jonny HolmströmView profile

Professor

• digital innovation
• digital transformation
• digital entrepreneurship
• +3 more

Jonny Holmström serves as Professor at Umeå University's Department of Informatics and directs the Swedish Center for Digital Innovation (SCDI), which he co-founded. He holds an additional affiliation as Professor at the Centre for Transdisciplinary AI, focusing on bridging theoretical research with practical AI applications across sectors including forestry, banking, and public services. His work appears in premier journals such as MIS Quarterly, Information Systems Journal, and Journal of Information Technology. His research centers on digital innovation, transformation, and entrepreneurship, examining how organizations navigate digital change through platform governance, AI integration, and entrepreneurial storytelling. Recent work investigates generative AI's impact on business model design, data work practices, and organizational transformation, emphasizing practical frameworks for managing digital transitions while addressing resistance and ethical considerations. Analysis of his 15 most recent publications (2024-2026) reveals a dominant focus on generative AI's organizational implications, particularly its role in reshaping platform governance, facilitating innovation through prompting, and transforming business models. Concurrent themes include digital platform evolution, data flow management in innovation networks, and citizen-centric digital government design, reflecting a consistent emphasis on practical implementation challenges in real-world contexts. Holmström leads significant research initiatives including a 28 MSEK program at Umeå University and the Kempe Foundation-funded SCDI AI Business Lab. His current project 'Using No-Code AI to Teach Machine Learning in Higher Education' (2024) aims to democratize AI education. He serves on editorial boards for CAIS, EJIS, Information and Organization, and JAIS, and heads the Swedish Center for Digital Innovation research group while participating in 'AI and society' collaborations. He founded and directs the Swedish Center for Digital Innovation (SCDI), which operates the SCDI AI Business Lab exploring practical AI applications for businesses. His work integrates with the Centre for Transdisciplinary AI to advance cross-sector AI implementation, particularly in public services and sustainable business models within the circular economy framework.