جست‌وجوی استاد و پژوهشگر

Florian T. Pokornyمشاهده پروفایل

دانشیار

• Robotics
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Florian T. Pokorny is an Associate Professor in Machine Learning at the Division of Robotics, Perception and Learning (RPL), Department of Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology. He coordinates research projects such as the Horizon Europe-funded SoftEnable and the WASP-funded Intelligent Cloud Robotics for Real-Time Manipulation at Scale . His research focuses on data-driven methods for robotic manipulation, including transfer learning, cloud robotics, and caging-based manipulation of rigid and deformable objects. Education: PhD in Mathematics, University of Edinburgh (supervisor: Michael Singer) MSc in Advanced Study in Mathematics (Part III), University of Cambridge BSc in Mathematics, University of Edinburgh Research Interests: His work emphasizes scalable robotic manipulation, leveraging deep learning and geometric/topological methods. Key areas include training data requirements, transfer learning, and cloud robotics paradigms for manipulation at scale. Recent projects explore energy margin analysis, caging-guided morphology optimization, and robust policy learning. Publications: His recent work spans topics like caging-based manipulation, federated learning, and cloud robotics infrastructure. Notable contributions include CageCoOpt (manipulation robustness), CloudGripper (open-source testbed), and RealCraft (zero-shot video editing). Awards & Grants: Funded by WASP, Horizon Europe, and the Knut and Alice Wallenberg Foundation. His group hosts the CloudGripper platform and collaborates on benchmarks like DLO@Scale. Advising & Labs: Supervises multiple PhD students and research engineers. Alumni include Robert Gieselmann (Amazon Robotics), Yiannis Karayiannidis (Chalmers University), and Anastasiia Varava (Postdoc at KTH). Active in organizing workshops like RoDGE (IROS 2025) and ICRA 2025 robotics learning events.

Miguel Serras Vascoمشاهده پروفایل

پژوهشگر

• Multimodal Perception
• Reinforcement Learning
• Representation Learning
• +۴ مورد دیگر

Miguel Serras Vasco is a postdoctoral researcher at KTH Royal Institute of Technology in Stockholm, Sweden, affiliated with the Robotics, Perception and Learning (RPL) division. He holds a PhD from Instituto Superior Técnico, University of Lisbon (2023), where his work earned the Best PhD Thesis in AI in Portugal award. His research focuses on multimodal perception, reinforcement learning, and aligning artificial agents with human perception. He previously worked as an RSS Pioneer and research intern at Sony AI. Education: PhD in Artificial Intelligence, Instituto Superior Técnico, University of Lisbon (2023) Research Interests: Vasco’s work bridges robotics, neuroscience, and AI, emphasizing embodied agents that co-exist with humans. He explores representation learning, human-aligned image models, and sample-efficient reinforcement learning. His recent projects include super-human autonomous racing agents and olfactory perception modeling with transformers. Key Contributions: Vasco co-developed the GT Sophy racing agent, achieved outstanding results in visual decoding from brain activity, and proposed methods like FLoRA for preference-based RL. His work on NeuralSolver advances algorithm extrapolation in reinforcement learning. Awards: Best PhD Thesis in AI in Portugal (APPIA, 2023) Outstanding Paper Award at RLC 2024 (for autonomous racing research) Grants/Advising: Vasco advises students on multimodal and reinforcement learning topics. He actively organizes conferences like the Reinforcement Learning and Video Games Workshop (RLVG) at RLC 2025 and collaborates with institutions like INESC-ID (Lisbon). Labs/Teams: Associated with the Collaborative Autonomous Systems unit at KTH and previously with the GAIPS Lab (INESC-ID, Lisbon).

• Robotics
• Industrial Automation
• Reinforcement Learning
• +۳ مورد دیگر

Jonathan Styrud is a Researcher and Industrial Doctoral Student at the Division of Robotics, Perception, and Learning (RPL) at KTH Royal Institute of Technology, collaborating with ABB Robotics. His research focuses on developing control architectures for industrial robots using reinforcement learning techniques, particularly Behavior Trees, to automate assembly tasks in dynamic environments. His work is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP-AI/MLX). He supervises master's theses, such as one exploring methods to avoid local minima in Genetic Programming of Behavior Trees. Notable contributions include investigating hybrid approaches between automated planning and machine learning to enhance robotic adaptability in unstructured settings. Research interests emphasize bridging the gap between simulation and real-world robot deployment, with a focus on transparency and modularity in control systems. His master's thesis proposal advocates for empirical evaluations of local minima mitigation techniques in robotic manipulation tasks, aiming to improve the efficiency of Genetic Programming. Academic supervision includes guiding projects on optimization algorithms for Behavior Trees, as detailed in his proposed master's thesis. Current affiliations include RPL at KTH and ABB Robotics, fostering industry-academia collaboration.

• Robotics
• Computational Geometry
• Topology in Robotics
• +۳ مورد دیگر

Anastasiia Varava is an affiliated faculty member and PhD student at KTH Royal Institute of Technology, working within the Division of Robotics, Perception and Learning. Her research focuses on computational geometry and topology applied to robotic manipulation, particularly caging theory and its practical implementations for handling rigid and deformable objects. She collaborates with advisors Florian Pokorny and Danica Kragic on theoretical and applied robotics challenges. Her work integrates robotics with interdisciplinary fields such as topology, machine learning, and computer vision. Key topics include path planning, deformable object manipulation, and geometric algorithms for motion verification. Recent contributions emphasize data-driven approaches for latent space modeling and visual action planning in robotics systems. Varava has authored or co-authored over 30 peer-reviewed articles and conference papers, covering topics from caging-based motion planning to molecular screening algorithms inspired by robotics. Her publications span journals like IEEE Transactions on Robotics and conferences such as IROS and ICRA, reflecting a strong focus on practical robotic systems with theoretical rigor. Her doctoral thesis, Path-Connectivity of the Free Space: Caging and Path Existence (2019), established foundational work on caging and path non-existence in robotics. Current projects involve advancing geometric evaluation techniques for data representations and exploring diffusion models for robotic skill learning.

• Human-Robot Interaction
• Augmented Reality
• Mixed Reality
• +۵ مورد دیگر

Yuchong Zhang is a Postdoc Fellow at KTH Royal Institute of Technology's Division of Robotics, Perception and Learning, supervised by Prof. Danica Kragic. He completed his Ph.D. at Chalmers University of Technology (2018-2023) and holds an M.Sc. from Nanyang Technological University (2016-2017) and B.Eng. from Hangzhou Dianzi University (2012-2016). Ph.D. in Interaction Design, Chalmers University of Technology, Sweden (2018-2023) M.Sc. in Computer Science, Nanyang Technological University, Singapore (2016-2017) B.Eng. in Computer Engineering, Hangzhou Dianzi University, China (2012-2016) His research centers on human-robot interaction through human-centered design, with expertise in augmented/mixed reality , interactive AI , and affective computing . He bridges cognitive science and engineering to develop intuitive interfaces for industrial tomography and wearable robotics, emphasizing perceptual accuracy and user experience in immersive systems. Publications from 2019-2025 reveal evolving focus from industrial AR visualization (2019-2021) to brain-robot interfaces (2025) and wearable robotics (2024). Key trends include multimodal feedback in AR, EEG-based control systems, and social drone design, consistently applying human-centered methodologies across HCI, robotics, and sensory augmentation domains. He supervises master's projects in interaction design and mobile development while contributing to major initiatives like BOS (Body-centric Operating System) and ELSA (European Lighthouse on Secure AI). His work integrates hardware prototyping with user studies for industrial and assistive applications. As part of KTH's Robotics, Perception and Learning group, he collaborates on projects including TOMOCON (industrial tomography sensors) and European AI safety frameworks, leveraging his background in cross-cultural academic environments (China, Singapore, Sweden).

Tobias Alfvénمشاهده پروفایل

استاد

• Global Child Health
• Sustainable Development Goals (SDG) Research
• Infectious Disease Epidemiology
• +۳ مورد دیگر

Tobias Alfvén is a Professor/Specialist Physician at Karolinska Institutet's Department of Global Public Health , where he leads the Global Child Health and the Sustainable Development Goals research group. His work spans 15+ countries with active projects in Nigeria, Uganda, Vietnam, DRC, and Sweden . Key roles include co-chair of the Centre of Excellence for Sustainable Health (KI-Makerere University partnership) and leadership in global health diplomacy initiatives. Medical Degree (2000) and PhD in Medical Science (2002) from Karolinska Institutet Docent in 2017, Clinical Professor in Global Child Health (2022) Former President of the Swedish Society of Medicine (2020-2024) Research focuses on child mortality reduction through diagnostic innovation (e.g., NeoTapLS smartphone app), emergency care systems (EREMISS project in Malawi), and SDG3 implementation across 30+ projects. His team addresses technology scaling (HOLICARE), multi-sectoral policy (e.g., climate change impact studies), and antimicrobial resistance in ICUs across Vietnam and Laos. Recent articles highlight 2025 breakthroughs in diagnostic systems for meningitis and cholera , with 2024 studies on RSV transmission , mpox , and hypothermia treatment . Awards include Resident Supervisor of the Year 2020 and Forte Post-doctoral Fellowship . Supervises 15+ PhD/Master's students . Collaborations span Johns Hopkins University, Makerere University, University of Bergen, and GSK , with funding from Swedish Research Council , ERC Carrier Grant , and Bill & Melinda Gates Foundation . Current clinical work at Sachsska Children's and Youth Hospital emergency department.

• Personalized Medicine
• Drug Development
• Pharmacogenomics
• +۸ مورد دیگر

Volker Lauschke is an Associate Professor at the Department of Physiology and Pharmacology, Karolinska Institutet, where he leads the Personalized Medicine and Drug Development research group. His work integrates advanced 3D cell culture systems, microfluidics, and molecular profiling to develop novel therapeutic strategies. Department: Physiology and Pharmacology (FyFa) Research Focus: Inflammatory conditions (NASH), infectious diseases (COVID-19), metabolic diseases (type 2 diabetes) Funding: Swedish Research Council Consolidation Grant, KI Faculty Consolidator Grant His research spans pharmacogenomics , population-scale genetics , and machine learning to map ethnogeographic variability in drug response genes. The lab develops 3D primary human tissue models of liver, pancreas, adipose tissue, and skeletal muscle using patient-derived cells, with emphasis on cell-cell interactions and tissue-tissue crosstalk in microfluidic systems. They uniquely employ Nano Reaction Injection Molding (NanoRIM) for biomedical device fabrication and BRET-based biosensors for intracellular signaling monitoring. Analysis of recent publications reveals a strong focus on precision medicine applications through ethnogeographic pharmacogenomic atlases (e.g., PharmFreq), organ-on-chip systems for metabolic disease modeling, and viral pathogenesis mechanisms for hemorrhagic fevers. Key methodologies include chemogenomic screening in patient-derived models, population genomics, and advanced microphysiological systems. Swedish Research Council's Consolidation Grant for "Modulation of Tissue Communication to Combat Non-Alcoholic Fatty Liver" KI Faculty Consolidator Grant (1.2 million SEK/year for 5 years) Contributions to WHO-recommended baricitinib treatment for severe COVID-19 The lab actively collaborates on major initiatives including the Biofab core facility at Biomedicum. Their work on hepatic spheroids has opened new avenues for liver regeneration research, while pharmacogenomic studies directly inform clinical implementation of precision medicine. Current projects emphasize rare variant analysis in pharmacogenes and development of microfluidic multi-organ systems for glycemic control modeling.

• Building Physics
• HVAC (Heating, Ventilation, and Air Conditioning)
• Energy Efficiency
• +۴ مورد دیگر

Mohsen Soleimani Mohseni is a Senior Lecturer at Halmstad University , affiliated with the School of Business, Innovation and Sustainability . He serves as Programme Director for the Master's Programme in Energy Smart Innovation in the Built Environment. His research focuses on Building Physics , HVAC Systems , and Energy Efficiency , with a particular emphasis on thermal performance optimization, control strategies for heating systems, and the application of artificial intelligence in climate control. Key research interests include: Thermal modeling of building components and systems Energy-efficient HVAC design and retrofitting Artificial neural networks for climate prediction and control Renovation technologies for sustainable buildings His publications span over 20 years, addressing topics such as transient radiator performance, low-energy building controls, and hybrid heating systems. He has authored technical handbooks like Formelsamling i energiteknik and contributed to international conferences on building automation and energy engineering. Mohsen collaborates on projects integrating smart technologies into building design, emphasizing practical solutions for climate-smart infrastructure.

Shahina Begumمشاهده پروفایل

استاد

• Artificial Intelligence
• Multimodal Machine Learning
• Explainable AI (XAI)
• +۴ مورد دیگر

Shahina Begum is a Professor in Artificial Intelligence at Mälardalen University (MDU), leading the Artificial Intelligence and Intelligent Systems group. She focuses on developing intelligent systems for medical and industrial applications, with expertise in multimodal machine learning, explainable AI, and decision support systems. She holds a PhD in AI from MDU (2011) and has led numerous research projects, including initiatives funded by the Swedish Knowledge Foundation and KK-Stiftelsen. Her teaching roles include designing and leading over 21 courses/learning modules in AI and machine learning, both on-campus and distance-based. She is the main responsible for AI content in MDU's 'Bachelor program in Applied AI' and has spearheaded MOOC courses like 'Basic Knowledge on ML' and AIClass. She also leads industrial collaboration projects such as IntoDeep, KIT, and PROMPT, addressing Industry 4.0 challenges. Research interests span sustainable AI development, trustworthy AI systems, and AI for manufacturing/predictive maintenance. She has received notable recognition, including the Prospect grant (2011) and inclusion in the Royal Swedish Academy's top 100 sustainable AI researchers (2020). Her work emphasizes bridging academic research with industry needs through collaborative initiatives. She has published extensively on multimodal learning, explainable AI, and applications in transportation, healthcare, and manufacturing. Her awards include the Best Paper Award at the 2024 conference for work on second-order learning. She actively contributes to academic governance, serving on evaluation committees, conference organizing committees, and funding review boards.

Bo Bernhardssonمشاهده پروفایل

استاد

• Control Engineering
• Medical Data Modeling
• Signal Analysis
• +۳ مورد دیگر

Bo Bernhardsson is a full Professor at Lund University's Department of Automatic Control within the Lund Institute of Technology (LTH). He also holds roles in ELLIIT (Linköping-Lund initiative on IT and mobile communication) and is a profile area member in Engineering Health, AI and Digitalization, and Natural and Artificial Cognition. After earning his Ph.D. in Automatic Control from Lund University in 1992 and a postdoctoral fellowship at the University of Minnesota, he returned to Lund, becoming a docent (1998) and full professor (1999). From 2001–2010, he worked at Ericsson as a mobile system design and optimization expert before resuming his academic role at Lund University. Education: Ph.D. in Automatic Control (Lund University, 1992), Docent (1998) Affiliations: ELLIIT, LTH Profile Areas (Engineering Health, AI & Digitalization), LU Profile Area (Natural and Artificial Cognition) His research focuses on EEG signal analysis , control of uncertain systems , radio-based sensing and communication , and medical data modeling , blending theoretical analysis with practical applications. His work contributes to UN Sustainable Development Goals through advancements in healthcare and communication systems. Recent research highlights include advancements in 5G NR localization, EEG-based auditory attention decoding, and transfer learning for medical signal processing. He has supervised over 37 students, including doctoral candidates like F. Heskebeck and D. Pjanić. Active in interdisciplinary collaborations, he organized workshops such as the 2021 AI Lund seminar on uncertain system modeling and contributed to projects like the 2020–2022 pandemic dynamics initiative. Bernhardsson has authored 146 publications, 19 research projects, and engaged in 41 academic activities, reflecting his leadership in both technical and educational spheres within control engineering and applied systems.

Bengt Lindholmمشاهده پروفایل

دانشیار

• Renal Medicine
• Chronic Kidney Failure
• Peritoneal Dialysis
• +۴ مورد دیگر

Bengt Lindholm is an Associate Professor and Senior Research Specialist at the Karolinska Institutet , leading the Renal Medicine at Novum group within the Department of Clinical Science, Intervention and Technology. His work focuses on clinical research in renal medicine, particularly chronic kidney failure, cardiovascular complications, metabolic disorders, and peritoneal dialysis optimization. He maintains active collaborations with Karolinska University Hospital and the Polish Academy of Sciences. Education: MD, PhD, B.Sc. (Economics) Key Research Areas: Chronic kidney disease, dialysis-related complications, vascular calcification, and nutritional interventions Awards: Life-Time Achievement Award in Peritoneal Dialysis (2006) Honorary Member, Polish Society of Nephrology (1998) Honorary Member, Spanish Society of Nephrology (2012) Medal from Polish Academy of Sciences (2015) Distinguished Fellow of ERA-EDTA (2017) Bengt Rippe Research Prize (2022) With over 775 publications and an h-index of 113, Lindholm's research explores dialysis fluid composition, remote monitoring systems, and nutritional strategies for CKD patients. His team has published extensively on peritoneal dialysis efficiency, cardiovascular risk factors, and medical interventions for hyperkalemia.

György Dánمشاهده پروفایل

استاد

• Applied Game Theory
• Critical Infrastructure Security
• Edge Computing
• +۵ مورد دیگر

György Dán is a Professor in Teletraffic Systems at KTH Royal Institute of Technology, Stockholm, Sweden. He holds a Ph.D. in Telecommunications from KTH (2006) and has extensive academic leadership roles, including Director of Third Cycle Education. His research focuses on networked systems design, with expertise in critical infrastructure security, edge computing, and cyber-physical systems. Dán has supervised over 20 PhD students and led major projects like VR DICE6G and REACT. He has authored/co-authored over 150 publications, receiving awards such as the Ericsson Research Foundation Award (2010-2014) and the 2020 KTH PhD Supervisor of the Year. Education Ph.D. in Telecommunications, KTH Royal Institute of Technology (2006) M.Sc. in Business Administration, Corvinus University of Budapest (2003) M.Sc. in Computer Engineering, Budapest University of Technology and Economics (1999) Research Interests His work spans applied game theory, smart grid security, mobile edge computing, and adversarial machine learning. Current projects include resilient edge computing systems and secure AI for cyber-physical infrastructures. Awards & Recognition Best Paper Awards at SNCNW 2025, IEEE SmartGridComm 2014, and IEEE Infocom 2008 Fulbright Visiting Scholar (University of Illinois, 2012-2013) Invited Professor at EPFL (2014-2015) Labs & Collaborations He leads the Network and Systems Engineering Division at KTH, collaborating with industries like Ericsson and ABB. His group focuses on experimental platforms like the GreenEyes testbed and stateful serverless edge computing.

Alexandre Bartelمشاهده پروفایل

استاد

• Software Engineering
• Computer Security
• Android Security
• +۳ مورد دیگر

Alexandre Bartel is a Professor at Umeå University's Department of Computing Science and a member of the Research Management Group Software at the Wallenberg AI, Autonomous Systems and Software Program (WASP). His primary research focuses on software engineering and computer security, with particular emphasis on Java vulnerabilities, Android security, and cryptographic systems. His recent publications highlight trends in Control Flow Integrity (CFI) adoption Java deserialization attacks Android malware detection using BERT Blockchain wallet security JVM fuzzing for type confusion Secure development practices As head of the Software Engineering and Security research group, he contributes to advancing security methodologies for complex software systems, particularly in collaboration with European research initiatives.

• Artificial Intelligence
• Formal Methods
• Neuro-Symbolic AI
• +۴ مورد دیگر

Andreas Brannstrom is a Postdoctoral Fellow at the Department of Computing Science, Umeå University, Sweden, conducting research on formal and neuro-symbolic methods for trustworthy, human-centered artificial intelligence. His work spans theoretical foundations in knowledge representation to applied verification of interactive systems and intelligent decision support. His research focuses on formal verification of human-agent interaction, neuro-symbolic AI integration, and ethical AI development. Key methodologies include Answer Set Programming (ASP), formal argumentation, and Description Logic (DL), targeting applications in deception detection, computational empathy, and behavior-change systems. Recent work emphasizes security in information-seeking dialogues and socio-technical aspects of AI deployment. Analysis of his 2023-2025 publications reveals a dominant trend in verifying social engineering vulnerabilities through formal methods, with significant contributions to machine ethics ontologies and multicultural affective computing. His research consistently bridges theoretical AI frameworks with real-world applications in healthcare, industrial logistics, and public safety. Brannstrom is affiliated with Umeå University's Agents and Reasoning Group, Formal Methods for Trustworthy Hybrid Intelligence, and Responsible Artificial Intelligence research groups. His active projects include "Strategic Argumentation to deal with interactions between intelligent systems and humans" (2020-2024) and "Collaborative mixed-reality aid for children with autism" (2019-2020), demonstrating commitment to socially impactful AI research.

Erik Elmrothمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• Edge Computing
• +۳ مورد دیگر

Erik Elmroth is a Professor at the Department of Computing Science, Umeå University. He leads research in distributed systems, cloud/edge computing, and autonomous resource management, directing a 30+ member research group. His leadership includes transformative roles as department head (2009-2021) and Deputy Director at High Performance Computing Center North (HPC2N). Elmroth serves on executive committees for the SEK 6.2B Wallenberg AI program (WASP) and SEK 390M eSSENCE initiative, and leads multiple Kempe Foundation projects. Research interests center on: Autonomous control of cloud/edge infrastructures Software-defined systems and federated clouds AI-driven resource optimization High-performance computing architectures Robust machine learning for distributed environments His publications emphasize adaptive cloud systems, anomaly detection, and federated learning, with consistent focus on scalability and resilience in edge/cloud deployments. Awards and honors: Member of Royal Swedish Academy of Engineering Sciences (IVA) Nordea Scientific Prize (2011) SIAM Linear Algebra Prize (2000) National HPC Lecturer appointment He has supervised 40+ PhD students and secured major grants including the Swedish Research Council's second-largest award for the Cloud Control project. Elmroth founded the Control Workshops series and co-founded Elastisys AB, a cloud security firm with 50+ employees recognized as Umeå's Spin-off Company of the Year.