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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.

Rasha Abdel RahmanView profile

Professor

• Language production
• Neurocognitive psychology
• Visual perception
• +5 more

Prof. Dr. rer. nat. Rasha Abdel Rahman is a leading figure in Neurocognitive Psychology at the Institute of Psychology, Humboldt-Universität zu Berlin . Her research bridges the domains of language production , visual perception , and semantic memory organization , with particular emphasis on electrophysiological mechanisms (EEG) and emotional influences on cognitive processing. Habilitation in Psychology (2008), Ph.D. in Psychology (summa cum laude, 2001), and M.S. in Psychology (1997) from Humboldt-Universität Since 2010: Heisenberg Professor of Neurocognitive Psychology 2009: Heisenberg Fellow Her research interests focus on: Language production mechanisms Interface between vision, semantics, and language Functional organization of semantic memory Attentional and emotional modulation of perception Face and object perception dynamics Mental imagery processes The laboratory employs behavioral and electrophysiological (EEG) methods to investigate how knowledge shapes perception and language processing. Recent studies examine: Emotional content's impact on social judgment AI-generated face perception Art perception influenced by artist morality Trustworthiness effects in visual consciousness Selected scientific awards include: Heisenberg-Fellowship (DFG, 2008) Heinz Heckhausen Junior Scientist Award (DGPs, 2002)

Sean B. AnderssonView profile

Professor

• Optimal Estimation
• System Identification
• Single Particle Tracking
• +4 more

Sean B. Andersson is a Professor in the Department of Mechanical Engineering at Boston University's College of Engineering. His research focuses on optimal estimation, system identification, single particle tracking, robotics, and control theory. He earned his Ph.D. from the University of Maryland, College Park. Education : Ph.D. in Mechanical Engineering (University of Maryland, College Park) His work integrates control algorithms with applications in microscopy, nanofabrication, and multi-agent systems. Recent research trends highlight persistent monitoring, trajectory optimization, MRI reconstruction, and dip-pen nanolithography. He has mentored numerous graduate and undergraduate students, many of whom now hold positions at institutions like MIT Lincoln Labs, University of Pennsylvania, and Juniper Networks. Scientific Contributions : Developed robust multi-agent control policies for data harvesting Advanced single particle tracking with real-time feedback Innovated in non-raster scanning probe microscopy Optimized sensor scheduling via minimax and semidefinite programming His lab team combines theoretical and applied research in robotics and control systems, with alumni contributing to academia, industry, and research labs globally.

Reza SamaviView profile

Associate Professor

• Information Security
• Machine Learning
• Trustworthy AI
• +5 more

Dr. Reza Samavi is an Associate Professor at Toronto Metropolitan University's Department of Electrical, Computer, and Biomedical Engineering, Faculty of Engineering & Architectural Science. He is also a Faculty Affiliate with the Vector Institute for Artificial Intelligence and directs the Trustworthy AI Research Lab (TAILab). Previously, he served as Assistant Professor and eHealth Graduate Program Coordinator at McMaster University's Department of Computing and Software (2014-2020). Holding a PhD in Computer Science (University of Toronto, 2013), his academic journey bridges industry experience with rigorous scholarly contributions. His research lies at the critical intersection of Trustworthy AI , Machine Learning Security , and Medical Informatics . He investigates Safety & Security of ML Algorithms Privacy-Preserving AI Systems Transparency Frameworks for Medical AI Blockchain-enabled Privacy Auditing Game Theory for Model Robustness Optimization-based Anonymization Techniques The TAILab research group under his leadership has produced groundbreaking work in Uncertainty Quantification for Neural Networks Robustness Against Adversarial Attacks Medical Image Analysis Clinical Decision Support Systems Emergency Medicine Predictive Modeling His recent projects focus on enhancing migrant youth mental health through LLM-based conversation agents and developing certified robustness guarantees for ensemble networks. Dr. Samavi's scholarly excellence is recognized through Privacy Technologies Research Award (IBM) Privacy By Design Research Award (Ontario IPC) Bridging Divides Emerging Research Grant (TMU) NSERC PGS-D Recipient (Co-supervised student) SOSCIP Accelerator Grant He has secured major funding from NSERC , SOSCIP , MITACS , HHS , and IDEaS programs. As a dedicated educator, Dr. Samavi teaches graduate courses in Secure Machine Learning and Software Testing while mentoring 15+ graduate students across PhD , MASc , and MEng programs. His lab has presented at premier venues including AAAI , IJCAI , and IEEE Transactions while maintaining active collaborations with institutions like Harvard, ETH Zurich, and the University of Waterloo.

Guoquan HuangView profile

Assistant Professor

• Robotics
• Computer Vision
• Robot Learning
• +5 more

Guoquan Huang is an Assistant Professor in the Department of Mechanical Engineering at the University of Delaware. He holds a B.Eng. in Automation from the University of Science and Technology, Beijing (2002), and M.Sc. and Ph.D. degrees in Robotics from the University of Minnesota (2009 and 2012). Prior to his current role, he was a Postdoctoral Associate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on robotics, computer vision, and autonomous systems, emphasizing probabilistic perception, estimation, and control for ground, aerial, and underwater vehicles. He leads the development of the OpenVINS platform for visual-inertial estimation and has contributed to advancements in SLAM (Simultaneous Localization and Mapping), sensor fusion, and multi-robot coordination. Education: B.Eng in Automation (Electrical Engineering), University of Science and Technology, Beijing, 2002 M.Sc. in Robotics, University of Minnesota, Twin Cities, 2009 Ph.D. in Robotics, University of Minnesota, Twin Cities, 2012 His research interests span robotics, computer vision, and autonomous systems , with a focus on: Visual-inertial navigation and SLAM Sensor fusion (LiDAR, IMU, camera) Autonomous vehicle control and safety Multi-robot cooperative localization His recent publications (2023–2025) emphasize robust algorithms for navigation in GPS-denied environments, real-time sensor calibration, and dataset development for aerial visual localization. He has pioneered techniques like decoupled error-state estimation and consistent parallel frameworks for SLAM. Labs/Teams: Leads the development of the OpenVINS research platform, focusing on visual-inertial state estimation. Collaborates on projects involving human-swarm interactions and resilient ground vehicle navigation.

Stefan KlusView profile

Lecturer

• Data-driven model reduction
• Transfer operator approximation
• Machine learning
• +8 more

Dr. Stefan Klus is a Lecturer at the School of Mathematics and Physics, University of Surrey. His research focuses on data-driven model reduction, transfer operator approximation, and kernel-based machine learning applied to dynamical systems. He specializes in interdisciplinary applications across quantum physics, fluid dynamics, and computational biology. Education: PhD in Industrial Mathematics (2011, Paderborn University) and Habilitation (2020, Freie Universität Berlin). Research Interests : Data-driven modeling and reduced-order methods Koopman operator theory and transfer operators Machine learning for dynamical systems (e.g., Deeptime library) Tensor decompositions and quantum systems analysis Graph-based analysis (e.g., microbiome dynamics) Publications : Klus has contributed to over 50 peer-reviewed articles, with recent work emphasizing: Kernel methods for quantum chemistry and physics Tensor-based approaches for high-dimensional systems Applications in climate science (e.g., Pacific SST modeling) Agent-based modeling and social systems Technical Contributions : Co-developer of the Deeptime Python library for dynamical modeling Pioneer in Koopman operator-based model reduction Advanced graph kernel methods for microbiome analysis

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.

Prithviraj AmmanabroluView profile

Assistant Professor

• Natural Language Processing
• Reinforcement Learning
• Artificial Intelligence
• +5 more

Prithviraj Ammanabrolu is an Assistant Professor at the University of California, San Diego (UCSD) , affiliated with the Department of Computer Science and Engineering . He leads the PEARLS Lab (Pragmatically Exploring Agents with Reinforced LanguageS) and collaborates with Nvidia as a Research Scientist. Research Focus: Bridging Machine Learning (particularly Reinforcement Learning ) with Natural Language Processing to create trustworthy and responsible language-based AI agents . Key Themes: Contextual language understanding, neurosymbolic world modeling, human preference alignment via feedback, and AI in grounded environments . Before joining UCSD in 2024, he worked on the Mosaic team at the Allen Institute for AI and as a Research Scientist at MosaicML (acquired by Databricks) . His work intersects Cognitive Science and AI scalability . Education: PhD in Computer Science from the Georgia Institute of Technology , advised by Professor Mark Riedl at the Entertainment Intelligence Lab . Projects: RL4LMs, ScienceWorld, Q-BERT, WorldGeneration, and LLMFoundry for Databricks foundation models.

Tihana BicanicView profile

Professor

• Invasive Fungal Infections
• Antifungal Resistance
• Cryptococcal Meningitis
• +2 more

Tihana Bicanic is Professor of Infectious Diseases and Mycology at St George's University of London, holding honorary appointments at the MRC Centre for Medical Mycology (University of Exeter) and serving as Director of the Infection Clinical Academic Group. Her clinical and translational research focuses on invasive fungal infections, particularly cryptococcal meningitis in HIV patients and ICU-acquired candidiasis/aspergillosis. She leads the CandiRes study on Candida resistance evolution and previously directed the AspiFlu project on influenza/COVID-associated aspergillosis. Key research domains: Cryptococcal meningitis pathogenesis and treatment optimization Antifungal resistance mechanisms and prevention strategies Genomic epidemiology of fungal pathogens Immunotherapy for fungal infections Her group's publications demonstrate consistent focus on clinical mycology, antimicrobial resistance, and immunopathology. Recent work emphasizes diagnostic innovation, therapeutic optimization, and translational approaches for critical care mycoses. Awards and recognition include: Fellowship in the European Confederation of Medical Mycology (FECMM) Member of Wellcome Trust's Pathogen Biology and Disease Transmission Discovery Advisory Group Research team includes laboratory technicians and clinical research fellows investigating fungal pathogenesis and treatment strategies across multiple UK ICUs.

• Robotics
• Human-Robot Interaction
• Social Robotics
• +5 more

Associate Professor David Rye is an Honorary Associate Professor in the School of Aerospace, Mechanical and Mechatronic Engineering at the University of Sydney, affiliated with the Australian Centre for Field Robotics. His research focuses on interdisciplinary robotics, blending engineering, social sciences, and art to explore human-robot interaction, tactile sensing, and autonomous systems. Key areas include social robotics, cooperative robot behavior, and creative robotics design. His work spans theoretical and applied robotics, including studies on robot collaboration dynamics, tactile feedback systems, and robotic excavation. Notable contributions include developing EIT-based sensitive skins for robots and analyzing human comfort in multi-agent interactions. He has led projects such as the Fish-Bird art-robotics collaboration and the experimental human-robot interaction facility funded by ARC grants. Publications highlight advancements in human-robot collaboration ethics, motion planning for social robots, and control systems for autonomous machinery. His interdisciplinary approach bridges robotics engineering with creative arts, fostering innovations in both technical and artistic domains.

Xiaolei GuoView profile

Professor

• Transportation
• Supply Chain Management
• Congestion Pricing
• +3 more

Xiaolei Guo is a Professor of Management Science at the Odette School of Business, University of Windsor. His expertise spans transportation systems, supply chain optimization, and infrastructure pricing strategies. He holds a Ph.D. in Transportation from the Hong Kong University of Science and Technology (2008) and a B.A. in Hydraulic Engineering from Tsinghua University (2004). His research focuses on congestion pricing mechanisms, transportation network modeling, and toll road economics. Notable areas include optimizing toll designs under uncertainty, analyzing autonomous vehicle impacts on ridesharing, and evaluating strategic distribution channel decisions under environmental regulations. Dr. Guo has contributed to over 30 peer-reviewed articles since 2005, exploring topics such as Braess paradox under bounded rationality, Pareto-improving congestion schemes, and profit maximization for private toll roads. His work bridges theoretical optimization with practical policy applications. He is an active member of the Canadian Transportation Research Forum (CTRF) since 2011 and the Institute for Operations Research and the Management Sciences (INFORMS) since 2009.

Vinod NamboodiriView profile

Professor

• Assistive Technologies
• Applied Computer Vision
• Smart Health
• +5 more

Prof. Vinod Namboodiri is the Forlenza Chair in Health Innovation and Technology at Lehigh University's Department of Computer Science & Engineering and College of Health. He leads the Accessibility and Assistive Technologies (ACCESS) Lab, focusing on computing technologies to address health disparities affecting people with disabilities. His NSF-funded research develops navigation solutions for individuals with disabilities, with emphasis on smart communities and built environment accessibility. He holds a Ph.D. from UMass Amherst and previously served as Full Professor/Associate Director at Wichita State University and Adjunct Senior Scientist at Envision Research Institute. His research spans assistive technologies, applied computer vision, and smart health systems. Notable work includes MABLESim (indoor accessibility simulation), NaVIP (visually impaired navigation), and economic analyses of accessibility investments. His publications explore both technical innovations and policy implications of assistive technologies. Prof. Namboodiri has received multiple awards for research, teaching, and innovation. His work bridges computer science with disability studies, emphasizing real-world impact through interdisciplinary collaboration. Current projects address indoor navigation systems, cost-benefit analysis of accessibility infrastructure, and human-agent interaction platforms for disability empowerment.

George HripcsakView profile

Professor

• Biomedical Informatics
• Electronic Health Records (EHRs)
• Data Mining
• +4 more

George Hripcsak is the Vivian Beaumont Allen Professor of Biomedical Informatics and Director of Medical Informatics Services at New York-Presbyterian Hospital, Columbia University. He holds affiliations with the Vagelos College of Physicians and Surgeons and the Data Science Institute (DSI). His expertise spans clinical informatics, electronic health records (EHRs), and medical knowledge representation standards. Hripcsak earned degrees in chemistry, medicine, and biostatistics, and is a board-certified internist. Research focuses on leveraging EHR data for clinical research and patient safety through data mining and causal inference techniques. Notable contributions include the Arden Syntax (a national standard for medical knowledge representation) and leadership in the Observational Health Data Sciences and Informatics (OHDSI) network. He chairs the AMIA Standards Committee and has advised federal health informatics policies under HIPAA. His academic awards include Fellowships in the American College of Medical Informatics (1995) and New York Academy of Medicine. Current projects emphasize federated learning, genomic risk prediction, and large-scale real-world evidence analysis through initiatives like LEGEND-T2DM and All of Us Research Program. Educations: MD, Biostatistics, Chemistry Labs/Teams: OHDSI, DSI, Medical Informatics Services Grants & Funding: Not explicitly listed in provided texts

Soufiene DjahelView profile

Professor

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +7 more

Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.

Caterina CrucianiView profile

Associate Professor

• Financial Economics
• Behavioral Finance
• Trust in Financial Advisory
• +7 more

Caterina Cruciani is an Associate Professor at the Department of Management , Venice School of Management , Ca' Foscari University of Venice. She serves as a member of the University Scientific Instrumentation Service Center (CSA) Management Committee and is affiliated with the Research Institute for Social Innovation . Research Interests Trust dynamics in financial advisory Behavioral finance and investor decision-making Sustainability disclosure and ESG integration Digital transformation in financial services Regional economic development and SME financing Agent-based modeling of cooperative behavior Key Article Trends (2009-2024): Span 15 years of research on financial trust (12 publications), behavioral economics (10), sustainability (6), and digital finance (5). Methodologically combines experimental economics , structural equation modeling , and Supervised Topic Modeling for ESG discourse analysis.