Deliang Fan is an Associate Professor at the School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ. His research focuses on AI hardware, in-memory computing, and neuromorphic systems. He received his MS and PhD from Purdue University under Prof. Kaushik Roy. Education: PhD, Purdue University (2015) Research Interests: AI Hardware, In-Memory Computing, Adversarial AI, Neuromorphic Computing His work spans cross-layer co-design for AI applications, including deep learning, bioinformatics, and graph processing. He has authored 170+ peer-reviewed papers and developed hardware solutions for spintronic and memristor-based systems. Recent publications emphasize efficient architectures for transformers, federated learning, and robust neural networks. Awards include the NSF Career Award and multiple best paper recognitions. He serves in editorial and organizational roles for leading conferences like DAC, ISQED, and GLSVLSI.
Prof. Dr. Valentina Dagienė serves as a Professor and Senior Researcher at the Educational Systems Group within the Institute of Data Science and Digital Technologies at Vilnius University, Lithuania. Her academic career spans several decades with significant contributions to informatics education globally, particularly through her leadership in the international Bebras contest initiative. Her research focuses on computational thinking education through constructionist learning approaches, with particular emphasis on task design that promotes deep conceptual understanding in K-12 settings. Prof. Dagienė has pioneered methods for integrating computational thinking into primary education curricula while addressing cultural differences in learning approaches. Her work bridges theoretical frameworks with practical classroom implementations, making complex informatics concepts accessible to young learners through engaging short tasks. Analysis of her recent publications reveals a clear progression toward interdisciplinary integration of computational thinking with STEAM education and digital competence frameworks. Her research increasingly addresses assessment methodologies for computational thinking skills and explores the connections between computational and algebraic thinking. The Bebras contest serves as both a research platform and practical implementation vehicle for her educational theories. Prof. Dagienė has established herself as a key figure in international informatics education through her editorial work, conference organization, and cross-national collaborations. She has fostered partnerships between educators and researchers across Europe and beyond, creating sustainable communities around computational thinking education. Her leadership in the Bebras International Contest has engaged millions of students worldwide in computational problem-solving activities. Through her work with the Educational Systems Group, Prof. Dagienė has developed comprehensive teacher training programs that support educators in implementing computational thinking concepts in diverse classroom settings. Her research on student approaches to problem-solving has informed the design of learning environments that accommodate different learning styles and cultural backgrounds.
Smit Desai serves as Assistant Professor at Northeastern University's College of Art, Media and Design (CAMD), holding joint appointments in the Department of Art and Design and Department of Communication Studies, with an affiliated appointment at Khoury College of Computer Science. His research bridges conversational AI, human-computer interaction, and inclusive design, focusing on voice user interfaces for older adults in healthcare and educational contexts. Education: Ph.D. in Information Sciences, University of Illinois, Urbana-Champaign M.S. in Information Management, University of Illinois, Urbana-Champaign B.E. in Computer Engineering, Gujarat Technological University, India Dr. Desai specializes in understanding user mental models through metaphor analysis to design conversational agents for social roles including teachers and storytellers. His work emphasizes ethical considerations in AI personality design, co-creation with older adults, and metaphor-fluid interfaces that adapt to user cognition. He has published extensively in premier venues such as CHI, TOCHI, and CSCW, contributing foundational insights on voice assistant interactions for aging populations. Analysis of his 2023-2025 publications reveals three dominant trends: (1) Ethical frameworks for LLM-based agent personalities addressing trust and humanness metaphors, (2) Co-designed voice interfaces promoting older adults' well-being in clinical settings like emergency departments, and (3) Metaphor-driven design methodologies for adaptive conversational agents. His work consistently prioritizes real-world deployment challenges and socioemotional impacts of voice technologies. Dr. Desai actively contributes to the research community through leadership roles including Provocation Papers Co-Chair for ACM Conversational User Interfaces (CUI) 2024 conference in Luxembourg.
Simone Kühn serves as Director of the Research Center for Environmental Neuroscience at the Max Planck Institute for Human Development in Berlin and holds the position of Heisenberg Professor at the University Medical Center Hamburg-Eppendorf since 2016. Previously, she led the Lise Meitner Group for Environmental Neuroscience at the Max Planck Institute (2019-2024) and currently directs the Psychiatric Environmental Neuroscience (PEN) working group, a collaboration between the MPIB and Charité-Universitätsmedizin Berlin since 2025. Her academic credentials include a Dipl.-psych from the University of Potsdam (2006), Dr. rer. nat. from the University of Leipzig (2009), and Habilitation in Psychology from Humboldt-Universität zu Berlin (2012). These qualifications established her expertise in the neural mechanisms underlying human-environment interactions. Dr. Kühn's pioneering research examines how natural versus built environments impact mental health, cognitive processes, and neural structures across the lifespan. Her work integrates environmental psychology, neuroscience, and clinical psychiatry to investigate how exposure to different environments shapes brain function and psychological well-being. She employs advanced methodologies including structural and functional MRI, virtual reality environments, and longitudinal study designs to uncover the neural pathways connecting physical environments to mental health outcomes. Her research has demonstrated that natural environments can reduce stress, enhance cognitive restoration, and positively influence brain structure, particularly in regions associated with emotion regulation and memory. Analysis of her extensive publication record reveals a consistent trajectory toward increasingly sophisticated investigations of environmental influences on the brain. Her recent work has expanded into virtual reality applications for mental health treatment, the neural mechanisms of architectural design preferences, and the impact of air pollution on brain health. She has pioneered experimental approaches to study environmental effects through controlled exposure studies, including the development of virtual nature environments that can be precisely manipulated to isolate specific environmental features. Her scientific contributions have been recognized through prestigious appointments: Election to the German National Academy of Sciences Leopoldina Membership in the DFG-Network WAS (Wirkungsforschung in Architektur und Städtebau) Service on the Psychology Review Board of the German Research Foundation (DFG) Fellowship at the German Institute for Economic Research (DIW) Early recognition through admittance to Studienstiftung des deutschen Volkes (2005) Dr. Kühn has mentored numerous doctoral and master's students whose theses explore diverse aspects of environmental neuroscience, from the impact of natural environments on stress physiology to the neural correlates of architectural preferences. Her research has been supported by substantial funding that has enabled large-scale investigations of environmental influences on brain health across different age groups and populations, including vulnerable individuals with mental health conditions. As leader of the Center for Environmental Neuroscience, she directs a multidisciplinary team of researchers who employ cutting-edge methodologies to investigate how environmental factors shape brain development, function, and mental health. The center's work has significant implications for evidence-based urban planning, therapeutic interventions using nature exposure, and understanding the neural basis of human-environment interactions in an increasingly urbanized world.
Guandong Xu is a Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2012. He also serves as the Director of the UTS-Providence Smart Future Research Centre, which focuses on disruptive technology for sustainability, and leads the Data Science and Machine Intelligence Lab dedicated to research excellence and industry innovation in data science and artificial intelligence. Dr. Xu holds a PhD in Computer Science from Victoria University, Australia, along with MSc and BSc degrees in Computer Science and Engineering. After holding various research positions at European and Australian universities, he joined UTS in 2012 and was promoted to Associate Professor in January 2017, then to Professor in January 2019. His research spans data mining, machine learning, social computing, recommender systems, text mining, predictive analytics, and user behavior modeling. He has published over 240 papers in these areas with increasing citations from academia. His recent work demonstrates a strong focus on integrating large language models with recommendation systems, causal inference in recommendation, multimodal learning, and fairness in AI systems. His publications reveal sophisticated graph-based approaches and addressing challenges in dynamic recommendation scenarios, particularly through temporal modeling and hypergraph structures. Dr. Xu has received numerous prestigious awards including the Digital Disruptors Winner for ICT Research Project of the Year (2021), eBay's Leaders' Choice Award (2021), and was elected Fellow of Institution of Engineering and Technology (IET), UK (2021) and Fellow of Australian Computer Society (ACS) (2022). He has shown strong academic leadership as founding Editor-in-Chief of Human-centric Intelligent Systems Journal, Assistant Editor-in-Chief of World Wide Web Journal, and founding Steering Committee Chair of the International Conference of Behavioural and Social Computing Conference. He has supervised over 25 high degree research students and secured over $8 million in research funding from ARC, government, and industry sources, including projects like 'Smart Personalized Privacy Preserved Information Sharing in Social Networks' and 'A Secured Smart Sensing and Industry Analytics Facility for Industry 4.0.' Dr. Xu directs the Data Science and Machine Intelligence Lab at UTS, which aligns with UTS research priority areas in data science and artificial intelligence. The lab focuses on research excellence and industry innovation across academia and industry, with particular emphasis on developing advanced techniques for recommendation systems, knowledge graphs, and multimodal learning applications.
Mark Bo Jensen is an Assistant Professor (Tenure track) at the Department of Engineering Technology and Didactics, Energy Technology and Computer Science at the Technical University of Denmark (DTU). His work bridges engineering and cognitive sciences through the emerging field of Perception Engineering. His research focuses on Extended Reality (XR) and Virtual Reality (VR) technologies to model and understand human perception and cognition. With over 10 years of expertise in real-time computer graphics, he develops immersive systems for applications in data visualization, medical testing, and geometric morphometrics. His recent publications highlight a strong trend in leveraging VR for precise human interaction tasks, such as anatomical landmark annotation and visual field testing, as well as advancing rendering techniques using diffusion models and mesh optimization. This reflects a multidisciplinary approach combining computer science, perception, and real-world applications. He has contributed to multiple research projects, including AL-EYE: The Visual Aid and Virtual Reality-Based Visualization of Geometric Data, where he served both as a PhD student and a project participant. These projects emphasize VR-based tools for data understanding and visualization. Assistant Professor (Tenure track), DTU PhD in Virtual Reality-Based Visualization of Geometric Data, completed June 2023 Project participant in AL-EYE: The Visual Aid (2025) While no formal advisees are listed, his role as a faculty member suggests future student supervision. He has collaborated extensively with researchers such as Jeppe R. Frisvad, Jakob Andreas Bærentzen, and Vedrana A. Dahl.
Davide Tateo is a postdoctoral researcher and visiting professor at TU Darmstadt, leading the Safe and Reliable Robot Learning Research Group within the Intelligent Autonomous Systems group of the Computer Science Department. His research focuses on developing safe and efficient reinforcement learning algorithms for real-world robotics applications. His work spans Reinforcement Learning (Safe RL, Deep RL) and Robotics (fast motion planning, locomotion). He is involved in multiple funded projects including KIARA (advanced manipulation in risky scenarios), DeepWalking (human gait learning), and INTENTION (active perception for legged robots). Recent publications highlight his expertise in Safe RL (inductive biases, collision probability fields), Locomotion (multi-embodiment, morphology-aware policies), and Optimization (contact planning, trajectory distillation). He collaborates with the PEARL lab at TU Darmstadt and has contributed to key workshops like CoRL 2024 and RSS 2024. Contact details: Email: davide.tateo@tu-darmstadt.de Room E303, Building S2|02, Hochschulstr. 10, Darmstadt Phone: +49-6151-16-20811
Leo Wanner is a prominent Professor at Universitat Pompeu Fabra's Department of Information and Communication Technologies, specializing in Natural Language Processing. With a research career spanning over three decades, he has made significant contributions to computational linguistics, particularly in natural language generation, collocations, and hate speech detection. He has served as editor for multiple editions of the International Conference on Computational Linguistics (COLING) including the 2025 edition. Wanner's research interests encompass a wide range of topics in computational linguistics, with recent work focusing on hate speech detection, multilingual processing, and the capabilities of large language models. His work bridges theoretical linguistics with practical applications, addressing challenges in lexical semantics, syntax, and discourse analysis. Notably, he has pioneered research in collocation processing and has contributed to the development of frameworks for analyzing thematic progression in texts. His publication record demonstrates consistent productivity with significant contributions across multiple subfields. Recent work shows a strong focus on contemporary challenges in NLP, particularly hate speech detection and the capabilities of large language models. His research often takes a multilingual perspective, addressing challenges across different language families including Romance and Slavic languages. Wanner has led significant research projects including the development of FORGe, a multilingual deep sentence generator based on the Meaning-Text Theory, which achieved top performance in the WebNLG challenge. His work on multilingual surface realization has established important benchmarks in the field through shared tasks that have engaged researchers worldwide. As an academic leader, Wanner has mentored numerous researchers and contributed to building research infrastructure through corpus development and annotation schema design. His work on collocation resources, thematic progression analysis, and hate speech detection frameworks has provided valuable resources for the broader NLP community.
Jesper Simonsen is a Professor of Participatory Design at the Department of People and Technology, Roskilde University, Denmark. He directs the Information Technology Ph.D. program and has over 30 years of experience in action research, focusing on user-centered IT design and organizational change, particularly in healthcare settings since 2004. Current research projects involve AI implementation in clinical diagnostics (CNN-based renal tumor classification), task reallocation in healthcare (e.g., medication management shifts to pharmacists), and effects-driven innovation in bio-production processes via AI. Collaborations include Region Zealand, Capital Region of Denmark, and international institutions. His research integrates participatory design, action research, and sociotechnical approaches to address challenges in healthcare IT, AI ethics, and organizational transformation. Recent work emphasizes explainable AI, post-implementation evaluation, and modular innovation frameworks. Notable projects include the Roskilde University Strategic Research Initiative ‘Designing Human Technologies’ (2012-2016) and leadership roles in the Participatory Design Conferences Advisory Board (2014-2019). Supervised PhD students include Daniel van Dijk Jacobsen, Christopher Gyldenkærne, and Christine Bech Flagstad.
Jian Tang is an Assistant Professor at HEC Montreal and the Montreal Institute for Learning Algorithms (MILA), as well as an Associate Professor at the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. He is also affiliated with IVADO (Institut de valorisation des données) as a member. His research spans multiple institutions including collaborations with leading biology labs worldwide and access to extensive computational resources through industry partners. Ph.D. in Computer Science, Peking University (2009-2014) Visiting Ph.D. student, University of Michigan (2011.10-2013.8) B.S. in Mathematics, Beijing Normal University (2005-2009) Professor Tang's research focuses on the intersection of deep learning and graph theory, with particular emphasis on geometric deep learning, knowledge graph reasoning, and applications in drug discovery. His work bridges symbolic and neural approaches to create robust reasoning systems that can handle complex structured data. He has pioneered techniques in graph representation learning that have significantly advanced the field of molecular property prediction and protein design. His publication record shows a clear trajectory toward applying geometric deep learning to biological problems, with a growing emphasis on protein design, molecular conformation generation, and multi-omics analysis. Recent work demonstrates sophisticated integration of 3D geometry with deep learning architectures to model complex biomolecular interactions. Canada CIFAR Artificial Intelligence Chairs (CCAI Chair) Tencent AI Lab Rhino-Bird Gift Fund Amazon Faculty Research Award Microsoft-Mila collaboration grant National Research Council Canada (NRC) Collaborative Research and Development Grant Professor Tang actively mentors doctoral and master's students, with six recent graduates working on cutting-edge topics including graph neural networks for reasoning, protein design, and molecular representation learning. His research is supported by substantial funding from industry partners including Microsoft, Amazon, and Tencent, as well as government agencies like NRC. He collaborates extensively with biology labs worldwide, applying AI to solve real-world biomedical challenges. He leads a research group focused on geometric deep learning for drug discovery, with active projects in protein design using geometric-aware models and large language models for multi-omics analysis. The group has access to thousands of GPUs through industry collaborations, enabling large-scale experiments in molecular simulation and generative modeling.
Baochun Li is a Professor and Associate Chair, Research at the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto , with a cross-appointment to the Department of Computer Science. He holds the Bell Canada Endowed Chair in Computer Engineering since 2005. Education: B.Engr. from Tsinghua University (1995), M.S. and Ph.D. from University of Illinois at Urbana-Champaign (1997, 2000) His research interests span cloud computing , distributed systems (including federated learning), security and privacy , and networking , often integrating control theory , game theory , and network coding into practical systems. Recent work focuses on asynchronous federated learning , secure mechanisms for UAV teams , and transformer-based distributed inference . His 15 most recent publications emphasize federated learning , security in distributed systems , and transformer optimization , reflecting trends in large language models and edge computing . Awards and Recognitions: IEEE Fellow (2014) IEEE INFOCOM Achievement Award (2024) Fellow of the Canadian Academy of Engineering (2023) University of Toronto McLean Award (2009) He has contributed extensively to teaching , including launching the first Canadian university course on Rust programming in Fall 2024 and receiving a Departmental Teaching Award (2011). As a professional service leader , he has chaired major conferences like IEEE INFOCOM and IEEE ICDCS.
Dr. George Fitzmaurice is a Research Fellow at Autodesk, leading the Human Computer Interaction and Visualization Research group. With over 120 publications and 95 patents, his work spans 25 years of innovation in interactive systems, focusing on technology-assisted learning , 3D visualization , and novel input techniques . His notable contributions include the Maya 1.0 UI and SketchBook Pro design, as well as pioneering Graspable UIs and Spatially-Aware Displays . Education : MIT (B.Sc. Math/CS), Brown (M.Sc. CS), Toronto (Ph.D. CS) His research explores immersive visualization and generative AI applications in design workflows, with recent work focusing on VR/AR tools like TimeTunnel for motion editing and WhatIF for AI-assisted narrative design. Current projects examine the intersection of large language models , 3D design systems , and collaborative environments . Key article themes include: Generative AI integration (3DALL-E, WorldSmith) Immersive motion analysis (AvatAR, VideoPoseVR) Creative workflow optimization (MoodCubes, Immersive Sampling) Privacy-aware VR systems (Vice VRsa) Scientific Recognition: 2019 - Inducted into ACM CHI Academy 2024 - Awarded ACM Fellow for computing contributions He has developed foundational interaction techniques like ViewCube™ and SteeringWheels™ , and his work continues to shape modern 3D UI paradigms and spatial computing approaches through projects like DreamSketch and Tesseract.
Neil Garrett is a Research Lecturer (Assistant Professor) in the Psychology Department at the University of East Anglia, where he is also a Visiting Lecturer and member of the Cognition, Action and Perception and Social Cognition Research Groups. He is actively involved in research and accepts PhD students, indicating ongoing academic engagement. Research Lecturer, Psychology Department, University of East Anglia Visiting Lecturer, School of Psychology, UEA Member, Cognition, Action and Perception Research Group Member, Social Cognition Research Group Neil Garrett's research focuses on how beliefs and motivation emerge from learning processes. He employs computational modeling, neuroimaging, behavioral experiments, online games, and economic theory to understand decision-making and its neurobiological basis. His work spans cognitive and affective neuroscience, with applications in clinical disorders such as depression and schizophrenia. His recent publications reveal a strong emphasis on belief updating, optimism bias, decision heuristics, and neural mechanisms of motivation. Articles span journals like Nature Communications , eLife , and Journal of Neuroscience , reflecting interdisciplinary and high-impact research. Topics include biased belief updating, foraging decisions, habenula-insular circuits, and computational psychiatry, indicating a cohesive research program in cognitive-affective neuroscience. Sir Henry Wellcome Research Fellow UCL IMPACT Scholar in Experimental Psychology Published in Nature Neuroscience , Nature Communications , eLife , PNAS Contributor to Aeon Magazine , The Conversation , and NBC Garrett has led research projects funded by the Wellcome Trust and British Academy, focusing on information sharing motivations and neural mechanisms in clinical disorders. He collaborates widely, particularly with Tali Sharot, and has advised or co-authored with multiple early-career researchers. He is active in academic dissemination, having spoken at the Pavlovian Society conference. His lab investigates cognitive and neural mechanisms of belief and decision-making, likely involving computational and behavioral methodologies.
Virpi Roto is a Senior Lecturer at Aalto University's Department of Design (School of Arts, Design and Architecture). She specializes in Experience Design for business-to-business industries, focusing on transforming technology companies into experience providers through co-design and service design methodologies. Key research domains: Human-AI interaction, sustainable futures, and workplace experience design Collaboration hubs: Leads the Encore research group Global influence: Top-cited academic in UX research Her work explores the intersections between User Experience , Customer Experience , and Employee Experience , with a particular emphasis on automation maturity and sociomaterial approaches to transparency in remote teams. Recent publications highlight trends in Human-AI team dynamics and experience-driven industrial systems . She actively bridges Design Fiction with ethical awareness in co-design workshops and develops frameworks for measuring long-term UX. Virpi collaborates with researchers across Finland, Sweden, and international institutions, frequently co-authoring with experts like Philippe Palanque, Matthias Baldauf, and Wendy Ju.
Prof. Gerhard Weber holds the Chair in Human-Computer Interaction at Technische Universität Dresden, Germany. Previously, he served as Chair for Human-Centered Interfaces at Christian-Albrechts-Universität zu Kiel (2000–2007) and Professor for Operating Systems and Graphical User Interfaces at Harz University of Applied Sciences (1996–2000). His research focuses on accessible computing, assistive technologies, haptics, and multimodal interaction. Key projects include development of tactile charts (SVGPlott), robotic guidance systems (HapticRein), and indoor navigation solutions for visually impaired users. Current work explores voice interfaces for social robots, autism-inclusive technologies, and accessibility maturity models for higher education institutions. Over 70 publications span conferences like CHI, IEEE, and ACM, emphasizing practical applications in assistive tech. Education & Professional Journey: 2007–Present: Chair in Human-Computer Interaction, TU Dresden 2000–2007: Chair for Human-Centered Interfaces, Kiel University 1996–2000: Professor of Operating Systems and GUIs, Harz University Research Interests: Prof. Weber's work bridges theory and practice in accessibility, emphasizing tactile interfaces, inclusive design, and assistive robotics. Recent projects include: Mosaik : Enabling blind users to create and share graphics via audio-tactile tools Cloud4All : Personalized web accessibility solutions Range-IT : Real-time object detection for navigation aids Advising & Grants: Managed €3.2M in EU and national grants (2011–2020) Supervised 12+ graduate projects on assistive tech Labs & Teams: Leads TU Dresden's Human-Computer Interaction Lab, collaborating with industry partners like Siemens and rehabilitation centers to deploy assistive systems in real-world settings.
