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Aniket KitturView profile

Professor

• AI-Augmented Cognition
• Collective Intelligence
• Social Computing
• +7 more

Aniket (Niki) Kittur is a Professor in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University's School of Computer Science. His research focuses on AI-augmented cognition, exploring how humans and computational systems can partner to accelerate knowledge acquisition and innovation. With over 100 peer-reviewed publications and 17 best paper awards or honorable mentions, Dr. Kittur has established himself as a leader in human-computer interaction and social computing. Dr. Kittur's research spans multiple interconnected areas focused on enhancing human cognition through technology. His work on crowd-augmented cognition examines how crowds and computation can collectively enhance human intellect. In social computing, he investigates how sociotechnical architectures can motivate and coordinate large groups for complex tasks. His research in data visualization and sensemaking explores how people collect, organize, and make decisions with online information. Most recently, his work has shifted toward LLM-augmented cognition, investigating how humans and large language models can work together in partnership to achieve better decisions and greater creativity than either could alone. Dr. Kittur's publications reveal a consistent trajectory toward increasingly sophisticated human-AI collaboration systems. Early work focused on crowdsourcing complex tasks (CrowdForge, CrowdSynthesis), then evolved to knowledge acceleration systems (Knowledge Accelerator, Fuse), and has recently centered on LLM-integrated cognition (Selenite, InkSpire, BioSpark). His research consistently demonstrates practical impact, with systems influencing products used by millions and receiving coverage in major media outlets including Nature News, The Economist, and The Wall Street Journal. Kavli fellow NSF CAREER award recipient Allen Newell Award for Research Excellence Inductee into the CHI Academy 17 best paper awards or honorable mentions across his publications Dr. Kittur has advised numerous students, including Andrew Kuznetsov, and has secured major research funding from NSF, NIH, Google, Microsoft, Bosch, Toyota, and other organizations. His Skeema browser extension project, which addresses tab overload through innovative project-based organization, has shown remarkable user retention and represents a practical application of his research on knowledge acceleration. His work with industry partners has influenced products used by millions, including Semantic Reader, Google Shopping, and Wikipedia features.

April Yi WangView profile

Assistant Professor

• Human-Computer Interaction
• Educational Technology
• Programming Support
• +4 more

April Yi Wang is a tenure-track Assistant Professor in the Department of Computer Science at ETH Zürich, where she directs the Programming, Education, and Computer-Human Interaction Lab (PEACH Lab). She is a core faculty member at the Institute for Intelligent Interactive Systems and associated with the ETH AI Center. Wang is also an active member of ETH HCI and Swiss CHI communities, contributing significantly to human-computer interaction and educational technology research. Dr. Wang's educational background includes: Ph.D. in Information Science from University of Michigan (2023), advised by Steve Oney and Christopher Brooks M.Sc. in Computer Science from Simon Fraser University (2018), advised by Parmit Chilana B.Eng in Computer Science from Zhejiang University (2016) Dr. Wang's research focuses on human-centered approaches to programming and data science. Her work reimagines programming as a form of literature that communicates with both machines and people, exploring creative representations like text, shapes, animations, and everyday objects. She investigates how to make programming more natural and intuitive through literate programming environments, with applications in professional and educational contexts. Her research spans human-computer interaction, educational technology, and AI-assisted programming tools. Analysis of Dr. Wang's recent publications reveals a strong focus on AI-enhanced educational tools, particularly for programming and data literacy. Her work increasingly integrates large language models to scaffold learning while maintaining user agency. There's a clear trajectory toward developing situated learning approaches that connect abstract concepts to real-world contexts through augmented reality and tangible interfaces. Her research bridges HCI, education, and AI to create more accessible and engaging technical learning experiences. Dr. Wang has received numerous prestigious awards including: 2023 Gary M. Olson Award and Honourable Mention Award at ACM CHI 2022 Rising Stars in EECS and Heidelberg Laureate Forum Young Researcher 2020 Best Short Paper Award at IEEE VL/HCC and Honourable Mention at ACM CHI 2019 Best Paper Award at ACM CSCW Dr. Wang actively mentors students through thesis projects at ETH Zürich, supervising numerous bachelor's and master's students on topics ranging from AI-assisted programming to data literacy tools. Her lab, PEACH Lab, has secured funding including the recent innovedum funding for the Coducate project. She serves on program committees for major conferences including CHI and UIST, and regularly reviews for top HCI and education journals. The PEACH Lab, directed by Dr. Wang, focuses on creating expressive, intelligent, and human-centered systems that make technical topics more accessible. The lab explores textual, visual, and embodied representations for programming, with emphasis on enhancing communication, collaboration, and learning. Current research directions include balancing automation with user agency, supporting diverse learning needs, and developing tools for interdisciplinary technical communication.

David LindlbauerView profile

Assistant Professor

• Human-Computer Interaction
• Mixed Reality
• Augmented Reality
• +8 more

David Lindlbauer is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University, where he leads the Augmented Perception Lab and co-directs the CMU Extended Reality Technology Center. His research bridges human perception, extended reality (AR/VR), and computational interaction techniques, focusing on developing systems that dynamically adapt interface elements based on environmental context, user cognition, and task requirements. He completed his PhD at TU Berlin under Prof. Marc Alexa and held a postdoctoral position at ETH Zurich's Advanced Interactive Technologies lab. His work has been published extensively at top venues including ACM CHI, UIST, and IEEE VR, with research themes spanning gaze tracking, spatial audio optimization, haptic feedback, and multimodal notification systems. Media outlets like MIT Technology Review and Fast Company Design have featured his innovations. Dr. Lindlbauer has received prestigious grants from Meta, NSF, and ETH Zurich, and serves on program committees for CHI, UIST, and ISMAR. He has been recognized with Best Paper awards at ISS 2023 and CHI 2016, and his lab develops tools like MineXR for personalized XR interfaces and RealityReplay for temporal change visualization in mixed reality environments.

John P. O'DohertyView profile

Professor

• Decision Neuroscience
• Reward-related Learning
• Computational Modeling
• +3 more

John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.

• Reconfigurable Computing
• Field-Programmable Gate Arrays (FPGA)
• High-Level Synthesis
• +3 more

Paolo Ienne is a Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), where he leads the Processor Architecture Laboratory (LAP) within the School of Computer and Communication Sciences. His research focuses on advancing reconfigurable computing systems through innovative FPGA architectures and high-level synthesis methodologies. His primary research domains include reconfigurable computing, FPGA architecture design, dynamically scheduled dataflow circuits, and hardware acceleration techniques. Recent work emphasizes memory system optimization for FPGAs, formal verification of circuit transformations, and rapid C-to-hardware compilation flows. He has pioneered approaches for handling thousands of outstanding memory misses in FPGA accelerators and developed novel techniques for switch-block exploration without explicit pattern enumeration. Analysis of his 2023-2025 publications reveals a strong trend toward practical FPGA deployment challenges, with increasing focus on HBM integration, virtual memory systems for PCIe-attached devices, and formally verified circuit transformations. His work consistently targets real-world bottlenecks in high-level synthesis toolchains while maintaining theoretical rigor in dataflow architecture design. Professor Ienne's laboratory receives support from the Swiss National Science Foundation and industry partners including Huawei, enabling cutting-edge research in FPGA-based acceleration. His collaborative network spans major semiconductor companies and academic institutions worldwide, with frequent co-authorship on conference proceedings and journal publications in IEEE and ACM venues.

• Cognitive Robotics
• Developmental Robotics
• Human-Robot Interaction
• +5 more

Tetsuya Ogata is a Professor at the Faculty of Science and Engineering, School of Fundamental Science and Engineering at Waseda University. He also holds joint appointments as a Fellow at the Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), and as a visiting professor at the National Institute of Informatics (NII). Professor Ogata serves as director of the Institute of AI and Robotics at Waseda University, chairperson of the AI Robot Association (AIRoA), and research supervisor of JST CREST "Fundamentals and Core Technologies for Embodied AI" since 2025. Professor Ogata received his B.S., M.S., and D.E. degrees in mechanical engineering from Waseda University in 1993, 1995, and 2000, respectively. He began his academic career as a Research Associate at Waseda University (1999-2001), followed by positions as a Research Scientist at RIKEN Brain Science Institute (2001-2003), Lecturer (2003-2005) and Associate Professor (2005-2012) at Kyoto University's Graduate School of Informatics, before becoming a Professor at Waseda University in 2012. He was also a JST PRESTO Researcher from 2009 to 2015. Professor Ogata's research focuses on cognitive developmental robotics, deep predictive learning, and the integration of vision, language, and action (VLA) for human-robot interaction. His work explores how robots can learn through experience and interaction with humans and environments, developing models that allow for flexible behavior generation and adaptation. His research has significant implications for creating robots that can understand human intentions, collaborate effectively in real-world settings, and continuously learn from their experiences. The integration of multimodal information processing with predictive models forms the core of his approach to embodied artificial intelligence. Analysis of Professor Ogata's recent publications reveals a strong focus on deep predictive learning frameworks that enable robots to anticipate future states and generate appropriate actions. His research spans multiple domains including soft object manipulation, bimanual coordination, transparent object grasping, and integration of large language models with robotic systems. A notable trend is the increasing emphasis on multimodal integration, combining visual, tactile, and linguistic information to create more robust and adaptable robotic systems. His recent work also shows growing interest in the application of foundation models to robotics, aiming to create more general-purpose robotic capabilities. Best Paper Award, Advanced Robotics, The Robotics Society of Japan (2024) Best paper award Nomination Finalist, IEEE/SICE International Symposium on System Integration (2024) Frontiers of Science Awards, The International Congress for Basic Science (2023) Minister of Education, Culture, Sports, Science and Technology Award (2023) Fellow, Japan Society of Mechanical Engineering (2023) Fellow, The Society of Instrument and Control Engineers (2022) Fellow, The Robotics Society of Japan (2022) IBM Academic Awards (2017) Professor Ogata has been instrumental in establishing collaborative research frameworks between academia and industry, serving in leadership roles for multiple professional organizations including the Robotics Society of Japan, Japanese Society for Artificial Intelligence, and Japan Deep Learning Association. His research has been supported by significant grants including JST CREST funding for "Fundamentals and Core Technologies for Embodied AI." He has mentored numerous researchers who have gone on to contribute to the field of robotics and AI, with many of his former students now holding positions in leading academic and industrial research institutions. Professor Ogata directs the Ogata Laboratory at Waseda University, which focuses on cognitive developmental robotics and deep predictive learning. The lab maintains strong collaborations with industry partners including major robotics companies and technology firms. In 2025, he played a key role in establishing the AI Robot Association (AIRoA), which brings together companies like Toyota, Nissan, and KDDI to advance the development of practical AI robotics technologies. His research group is known for its interdisciplinary approach, combining insights from neuroscience, cognitive science, and engineering to create more human-like robotic capabilities.

• Theoretical Computer Science
• Graph Algorithms
• Dynamic Algorithms
• +7 more

Nicole Wein is an Assistant Professor in the Computer Science and Engineering Division of the Department of Electrical Engineering and Computer Science (EECS) at the University of Michigan, College of Engineering. Her research lies in theoretical computer science, focusing on graph algorithms, dynamic algorithms, parameterized algorithms, distributed algorithms, online algorithms, and fine-grained complexity. She is part of the Theory of Computation Lab and advises both PhD and undergraduate researchers. PhD, Massachusetts Institute of Technology (MIT), advised by Virginia Vassilevska Williams Postdoctoral Fellow, DIMACS Research Fellow, Simons Institute, UC Berkeley MS, Stanford University BS, Computer Science/Math, Harvey Mudd College Her research explores fundamental algorithmic questions in combinatorial settings, particularly how algorithms handle dynamic data, extract information efficiently (e.g., in linear time), and understand shortest path structures in graphs—especially directed ones. She investigates problems in distance estimation, spanners, hopsets, dynamic graph algorithms, and hardness of approximation. Her work combines theoretical depth with practical implications for algorithm design. The recent publications reflect a strong trend in fine-grained complexity and graph algorithm design, with a focus on proving tight bounds, developing efficient approximations, and understanding structural limitations in directed and dynamic graphs. Her work frequently appears in top venues such as STOC, FOCS, SODA, and ICALP, often in collaboration with leading researchers in the field. Scientific Awards and Recognition: Invited to special issue of SIAM Journal on Computing (SICOMP) (FOCS 2022 paper) Invited to Highlights of Algorithms (HALG) (FOCS 2022 paper) Invited to minisymposium at CANADAM (ESA 2022 paper) Work featured in Quanta Magazine Nicole Wein actively mentors students, including current PhD student Jubayer Nirjhor and former undergraduate researchers like Sam Hiken (now pre-doc at MIT). She has served on program committees for major conferences including SODA, FOCS, ICALP, and ITCS, and co-organized the DIMACS workshop on Modern Techniques in Graph Algorithms (2023). She also contributes to the academic community through outreach, such as her article offering reassurance to early-stage PhD students in theoretical computer science. She leads and participates in collaborative research groups and workshops, emphasizing supercollaboration and interdisciplinary communication in algorithms. Her lab fosters a strong research environment in theoretical computer science at the University of Michigan.

Frede BlaabjergView profile

Professor

• Power Electronics
• Wind Turbines
• Photovoltaic (PV) Systems
• +6 more

Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Prof. Dr. Andreas Butz is a Full Professor and Chair for Human-Computer Interaction at the Department for Informatics, Ludwig-Maximilians-Universität München (LMU Munich). He leads the Media Informatics Group, focusing on innovative interaction techniques and interfaces in immersive environments like VR/AR, automotive systems, and smart spaces. His research emphasizes perceptual user interfaces, social robotics, and designing systems that balance invisibility with transparency. Key research areas include: Virtual/Augmented Reality interfaces for productivity and social interaction AI-driven decision support in safety-critical domains (aviation, healthcare) Haptic and wearable interaction technologies Automotive UI design for driver assistance systems Principles of explainable AI and human-AI collaboration His work bridges theory and practice through projects like: VR-based movement training systems AI trust calibration mechanisms Multi-modal interaction frameworks for automotive environments Systems for analyzing long-term music listening behavior Recent articles explore topics ranging from AI support in pilot decision-making to haptic wearables and creative writing interfaces. His team collaborates with industry partners on electric vehicle information systems and in-car interaction challenges.

David MelcherView profile

Professor

• Cognitive Neuroscience
• Perception
• Attention
• +7 more

David Melcher is Professor of Psychology and Program Head in Psychology at New York University Abu Dhabi (NYUAD), where he also serves as a Global Network Professor. He is affiliated with the Division of Science and leads the Perception and Active Cognition Lab, focusing on the integration of perception, attention, memory, and action within a cognitive neuroscience framework. PhD in Psychology and Cognitive Science, Rutgers University (2001) Former researcher and professor in Italy and the UK Current leadership: Program Head, Psychology, NYUAD David Melcher's research centers on cognitive neuroscience , particularly how perception, attention, working memory, eye movements, and self-motion interact to shape cognition and behavior. His lab emphasizes active cognition —the idea that perception is not passive but dynamically shaped by action, context, and goals. He investigates how temporal dynamics in neural processing organize perceptual experiences and guide decision-making. His work spans both healthy and clinical populations, exploring individual differences in spatial and temporal processing across the lifespan. The 15 most recent publications reflect a consistent focus on temporal organization in cognition , perception-action coupling , and neural mechanisms of attention and memory . Keywords across these works include cognitive neuroscience, perception, and neuroimaging, with subfields ranging from eye movement research and neural synchrony to computational modeling and clinical neuropsychology. Collectively, they demonstrate a trajectory toward integrative models of brain function that bridge behavioral, neuroimaging, and computational approaches. Among his notable recognitions is the Distinguished Scientific Award for Early Career Contribution to Psychology from the American Psychological Association (2011), highlighting the early impact of his work in cognitive neuroscience. Distinguished Scientific Award for Early Career Contribution to Psychology, APA (2011) David Melcher has advised numerous students through capstone projects in psychology and computer science, fostering interdisciplinary research at the intersection of cognitive science and technology. His research has been generously supported by major funding agencies including the European Research Council , the US National Institutes of Health , the Italian Ministry of Research and Education , and the Chinese Ministry of Foreign Expert Affairs . He also contributes to the academic community as a member of the editorial boards of Journal of Vision , Psychonomic Bulletin & Review , Perception , and iPerception . He leads the Perception and Active Cognition Lab at NYUAD, which employs a multidisciplinary approach combining behavioral experiments, neuroimaging (fMRI, EEG, MEG), eye-tracking, computational modeling, and clinical assessments. The lab’s research aims to understand how the brain constructs stable percepts from dynamic sensory input, particularly during active engagement with the environment.

Gerd BruderView profile

Associate Professor

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +7 more

Gerd Bruder is an Associate Professor at the University of Central Florida , affiliated with the Department of Computer Science . He previously held positions as a Research Associate Professor at UCF's Institute for Simulation and Training (2016-2022), Post-Doc at University of Hamburg (2014-2016), and Post-Doc at University of Würzburg (2011-2014). Habilitation : Computer Science, University of Hamburg (2017) Ph.D. : Computer Science, University of Münster (2011) M.Sc. : Computer Science (minor in Mathematics), University of Münster (2009) Research Interests : Gerd Bruder's work focuses on Extended Reality (XR) systems, spanning Virtual Reality (VR) , Augmented Reality (AR) , and Mixed Reality (MR) . Key areas include human factors , digital twins , 3D user interfaces , and perceptual modeling , with applications in healthcare, military operations, architecture, and smart environments. Recent Publications highlight innovations in XR locomotion , trust calibration with autonomous agents, spatial cognition , and haptic-visual integration . His 2025 articles address task-switching efficiency in XR and collaborative mixed reality design. Scientific Awards : Best Paper at ACM VRST 2023 2021 TechConnect Innovation Award Best Demo at ACM SUI 2021 Multiple Best Paper Awards (2016-2023) Best Poster & Demo Awards (2015-2020) Patents include systems for medical simulation , smart environment interruption management , and adaptive AR interfaces . His work bridges academic research and practical applications across VR, AR, and MR domains.

Niels HenzeView profile

Professor

• Human-Computer Interaction
• Predictive Models in Interactive Systems
• Mobile Human-Computer Interaction
• +5 more

Niels Henze is a Professor at the Chair of Media Informatics within the Faculty of Languages, Literature and Cultural Studies at the University of Regensburg, where he has been serving since May 2018. His research centers on human-computer interaction, with a strong focus on predictive models in interactive systems, mobile interaction, augmented and virtual reality, and attention-aware computing. His research interests include: Human-Computer Interaction (HCI) Predictive modeling for runtime adaptation Mobile and wearable interaction Augmented and Virtual Reality (AR/VR) Attention-aware and context-sensitive systems Sociocognitive aspects of interactive technologies The analysis of his recent publications reveals a consistent focus on leveraging user behavior and contextual cues to build intelligent, adaptive interfaces. His work integrates machine learning with interaction design, emphasizing real-time model updates, implicit feedback, and cognitive load awareness to improve usability and user experience across mobile and immersive platforms. Scientific awards: No awards mentioned in the provided text. Niels Henze leads research in adaptive interactive systems and advises students in the field of media informatics. He has previously held a junior professorship at the University of Stuttgart and completed his doctorate at the University of Oldenburg under Susanne Boll. He is actively involved in advancing the theoretical and practical foundations of predictive and attention-aware computing. Grants and funding sources are not specified in the text. He is associated with the Institute for Information and Media, Language and Culture (I:IMSK) at the University of Regensburg, contributing to a multidisciplinary environment that bridges informatics with cultural and linguistic studies.

Maria T. SchultheisView profile

Professor

• Neurorehabilitation
• Virtual Reality Technology in Psychology
• Driving Capacity After Neurological Compromise
• +3 more

Maria T. Schultheis is a Professor in Drexel University's Department of Psychological and Brain Sciences and holds a joint appointment in the School of Biomedical Engineering, Science and Health Systems. As Interim Director of Clinical Training, she oversees clinical psychology education. She earned her PhD in Clinical Psychology from Drexel University in 1998. Her research focuses on neurorehabilitation, particularly applying virtual reality (VR) technology to assess and improve driving capacity and everyday functioning in individuals with neurological disorders like traumatic brain injury, stroke, and multiple sclerosis. She has pioneered VR-based driving simulators for clinical evaluation and rehabilitation. Her work integrates clinical psychology, engineering, and transportation science, addressing cognitive, physical, and behavioral demands of driving post-neurological injury. Key projects include developing driving assessment protocols for disabled populations and investigating fatigue management in MS patients. Her interdisciplinary approach has been funded by NIH, NIDRR, and the NMSS. Notable awards include the 2007 APA Early Career Award (Division 40) and recognition from the National Academy of Neuropsychology. Schultheis leads the Applied Neuro-Technologies Lab, emphasizing ecologically valid methodologies. Over 35 peer-reviewed publications and presentations at international forums highlight her contributions. She serves on the National Research Council’s Transportation Research Board, influencing policy on neurological disorders and mobility. Grants have supported projects like VR-based financial competency assessments and understanding dual-task demands in post-concussion driving. Her research also explores decision-making competency in young adults and the neurocognitive correlates of risky driving behaviors. Collaborations with biomedical engineers and transportation specialists reflect her commitment to bridging clinical practice and technological innovation for functional recovery.

David PeetersView profile

Associate Professor

• Multimodal Communication
• Multilingualism
• Bilingualism
• +3 more

David Peeters is an Associate Professor at Tilburg University's Department of Communication and Cognition, part of the Tilburg School of Humanities and Digital Sciences. His research focuses on multimodal communication, multilingualism, and digital communication, leveraging immersive virtual reality (VR) technologies combined with EEG, eye-tracking, and fMRI. He explores neurobiological underpinnings of language, including neuropragmatics, non-verbal communication, and multilingualism. His work is supported by grants such as the NWO Veni and Tilburg University Fund. Peeters teaches courses on virtual reality, language psychology, and digital literature integration in education. He is a Research Fellow at the Donders Institute and President of the Tilburg Young Academy. Key research interests include the role of gesture and iconicity in second language acquisition, bilingual language switching in immersive environments, and the impact of dataism on academic publishing. He collaborates with libraries and schools to integrate digital literature into curricula and public collections. His scientific awards include the NWO Veni Grant and a Fellowship from the International Max Planck Research School for Language Sciences. His research bridges cognitive science, linguistics, and technology, emphasizing ecologically valid experimental paradigms.

Amitai ShenhavView profile

Associate Professor

• Cognitive Neuroscience
• Motivation
• Decision-Making
• +4 more

Amitai Shenhav is an Associate Professor at the University of California, Berkeley, specializing in Cognitive Neuroscience. His research explores the neural and computational mechanisms underlying motivation, affect, decision-making, and cognitive control, as detailed on the Shenhav Lab website . Ph.D., Harvard University Key research themes include: Explaining motivated behavior through affective gradients Modeling decision-making with mutual inclusivity and value integration Investigating cognitive control allocation under varying motivational contexts Understanding neural dynamics in target-distractor interactions Recent publications (2025–2024) highlight his work on value-based decision-making, effort allocation, and computational models of cognitive control. These studies often bridge behavioral experiments with neural recordings and theoretical frameworks. Scientific contributions include: NSF CAREER Award (2021) for research on motivation in cognition He mentors students and collaborators in his lab, focusing on psychophysiological experiments, computational modeling, and neuroeconomic paradigms. His work intersects with psychology, neuroscience, and artificial intelligence, particularly in attention training applications.