Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools
Kusum L. Ailawadi is the Charles Jordan 1911 TU'12 Professor of Marketing at the Tuck School of Business at Dartmouth College. She has established herself as a leading expert in marketing channel strategy, brand equity, and multi-channel distribution systems. Her research examines the strategic interaction and distribution of power between manufacturers and their distribution channel partners, with particular focus on how store brands, promotions, and brand equity affect performance. Education: PhD, University of Virginia, 1991 MBA, Indian Institute of Management, 1984 BSc (Honors), St. Stephen's College, Delhi University, 1982 Professor Ailawadi's research spans two primary streams: the first focuses on manufacturer-retailer relationships and channel strategy, examining how power dynamics affect brand performance; the second investigates how marketing actions influence consumers' health status and the nutritional quality of grocery shopping. She has pioneered research showing how warehouse club shopping affects consumer behavior, revealing that club store shoppers spend more, shop more frequently, and consume more calories than non-club shoppers. Her work on multi-channel distribution has been synthesized in her influential 2020 book Getting Multi-Channel Distribution Right , which provides practical guidance for managing brands across physical and digital channels. Her extensive publication record in top marketing journals like Journal of Marketing , Journal of Marketing Research , and Marketing Science demonstrates consistent scholarly impact. Analysis of her recent work shows a strong focus on the evolving retail landscape, with particular attention to private label brands, multi-channel strategies, and the behavioral economics of consumer shopping patterns. Her research increasingly bridges marketing theory with practical applications in retail strategy and consumer health. Notable Awards: Winner, Paul H. Root Award for Significant Contribution to the Advancement of the Practice of Marketing (2018) Distinguished Alumni Award, Indian Institute of Management Bangalore (2020) Winner, John D.C. Little Best Paper Award, Marketing Science (2005) Winner, First William Davidson Award for Best Contribution to Theory and Practice in Retail Marketing (1997) Multiple finalist positions for Paul E. Green Award across various years Professor Ailawadi serves as president of the INFORMS Society for Marketing Science and has held editorial positions at major marketing journals including Journal of Marketing , Journal of Marketing Research , and Marketing Science . She teaches the highly regarded MBA elective on Multi-Channel Routes to Market and has consulted with companies across consumer goods, retailing, consulting, and financial services sectors. Her expertise has also been sought in legal cases related to distribution, brand equity, and promotions, where she has served as both consulting and testifying expert. Her research has been widely covered in media outlets including Harvard Business Review , Wall Street Journal , Forbes , and Advertising Age , demonstrating the practical relevance of her academic work. Her TEDx talk 'Outsmarting the Marketers' further illustrates her ability to translate complex marketing concepts for broader audiences.
Chuang Gan is an Assistant Professor at the University of Massachusetts Amherst, affiliated with the College of Information and Computer Sciences and the Department of Computer Science. His work focuses on advancing artificial intelligence, robotics, computer vision, and embodied agents through interdisciplinary research combining neural networks, physical simulations, and multimodal learning. Research interests include generative models, reinforcement learning, vision-language integration, and scalable autonomous systems. He explores topics like world modeling for robots, adaptive policy learning, and physics-driven AI. His projects often involve creating systems that learn from visual, auditory, and tactile inputs to perform complex tasks such as object manipulation, navigation, and decision-making in dynamic environments. Recent research trends emphasize embodied AI systems capable of long-horizon planning, compositional reasoning, and efficient learning from limited data. His work bridges theory and practice, with applications in robotics, simulation platforms, and multimodal generation. Key contributions include frameworks for 3D scene understanding, adaptive world models, and novel training paradigms for large language models. His research has been applied to robotics platforms like RoboDreamer and UBSoft, focusing on unbounded soft environments. Collaborations involve designing benchmarks for physical scene understanding (e.g., Physion++), and creating tools like DiffTactile for tactile simulation. His work often integrates principles from differential geometry, PDE dynamics, and game theory. Chuang Gan’s research group develops open-source tools and benchmarks, such as the SoftZoo robot co-design platform and the SOK-Bench situated reasoning benchmark. His team emphasizes scalable alignment methods beyond human supervision and explores ethical AI through principles like symmetry-enhanced training.
Gioele Zardini is the Rudge (1948) and Nancy Allen Assistant Professor at MIT's Department of Civil and Environmental Engineering (CEE), with affiliations to the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS). He holds a PhD from ETH Zurich and previously worked as a postdoctoral scholar at Stanford University. His research focuses on co-design of complex systems, autonomous systems, and game-theoretic modeling of transportation networks. Education: BSc and MSc in Mechanical Engineering and Robotics from ETH Zurich (2017–2019), PhD in 2023. He has held visiting roles at nuTonomy Singapore, Stanford, and MIT. Research interests include co-design methodologies, autonomous vehicle systems, compositionality in engineering, and strategic interactions in mobility networks. Recent work emphasizes scalable fleet coordination, safety-critical robotics, and user-centric transportation solutions. Notable awards include the 2024 ETH Doctoral Dissertation Award (Silver Medal), Best Paper at ITSC 2021, and federal grants for enhancing urban transit equity. He leads the Zardini Lab, fostering interdisciplinary collaboration in systems engineering and autonomy. Grants and advising: Received federal grants for transit accessibility projects. His work on Autonomy Talks has produced over 180 recorded lectures, promoting knowledge exchange in autonomous systems. Labs/Teams: Principal Investigator at LIDS, affiliate at IDSS, and founder of the Zardini Lab, focusing on systems co-design, mobility innovation, and game-theoretic frameworks.
James T. Enns is a Professor and Distinguished University Scholar in the Department of Psychology within the Faculty of Arts at the University of British Columbia. His research primarily focuses on the role of attention in human vision, with secondary interests in developmental psychology and human-machine interaction. Dr. Enns' research interests span perception, attention, vision, cognition, development, and human-machine interaction. His work explores how the human mind selects information, with particular emphasis on visual attention mechanisms. His laboratory research investigates the fundamental processes of visual perception and how attention modulates these processes across different contexts and developmental stages. Analysis of Dr. Enns' publication record reveals consistent engagement with visual perception, attentional mechanisms, and cognitive processing. His research demonstrates expertise in both theoretical frameworks and experimental methodologies related to visual attention, with applications spanning basic cognitive science to potential implementations in human-computer interaction systems. His work often bridges theoretical cognitive psychology with practical applications. Canadian Society for Brain, Behaviour and Cognitive Science Donald O. Hebb Distinguished Contribution Award (2013) Distinguished University Scholar, UBC (2004) Robert E. Knox Master Teaching Award (2004) Royal Society of Canada Fellow (2002) Killam Faculty Research Prize (1994) Killam Faculty Research Fellowship (1993) Society of Experimental Psychology Fellow Dr. Enns has served as Editor for the Journal of Experimental Psychology: Human Perception and Performance, and as Associate Editor for Psychological Science, Consciousness and Cognition, and Visual Cognition. His research has been supported by grants from NSERC, the Canadian Foundation for Innovation, the Australian Research Council, BC Health, and Nissan. He has authored textbooks on perception, edited research volumes on the Development of Attention, and published numerous scientific articles on vision, attention, and cognitive science. Dr. Enns is currently accepting graduate students and continues to mentor the next generation of cognitive scientists. Dr. Enns leads the UBC Vision Lab, which focuses on how the human mind selects information. The lab conducts research on visual attention, perception, and cognitive processes using a variety of experimental methodologies.
Professor Janet McColl-Kennedy is a leading figure in marketing and service science at The University of Queensland's Business School. She serves as Program Lead for Innovation Pathways (FaBA) and co-founded the Service Innovation Alliance (SIA) research hub, focusing on customer experience, AI, digital transformation, and sustainability. With Fellow status in the Academy of the Social Sciences in Australia and the Australian and New Zealand Marketing Academy, she holds international recognition including Research.com's World's Best Business Scientists ranking and the Christopher Lovelock Career Contributions to the Services Discipline Award (2025). University of Queensland Business School Honorary Visiting Professor, Cambridge Service Alliance Research Collaborator, University of Cambridge Her research spans customer experience management, service ecosystems, digital transformation, and healthcare services. She has pioneered frameworks for customer value co-creation and service recovery strategies, integrating AI and behavioral science. Her 2019 paper on customer experience insights was implemented by a major B2B organization, while her work on value co-creation improved outcomes at Lutheran Community Care. Recent publications focus on AI impacts in food and beverage services, sustainable service ecosystems, and digital health interventions. She has secured over $89 million in competitive grants, including multiple ARC Linkage and Discovery Projects, and leads cross-disciplinary teams with institutions like Cambridge University and Arizona State University. 2024 - ARC College of Experts appointment 2023 - Bo Edvardsson Industry Impact in Services Award 2022 - Elected Fellow of Academy of the Social Sciences in Australia 2021 - Clarivate Highly Cited Researcher 2018 - Ranked most influential marketing academic in Australia With over 220 publications and a Google Scholar H-index of 62, she has mentored 15 PhD students and examined theses at multiple universities. Her teaching spans 30+ years across undergraduate, postgraduate, and executive programs in Australia, USA, Italy, China, and Korea, with awards for blended learning and corporate education.
Emily S. Cross is Professor at the University of Glasgow's School of Psychology & Neuroscience, where she co-directs the Social Brain in Action Lab (SoBA) and leads the ERC Starting Grant 'Social Robots' project. She completed her PhD at Dartmouth College and held positions at Bangor University, Radboud University, and the University of Western Australia before joining Glasgow. Her research explores: Experience-dependent plasticity through dance and motor learning Social cognition in human-robot interaction Emotional processing during action observation Aesthetic perception of movement Cross-cultural differences in technology acceptance Professor Cross uses neuroimaging (fMRI), neurostimulation (TMS, tDCS), and behavioral methods to study how we perceive and learn from human and artificial agents. Her work has been published in Trends in Cognitive Sciences, Journal of Neuroscience, and Philosophical Transactions of the Royal Society. She currently supervises projects on robot-assisted health interventions and develops VR paradigms to study social cognition.
Andrea Megela Simmons is a Professor at Brown University in the Department of Cognitive, Linguistic, and Psychological Sciences with a secondary appointment in the Department of Neuroscience . She is a member of the Carney Institute for Brain Science and serves as a Principal Investigator on an ONR MURI project. Education : A.B. from the University of Pennsylvania (1973), Ph.D. from Harvard University (1978), Postdoctoral research at Cornell University Simmons specializes in cognitive and neural mechanisms of sound perception and communication across species including frogs, bats, dolphins, and humans. Her work bridges behavioral neuroscience, comparative neurology, and developmental studies to explore auditory processing, echolocation, and sensory integration. Her recent publications highlight interdisciplinary trends in auditory neuroscience, focusing on sound exposure effects, metamorphic neurodevelopment, and sensory-motor coordination in cluttered environments. Key subfields include echolocation, lateral line function, tectal connectivity, and acoustic adaptation across species. Scientific Awards : Fellow, Acoustical Society of America Simmons has received grants from the Office of Naval Research (ONR) for MURI projects and has taught courses such as Animal Behavior , Evolution and Development of the Brain , and Auditory Perception Laboratory .
Shuran Song is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. Previously, she was faculty at Columbia University. She holds a Ph.D. in Computer Science from Princeton University and a BEng from HKUST. Her research focuses on the intersection of computer vision and robotics, particularly in embodied AI, robot manipulation, and sensorimotor learning. Song's work emphasizes learning from physical interactions to enable robots to perform complex tasks autonomously. She leads the Robotics and Embodied AI Lab (REAL@Stanford) and has received prestigious awards, including the NSF Career Award, Sloan Fellowship, and Microsoft Faculty Fellowship. Education: Ph.D., Computer Science, Princeton University; BEng, HKUST Affiliations: Stanford School of Engineering, Department of Electrical Engineering Research interests include deformable object manipulation, visuomotor policy learning, and generalizable robot skills. Her lab develops algorithms for robots to learn through interaction, with applications in household assistance (e.g., TidyBot) and industrial automation. Notable contributions include the TossingBot and Diffusion Policy frameworks. Publications span robotics, computer vision, and AI conferences (RSS, ICRA, CVPR), focusing on policy learning, deformable object handling, and embodied intelligence. Awards highlight her impact in advancing robot learning and perception. Advises doctoral and master's students in robotics and AI, and collaborates on grants from NSF, DoD, and industry partners. Teaches courses on robot perception and embodied AI at Stanford.
Hedvig Kjellström is a Professor at the Division of Robotics, Perception and Learning within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. She holds significant affiliations with the Swedish e-Science Research Centre and the Max Planck Institute for Intelligent Systems in Germany. Her work spans multiple interdisciplinary domains and she serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025. Her research centers on Computer Vision as a sub-field of AI, with three interconnected themes: Computational Aesthetics (exploring aesthetic aspects of human communicative behavior), Communicative Behavior (developing models of how humans and animals perceive and produce non-verbal communication), and Embodied Artificial Intelligence (creating methodologies for robots and autonomous agents to perceive the world through sensors, primarily vision). Her work has significant applications in medical diagnostics, animal welfare, human-robot interaction, and creative arts. Analysis of her recent publications reveals a strong trend toward multimodal AI systems that integrate vision, language, and action understanding. Her research increasingly focuses on animal-centered applications, particularly equine pain detection and behavior analysis, while maintaining strong foundations in human communication modeling, gesture recognition, and 3D reconstruction techniques. The interdisciplinary nature of her work bridges computer science with veterinary medicine, neuroscience, and performing arts. Hedvig Kjellström actively supervises numerous PhD and Master's students across various projects and maintains extensive collaborations with institutions including Karolinska Institutet, Swedish University of Agricultural Sciences, and international partners. Her research is supported by major funding bodies including WASP, VR, and SeRC. She leads or participates in several notable projects including OrchestrAI (communication between conductor and orchestra), ANITA (Animal Translator), MARTHA (3D horse motion analysis), and STING (synthesis and analysis with transducers and invertible neural generators). Her work with ACAI (Animal Centered Artificial Intelligence), which she co-founded and directs, demonstrates her commitment to applying AI for animal welfare.
Natasha Zhang Foutz is a Research Associate Professor of Commerce at the McIntire School of Commerce, University of Virginia . Her work bridges Artificial Intelligence , Marketing Analytics , and Consumer Behavior , with a focus on Digital Content and Location-Based Services . She teaches Marketing Analytics , Entertainment Marketing , and Marketing Models across undergraduate to PhD programs. Ph.D. in Marketing, Cornell University M.S. in Statistics & Marketing, Cornell University B.S. in Economics, Fudan University Her research investigates: AI-Powered Entertainment Marketing : Using machine learning to analyze consumer behavior in digital content. Privacy and Ethical Data Use : Studying consumer trade-offs between privacy and public good, especially during crises like the COVID-19 pandemic . Location Analytics : Leveraging mobile data for urban economics, real estate, and emergency response modeling (e.g., MobiRescue for disaster logistics). Prosocial Consumer Behavior : Exploring how social capital and diversity drive innovation and policy compliance. Recent publications highlight trends in Reinforcement Learning for crisis management, Privacy-Preserving AI , and Freemium Pricing Models in digital markets. Her awards include the 2025 UVA Outstanding Researcher Award and the 2018 Mallen Award for motion picture studies. Natasha serves as an Area Editor for multiple journals, emphasizing Data Science in marketing. She has advised numerous PhD students and collaborated on projects analyzing Big Data in consumer mobility and platform economics.
Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .
Barbara Gail Montero is the Rev. John A. O’Brien Professor of Philosophy at the University of Notre Dame, where she holds a faculty position in the Department of Philosophy within the College of Arts and Letters. She earned her BA from the University of California, Berkeley, and her PhD from the University of Chicago. Her research focuses on two core areas: the metaphysical relationship between mind and body, and the role of consciousness in expert action. Notably, she explores how physicalism interacts with abstract entities and how athletes defy skill plateaus through orthogonal models of attention and automaticity. Her key publications include Continuous Improvement: Intertwining Mind and Body in Athletic Expertise (2022, co-authored), A Very Short Introduction: Philosophy of Mind (2021), and Thought in Action: Expertise and the Conscious Mind (2016). She has also published influential papers on pain memory gaps, expertise-induced amnesia, and critiques of flow-state theories. Montero’s interdisciplinary work bridges philosophy with dance performance, as seen in collaborations like Curved Spacetimes: Where Friedrich Nietzsche Meets Virginia Woolf . Her teaching spans philosophy of mind, logic, and science, emphasizing neural plasticity and conscious engagement in expertise.
Alexandra Paige Fischer is an Associate Professor at the University of Michigan School for Environment and Sustainability (SEAS) . Her research focuses on the human dimensions of environmental change , with emphasis on climate change adaptation , wildfire risk governance , and collective action in forested ecosystems . She collaborates with interdisciplinary teams and serves as a contributing author to the IPCC Sixth Assessment Report . PhD, Oregon State University (Forest Resources Social Science) MS, Oregon State University (Forest Resources Social Science) BA, Hampshire College (Cultural Anthropology) Her research integrates theories from natural resource sociology and human-environment geography , employing qualitative interviews , quantitative surveys , and social network analysis . She leads the Western Forest and Fire Initiative and investigates socio-ecological systems in fire-prone regions and coastal communities. Her work spans the U.S. West and Chile , where she explores global wildfire challenges and flammable plantation impacts. Recent publications highlight her contributions to climate adaptation frameworks , collective risk mitigation , and socio-ecological network analysis . She has received recognition as a Fulbright Scholar and leading fire science researcher . Fulbright Scholar, Facultad de Ciencias Forestales y Recursos Naturales, Universidad Austral de Chile 50 Female Leading Scholars in Fire Science Grants include USDA Forest Service projects on climate change impacts on family forestlands and forestry responses to climate change . She actively contributes to Nature Sustainability , Global Environmental Change , and serves as Associate Editor for Ecology and Society and Frontiers in Climate .
Dhruv Shah is an Incoming Assistant Professor of Electrical and Computer Engineering at Princeton University starting January 2026 and currently serves as a Senior Research Scientist at Google DeepMind. He is also an Associated Faculty member in Princeton's Center for Statistics and Machine Learning, focusing on the convergence of machine learning and robotics for real-world deployment. His academic credentials include a Ph.D. and M.S. in Electrical Engineering and Computer Sciences from the University of California, Berkeley (2024) and a B.Tech. (Honors) in Computer Science and Engineering from the Indian Institute of Technology, Bombay (2019). Shah's research pioneers foundation models for robotics, emphasizing large-scale robot learning, out-of-distribution generalization, and long-horizon reasoning. His group adopts a full-stack methodology spanning algorithmic innovation to system design, drawing from cognitive science to develop physical AI systems at the perception-learning-control interface. Key focus areas include reinforcement learning, human-robot interaction, and continual learning for challenging environments. Analysis of his 15 most recent publications reveals dominant trends in foundation models for visual navigation, language-conditioned policies, and multi-agent systems. His work increasingly integrates multimodal inputs (vision, language) while addressing generalization gaps in real-world settings, with strong emphasis on efficient data curation and scalable robot learning frameworks. His accolades feature the Microsoft Future Leaders in Robotics & AI Fellowship (2024), two IEEE ICRA Best Conference Paper Awards (2024), multiple ICRA finalist awards across cognitive robotics and manipulation categories, and the Berkeley Fellowship (2019-2024). Shah will recruit PhD students for Princeton's upcoming admissions cycle, establishing a research group dedicated to full-stack robotics development. While specific grant details aren't provided, his trajectory indicates significant funding for AI-robotics convergence projects, particularly in foundation model development and real-world deployment challenges. His laboratory at Princeton will integrate algorithmic innovation with system design, focusing on physical AI systems that bridge perception, learning, and control while maintaining strong ties to cognitive science principles for human-aligned robotic intelligence.
