Jason Foster is an Assistant Professor at the Faculty of Engineering, University of Toronto, specializing in Engineering Education and Philosophy of Engineering . His work bridges rigorous academic inquiry with practical applications in engineering pedagogy. His research focuses on Research Through Design , aiming to redefine how design and education intersect. Key projects include analyzing the utility of design tools in small enterprises, developing coherent engineering requirements models, and creating open-source lab equipment for budget-constrained institutions. Recent publications highlight trends in engineering education, such as integrating multidisciplinary design, flexible project planning, and addressing intersubjective grading dynamics. His work emphasizes interdisciplinary collaboration, sustainable development, and systems thinking in curricula. He supervises graduate students through a junior colleague/collaborator model, prioritizing adaptability and critical engagement. No awards or formal honors are mentioned in the provided texts.
Matthieu Cord is a Professor at Sorbonne University and Scientific Director of valeo.ai, leading research in computer vision, deep learning, and computational cooking. He heads the MLIA team at ISIR Lab, focusing on multimodal models, transformers, and efficient architectures. Research areas include computer vision, large language models with vision, and AI-driven food analytics. Key projects: VISA-DEEP AI chair, Foundation VaViM models, and SmolVLA collaboration with Hugging Face. His recent work examines scalable multimodal models , trajectory prediction , and diffusion-based segmentation , with studies on in-context learning and biased shortcut learning in visual question answering. Articles highlight DeiT variants , fishr for OoD generalization , and STEEX for counterfactual explanations . Scientific awards include IUF Honorary Membership (2009), BMVC 2017 Best Paper, and ICIP 2018 Best Paper. As an advisor, he supervised PhD theses on topics like GAN editing , semantic segmentation , and multimodal retrieval . Current roles involve mentoring the 'Research Band' at MLIA and leading EU-funded initiatives like SCAPE. His work bridges theoretical AI exploration with practical applications in autonomous driving and food technology.
Marcia C. Linn is the Evelyn Lois Corey Professor of Instructional Science in the Berkeley School of Education at the University of California, Berkeley. She serves as Chair of the Graduate Group in Science and Mathematics Education (SESAME) and has made significant contributions to the field of science education for over five decades. Dr. Linn is a member of the National Academy of Education and a Fellow of multiple prestigious organizations including the American Association for the Advancement of Science (AAAS), the American Psychological Association (APA), the Association for Psychological Science (APS), the American Educational Research Association (AERA), and the International Society of the Learning Sciences (ISLS). Dr. Linn earned her B.A. in Psychology and Statistics (1965), M.A. in Educational Psychology (1967), and Ph.D. in Educational Psychology (1970) from Stanford University, where she worked under Lee Cronbach. Her early career included working with Jean Piaget at the Institute Jean Jacques Rousseau in Geneva, Switzerland (1967-68), serving as a Fulbright Professor at the Weizmann Institute of Science in Israel (1983), and conducting research at University College in London. She has been a fellow at the Center for Advanced Study in Behavioral Sciences three times and a Writing Resident at the Rockefeller Foundation Bellagio Center twice. Dr. Linn's research focuses on how students learn science and how technology can be used to improve science education. She developed the Knowledge Integration framework, which has become widely used in science education. Her work explores the intersection of cognitive science and educational practice, with particular attention to how students develop understanding of complex scientific concepts. She has pioneered the use of technology in science education, developing the Web-based Inquiry Science Environment (WISE) and directing the NSF-funded Technology-Enhanced Learning in Science (TELS) center. Dr. Linn's recent publications demonstrate a clear trajectory toward integrating artificial intelligence with science education. Her work increasingly focuses on how AI can support knowledge integration, facilitate science learning opportunities, and promote equitable educational experiences. She examines how technology can help students develop deeper understandings of scientific concepts through inquiry-based learning while addressing issues of social justice in science education. Scientific Awards and Honors National Association for Research in Science Teaching Award for Lifelong Distinguished Contributions to Science Education American Educational Research Association Willystine Goodsell Award Council of Scientific Society Presidents first award for Excellence in Educational Research Fulbright Professor (1983) Apple Wheels for the Mind grant (1985) National Institute of Education grant (1983) Throughout her career, Dr. Linn has secured significant funding for educational research, including multiple National Science Foundation grants. She directed the NSF-funded Technology-Enhanced Learning in Science (TELS) center and has led numerous projects investigating the cognitive consequences of computer environments for learning. She has advised countless students and researchers in the field of science education, shaping the next generation of educational researchers and practitioners. Dr. Linn directs the Web-based Inquiry Science Environment (WISE) project and has been instrumental in developing technology-enhanced learning environments for science education. Her laboratory has been at the forefront of creating and testing innovative learning technologies that support students in developing deep understanding of scientific concepts through inquiry-based approaches.
Dr. Michael Baym is an Associate Professor of Biomedical Informatics at Harvard Medical School with affiliate appointments in Microbiology and the Laboratory of Systems Pharmacology, and as an Associate Member of the Broad Institute. He leads the Baym Lab, which studies microbial evolutionary genomics and antibiotic resistance through a hybrid of experimental, computational, and theoretical approaches. His research focuses on: Antibiotic Resistance Evolution and practical interventions Mobile Genetic Elements (plasmids, phages, transposons) Computational Genomic Algorithms for big data analysis Synthetic Biology tools and technologies Key recent publications explore phage discovery systems , phylogenetic compression of microbial genomes, and RNA-guided gene drives in plasmids. His work is supported by multiple NIH/NIGMS and NSF grants including a MIRA award. Scientific honors include: Packard Fellowship (2018) Pew Biomedical Scholarship (2020) Sloan Research Fellowship (2020) A. Clifford Barger Excellence in Mentoring Award (2021) SSQBio Mentorship Award (2022) The lab actively trains PhD students and postdoctoral fellows with alumni occupying academic and industry positions globally. Current team members include researchers from interdisciplinary backgrounds working at the intersection of experiment, computation, and theory .
Gavan J. Fitzsimons is the Edward S. & Rose K. Donnell Distinguished Professor of Marketing and Psychology at Duke University's Fuqua School of Business , with a secondary appointment in the Department of Psychology & Neuroscience. He is a Faculty Network Member of the Duke Institute for Brain Sciences . His research bridges consumer psychology, behavioral decision-making, and social cognition, focusing on nonconscious influences on consumption patterns. Education: Ph.D., Columbia University (1995) Key research themes include subconscious consumer behavior , brand relationships , health-related consumption , and social dynamics in purchasing decisions . Recent work examines financial stress effects on purchase satisfaction, secret consumer behaviors in relationships, and pandemic-related decision-making. Notable trends in his 2023-2025 publications involve Marketing's subconscious influence (2025: Quality-Quantity Tradeoffs) Brand teasing as relationship-building (2025: Humor in Branding) Financial constraint effects on consumer happiness (2024: Opportunity Cost Analysis) Crisis behavior during pandemics (2024: Prosociality Across 39 Countries) Health behavior spillovers in families (2024: Parental Food Choices) Scientific Contributions include Foundational work on nonconscious consumer psychology (2008 JCP editorial) Methodological innovations in moderated regression analysis (2013 JMR ) Behavioral economics of brand sincerity effects (2015 JCR )
Dr. Michelle Cannon is a Lecturer in Digital Arts and Media Education at the University College London (UCL) Institute of Education's Culture, Communication & Media department. She co-leads the Digital Storytelling module and serves as a dissertation supervisor for the MA Digital Media: Education program. Co-investigator, ESRC/AHRC-funded Play Observatory project Editorial board member: Film Education Journal, Learning, Media and Technology Executive Committee Member, Media Education Association International collaborations: British Film Institute, EU cultural agencies Her research explores digital media production in educational settings, focusing on film literacy, postdigital theory, and pandemic-related learning adaptations. Utilizing ethnographic and participatory visual methods, she investigates how children's creative practices intersect with social and cultural learning. Recent publications highlight her work on: Digital storytelling and transludic practices in pandemic contexts Ethnographic studies of postdigital play environments Critical media education frameworks Comparative analysis of European film literacy programs Scientific contributions include: ESRC/AHRC grant for children's play research International film literacy framework development Leadership in EU-funded scoping studies She trains teachers in digital media integration and has evaluated school film programs for the BFI. Her longitudinal study on lower-achieving children's learning experiences included documentary film production.
Georg Martius is a Full Professor in the Department of Computer Science at the University of Tübingen's Faculty of Science and a Max Planck Research Group Leader at the MPI for Intelligent Systems. Since April 2023, he has been a core member of the DFG-funded Cluster of Excellence 'Machine Learning: New Perspectives for Science,' which received extended funding through 2032 for its mission to integrate machine learning into fundamental scientific discovery processes. His academic foundation includes a PhD from the University of Göttingen and Bernstein Center for Computational Neuroscience (2005), a Diploma in Computer Science from the University of Leipzig (2003), and a visiting research period at the University of Edinburgh's Division of Informatics. Postdoctoral positions followed at the Max Planck Institutes for Dynamics and Self-Organization (Göttingen, 2009), Mathematics in the Sciences (Leipzig, 2010), and IST Austria (2015). Professor Martius's research pioneers the intersection of reinforcement learning, robotics, and tactile sensing, with emphasis on developing autonomous systems capable of natural locomotion, dexterous manipulation, and physical-world understanding. His work bridges theoretical machine learning with practical hardware applications, particularly in creating differentiable simulators, superresolution tactile sensors, and biologically plausible learning frameworks for robotic control. Analysis of his 2024-2025 publications reveals dominant trends in offline reinforcement learning (especially goal-conditioned and diversity-maximization techniques), object-centric representation learning for video understanding, and tactile sensing innovations. A strong thread connects foundation models to world model construction, while his work on differentiable physics engines enables precise collision handling and contact dynamics for real-world robotic control. His leadership roles include directing the Distributed Intelligence research team at Tübingen and contributing to major collaborative initiatives like the Real Robot Challenge and Myochallenge 2022. The Cluster of Excellence appointment represents recognition of his contributions to transforming scientific methodology through machine learning, particularly in automating hypothesis generation and experimental design. Current projects focus on integrating large-scale machine learning with embodied intelligence, advancing tactile perception systems like the Minsight vision-based sensor, and developing neuroplasticity-inspired approaches for robust out-of-distribution detection. His work directly impacts fields requiring physical interaction intelligence, from autonomous navigation to medical robotics, with emphasis on sample-efficient learning from limited real-world data.
Aura Istrate is a Lecturer/Assistant Professor in Urban Planning & Sustainable Urbanism at the School of Architecture, Planning and Environmental Policy at University College Dublin (UCD). With an international background spanning multiple continents, she conducts interdisciplinary research on sustainable urban development, focusing on active mobility, nature-based solutions, and climate-neutral cities. She teaches GIS and urban planning modules while coordinating several significant research projects across European and Asian contexts. University College Dublin, School of Architecture, Planning and Environmental Policy Primary Coordinator of C-NEWTRAL (Horizon MSCA-DN 2024-2028) Co-Leader of REALLOCATE (Horizon Europe project 2023-2027) Principal Investigator for BIODIVERSA+ projects (NatureScape and NBS4AQUAMISSION) Educated at the University of Architecture and Urban Planning 'Ion Mincu' in Bucharest (BA and MA) and the University of Liverpool (PhD), Dr. Istrate further enhanced her teaching credentials with a Professional Certificate in University Teaching & Learning from UCD. Her academic journey reflects a strong foundation in architectural and urban planning principles combined with specialized expertise in sustainable urbanism. Dr. Istrate's research focuses on smart and sustainable urbanism, particularly examining active mobility, livable streets, green public spaces, and nature-based solutions in urban planning. Her work employs participatory, geospatial, and mixed methods to inform smart communities and the transition to climate-neutral cities. She has practical international experience in urban design and planning, with ongoing collaborations spanning European and Asian countries, currently teaching and researching across cultures in UCD and UCD's International Colleges (CDIC). Her recent publications reveal a strong focus on street vitality, urban heat adaptation, and nature-based solutions. The research demonstrates methodological diversity combining quantitative spatial analysis with qualitative community engagement approaches. Her work spans multiple geographic contexts, with particular expertise in Chinese urban environments and European cities, showing how urban planning concepts need to be contextualized for different cultural settings. The articles consistently address climate adaptation challenges through innovative approaches like urban nature games and fine-grained street classification systems. Dr. Istrate serves as a PhD thesis supervisor and is actively involved in major research initiatives including C-NEWTRAL (as Primary Coordinator), REALLOCATE (as Co-Leader), and BIODIVERSA+ projects (as PI for NatureScape and NBS4AQUAMISSION). Her grant portfolio includes Horizon Europe projects and other significant funding that supports interdisciplinary research on climate-neutral urban development. She has coordinated multiple teaching modules including Planning Design & Development, GIS & Planning, Intro to Spatial Planning, and Local Planning Studio. She leads international research collaborations and maintains active partnerships across various European and Asian countries. Her work bridges academic research with practical urban planning applications, particularly through her focus on research-by-design approaches and participatory methods that engage communities in the planning process. She has served as a lecturer, tutor, or teaching assistant across departments of Architecture, Planning, Environmental Studies, Global Studies, and Human Geography in Ireland, the UK, Czechia, Sweden, China, and Romania since 2010.
Cecilia O. Alm is a Professor in the Department of Psychology within the College of Liberal Arts at Rochester Institute of Technology (RIT), where she serves as the Artificial Intelligence Program Director. She holds multiple leadership roles including Director of the Center for Human-aware AI and Director of the Computational Linguistics and Speech Processing Lab (CLaSP). Her institutional affiliations span the School of Information, Ph.D. Programs in Cognitive Science and Computing and Information Sciences, Department of Computer Science, and MS in Data Science program. Dr. Alm earned her Ph.D. from the University of Illinois at Urbana-Champaign. Her research focuses on human-centered artificial intelligence with particular emphasis on linguistic and multimodal sensing, affective computing, and natural language processing. She investigates how AI systems can better understand and respond to human communication through multimodal dialogue processing, with applications in accessibility, education, and healthcare. Her recent publications demonstrate a strong trend toward developing inclusive AI systems, particularly through projects addressing Deaf community needs (MULTICOLLAB-ASL), subtle emotion recognition (FUSE corpus), and bias mitigation in NLP. The work consistently integrates multimodal data streams (speech, gaze, gesture) to create more responsive human-AI interaction frameworks. Current research directions emphasize diversity in AI education, visual prosody in sign languages, and human-in-the-loop AI development. Dr. Alm leads several significant NSF-funded initiatives including the AWARE-AI program, IRES AI-PROWIL international research experience, and collaborative projects with Gallaudet University focused on Deaf scientist-centered AI research. She has secured over $2.5 million in external funding for her work on human-aware AI systems. She directs the CLaSP lab which provides research opportunities for PhD, MS, and undergraduate students, with graduates employed at major technology companies including Amazon, Apple, Microsoft, and Facebook. The lab focuses on real-world AI applications in accessibility, human-robot interaction, and multimodal communication systems.
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
Eric J. Gangloff is an Assistant Professor in the Department of Biological Sciences at Ohio Wesleyan University (OWU). His research focuses on understanding how organisms adapt to environmental changes, particularly in reptiles and amphibians, using integrative approaches combining field studies, lab experiments, and molecular techniques. He holds a B.A. from Cornell University, an M.A. from the University of Denver, and a Ph.D. from Iowa State University. Dr. Gangloff leads a lab investigating physiological and ecological adaptations in species such as the common wall lizard, garter snakes, and red-backed salamanders. Notably, his work on Ohio’s invasive wall lizards has been funded by the NSF, exploring their evolutionary success in urban environments. Collaborations span institutions worldwide, including France, Canada, and Australia. His recent studies examine how temperature, oxygen availability, and urbanization influence lizard physiology, behavior, and survival. Key themes include thermal biology, ecological traps, and resilience to pollutants like lead. The lab actively involves undergraduate students in field and lab research, emphasizing hands-on learning. Gangloff’s lab website (https://glare-owu.wixsite.com/glare) showcases ongoing projects and publications. His work bridges basic science and applied conservation, addressing global challenges in biodiversity and climate change.
Matthew Dunbabin is a Professor at Queensland University of Technology (QUT) and Chief Investigator at the Australian Centre for Robotic Vision (ACRV). His expertise spans environmental robotics, with a focus on vision-based autonomous systems for marine conservation, water quality monitoring, and greenhouse gas management. He holds a PhD from QUT and a BEng (Aerospace) from RMIT. Dunbabin has led projects at CSIRO and QUT, developing robots like COTSBot and RangerBot to combat marine pests and promote reef restoration. His work has earned national and international awards, including the 2019 Australian Water Association Award and 2016 Google Impact Challenge. Education: PhD in Engineering, Queensland University of Technology (Queensland, Australia) BEng (Hons) in Aerospace Engineering, Royal Melbourne Institute of Technology (Melbourne, Australia) Research Interests: Environmental robotics and autonomous systems Vision-based perception and classification Marine habitat restoration and pest control Greenhouse gas monitoring via autonomous vehicles Cooperative robotics and sensor networks Awards & Recognition: 2019 Australian Water Association Award (SAMMI Project) 2019 Good Design Award - Sustainability (RangerBot) 2016 Google Impact Challenge People’s Choice Award (RangerBot AUV) 2010 Australian ICT Industry Association National iAward (iSnet) 2006 Queensland Engineering Excellence Innovation Award (Starbug Project) Grants & Projects: ARC Centre of Excellence for Robotic Vision (ACRV): Leading robotic vision research (2014–present) Revolutionising Protection Against Air Pollution: Air quality monitoring networks (2015–present) Establishing Advanced Networks for Air Quality Sensing: Sensor development for urban environments (2017–present) Labs & Collaborations: ACRV at QUT Institute for Future Environments (QUT) CSIRO Autonomous Systems Laboratory (2001–2013)
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.
Haryadi S. Gunawi is a Professor in the Department of Computer Science at the University of Chicago where he leads the UCARE research group (UChicago systems research on Availability, Reliability, and Efficiency). His work focuses on improving the dependability of storage and cloud computing systems, with a particular emphasis on addressing performance stability, reliability, and scalability challenges in modern computing environments. Dr. Gunawi received his Ph.D. in Computer Science from the University of Wisconsin, Madison in 2009. Following his doctoral studies, he was a postdoctoral fellow at the University of California, Berkeley from 2010 to 2012 before joining the University of Chicago faculty. His research focuses on three main areas: (1) performance stability, where he builds storage and distributed systems robust to latency tails and "limping" hardware; (2) reliability and scalability, where he addresses concurrency and scalability bugs in cloud-scale distributed systems; and (3) the intersection of machine learning and systems, exploring how machine learning techniques can solve operating and storage system problems. His work often combines theoretical insights with practical system implementations that address real-world challenges in cloud and storage infrastructure. Dr. Gunawi's publication record shows a consistent focus on storage and cloud system reliability, with recent work increasingly incorporating machine learning techniques to address traditional systems challenges. His research spans the full stack from hardware interfaces to distributed system design, with a strong emphasis on practical solutions that can be deployed in production environments. His work often involves close collaboration with industry partners to ensure real-world relevance and impact. Dr. Gunawi has received numerous prestigious awards including the NSF CAREER award, NSF Computing Innovation Fellowship, Google Faculty Research Award, multiple NetApp Faculty Fellowships, and an Honorable Mention for the 2009 ACM Doctoral Dissertation Award. He has also received the Provost's Global Faculty Award and Facebook Faculty Research Award, highlighting the broad recognition of his contributions to the field. As an advisor, Dr. Gunawi has mentored several PhD students including Ruidan Li, Ray Andrew, Rani Ayu Putri, and William Nixon. His research has been supported by major grants from NSF, Google, Facebook, and NetApp, enabling his team to pursue ambitious research projects at the intersection of systems, storage, and machine learning. Dr. Gunawi leads the UCARE research group at UChicago, which focuses on improving the dependability of storage and cloud-scale distributed systems. He is also involved with the Chameleon cloud research infrastructure project and the broader Systems Group at UChicago, contributing to a vibrant research community focused on systems, programming languages, and software engineering.
Prof. Dr. Michael Gröschel is a Professor of Business Informatics at the Faculty of Computer Science, Mannheim University of Technology. His expertise spans Business Process Management (BPMN, Process Mining), Digital Transformation, and innovative Business Models. He teaches courses on BPM, project management, and e-business, often collaborating with industry clients through student projects. As a consultant, he specializes in BPMN training and IT-driven business strategy. His work emphasizes practical applications of IT tools like RPA and low-code platforms. Recent publications focus on RPA bot performance evaluation, AI in automotive trade, and business model-IT alignment. Prof. Gröschel’s research bridges academic insights with real-world challenges, particularly in leveraging technology for business innovation. He has authored books and articles on business intelligence tools, mobile business strategies, and digital customer care. His consulting services include executive coaching for academic career advancement and enterprise IT management best practices. Office: Building A, Room 007c | Phone: +49 621 292-6764 | Professional website available for further engagement opportunities.
