Dominik Hangartner is a Professor of Political Analysis at ETH Zurich and co-director of the Stanford-Zurich Immigration Policy Lab. His research combines fieldwork and statistical analysis to evaluate migration policies and political institutions. Education: Doctorate in Social Sciences, University of Bern (2011) Research Interests focus on: Immigrant integration Effects of direct democracy Discrimination monitoring Refugee policy evaluation Political economy of migration Publications span Science , Nature , and American Political Science Review , with recent work analyzing refugee return dynamics, welfare migration, and media effects during crises like the Syrian refugee influx and the pandemic. Scientific Awards: Philip Leverhulme Prize National Latsis Prize ERC Starting Grant Grants & Projects include EU and Swiss National Science Foundation funding for immigration policy experiments. He collaborates with the Immigration Policy Lab on algorithmic integration strategies and field experiments.
Christos Gatzidis serves as Executive Dean of Bournemouth University's Faculty of Science and Technology since October 2023, overseeing six departments including Computing and Informatics, Creative Technology, and Psychology. Previously Deputy Dean (2021-2023) and Head of Creative Technology Department (2016-2021), he was appointed Professor in Creative Technology in November 2019. The Faculty leads five REF Units of Assessment and secures funding from AHRC, NIHR, and Innovate UK for research spanning digital healthcare, gaming technologies, and cultural heritage applications. His educational qualifications include: PhD in Information Science, City University London (2010) PG Cert in Research Degree Supervision, Bournemouth University (2010) MA in Computer Animation, Teesside University (2003) BSc (Hons) in Computer Studies (Visualisation), University of Derby (2002) Professor Gatzidis specializes in computer graphics with research spanning virtual reality, serious games, and digital healthcare applications. His work bridges technical innovation and practical implementation, particularly in mindfulness prototypes for healthcare and stroke rehabilitation systems. Current projects focus on the multidisciplinary application of gaming technologies in medical contexts, emphasizing user experience and therapeutic outcomes through collaborations with industry partners. His publication record (2014-2025) demonstrates evolving expertise from foundational computer graphics research in terrain generation and deformation to applied work in healthcare, cultural heritage, and music education. Key trends include virtual reality for therapeutic mindfulness, usability studies in mobile gaming, and digital cultural presentation techniques, reflecting a trajectory toward socially impactful technological solutions with strong industry translation. No scientific awards are documented in the provided information. He has supervised PhD students and secured competitive research funding, including two Innovate UK Knowledge Transfer Partnerships. His principal investigator role in a virtual reality mindfulness prototype project exemplifies his approach to translating academic research into practical industry solutions, with current focus on expanding knowledge exchange activities to support the University's civic engagement mission. As Executive Dean, he leads faculty-wide research strategy across six departments, fostering interdisciplinary collaborations particularly in digital healthcare and cultural heritage. His personal research integrates computer graphics expertise with clinical applications through partnerships with healthcare providers and technology companies, driving innovation in therapeutic VR systems and educational gaming platforms.
Professor Thanos Papadopoulos is a faculty member at the University of Kent , serving as Deputy Dean and Head of the Department of Analytics, Operations & Systems. He is affiliated with the Centre for Logistics and Sustainability Analytics (CeLSA) . PhD : Warwick Business School, University of Warwick MSc : Informatics, Athens University of Economics and Business Diploma : Computer Engineering and Informatics, Patras University His research focuses on Operations and Information Management , with emphasis on digital technologies in supply chains , resilience , and sustainability . Recent work explores AI, metaverse, and data-driven strategies. He has authored 150+ peer-reviewed publications and collaborates with journals like British Journal of Management as Associate Editor. Awards include Stanford's Top 2% Researchers and Clarivate Highly Cited distinctions. Professor Papadopoulos supervises students in supply chain management , big data , and sustainability . His projects address geopolitical disruptions and digital transformation in manufacturing and retail.
Elvin Karana is a Professor of Materials Innovation and Design at Delft University of Technology's Faculty of Industrial Design Engineering. His work bridges the gap between material science, design, and human-computer interaction with a focus on emerging materials and their experiential qualities. He leads the Materials Experience Lab, which investigates how materials communicate ideas and beliefs while enhancing functionality and user experience. Dr. Karana's research interests center on Materials Design, Emerging Materials, Material Driven Design, Bio-based Materials, and Materials Experience. His work explores how living materials can be incorporated into design practices, particularly focusing on microbial interactions, textile interfaces, and regenerative material ecologies. He investigates how materials can be designed to create serene experiences, facilitate multispecies interactions, and support sustainable practices in human-computer interaction. His recent publications demonstrate a strong trend toward biodesign and living materials, with significant focus on microbial systems like cyanobacteria and flavobacteria. His work explores the design space of direct interactions with living organisms, examining how materials can be designed for performativity and how livingness can be understood as a material quality. The research spans textile interfaces, material ecologies, and regenerative design approaches that integrate living systems into everyday artefacts. Best Paper Honourable Mention (2023) Dr. Karana serves as a member of the Supervisory Board/Advisory Board at Avans University of Applied Sciences (CARADT) from May 2024 to December 2025. His research has been featured in various media outlets including TU Delft, Delta, Strawberry Earths, and architectmagazine, highlighting the societal impact of his work on living materials. His projects often involve interdisciplinary collaborations across design, biology, and engineering disciplines. He leads the Materials Experience Lab, which approaches materials as a medium that communicates ideas, beliefs, and approaches while compelling users to think, feel, and act in certain ways. The lab's work emphasizes the dual role of materials as both technical and experiential components in design, exploring how material qualities can be harnessed to create meaningful interactions and sustainable solutions.
Francis Y. Yan is an Assistant Professor of Computer Science at the University of Illinois Urbana-Champaign (UIUC), holding an affiliate appointment in Electrical & Computer Engineering within the Grainger College of Engineering. He leads the Illinois Networked Systems and AI (NSAI) research group, focusing on building intelligent networked systems that are safe, robust, and performance-optimized through practical machine learning integration. Prior to joining UIUC in January 2025, he served as a Senior Researcher at Microsoft Research Redmond under Victor Bahl. His educational background includes: Ph.D. in Computer Science from Stanford University (2020), advised by Keith Winstein and Philip Levis B.S. in Computer Science (Yao Class) and B.A. in Economics from Tsinghua University (2015) Additional undergraduate studies at MIT Yan's research adopts a holistic approach to practical machine learning for networked systems, emphasizing judicious application rather than indiscriminate use. He builds real-world systems and research platforms to lay ML foundations, devises deployable algorithms using domain insights, and validates performance through extensive empirical evidence. His work consistently addresses operator concerns regarding ML deployment—focusing on safety, robustness, generalization, and efficiency—while strategically combining ML with classical networking and systems techniques. Analysis of his 15 most recent publications (2023-2025) reveals dominant themes in resource allocation for microservices (DeDe, Autothrottle), real-time video optimization (Mowgli, GRACE), and LLM-driven network algorithm design. His work bridges theoretical advances with industrial deployment, evidenced by platforms like Puffer (400,000+ users) and OpenNetLab that have become community standards for validating congestion control algorithms. His research has been recognized with top honors: USENIX NSDI Outstanding Paper Award (2024) for Autothrottle APNet Best Paper Award (2022) IRTF Applied Networking Research Prize (2021) USENIX NSDI Community Award (2020) USENIX ATC Best Paper Award (2018) for Pantheon Yan actively recruits master's and undergraduate researchers for his NSAI group, prioritizing self-motivated students for projects in networked systems and AI. His research is supported by industry collaborations (notably Microsoft) and manifests in deployable platforms like Puffer—which has enabled award-winning research at NSDI and SIGCOMM—and OpenNetLab for real-time communications. His work directly impacts production systems including Microsoft Teams and Bing. He founded and directs the Illinois Networked Systems and AI (NSAI) research group, which operates critical infrastructure including Puffer (a live TV service and research platform) and OpenNetLab. These platforms facilitate community-wide validation of novel algorithms, with Puffer alone supporting multiple best-paper awards at top conferences. Current workstreams span cloud resource management (Teal, Autothrottle, DeDe), low-latency video (Puffer, Tambur, Mowgli), and LLM-augmented systems (Nada, Designing Network Algorithms via LLMs).
Jeff S Abramson is a Professor of Physiology in the David Geffen School of Medicine at the University of California Los Angeles (UCLA). His research focuses on the structural and functional characterization of membrane transport proteins, particularly sugar transporters and mitochondrial channels. He maintains an active laboratory investigating the molecular mechanisms of cellular transport processes. Dr. Abramson's primary research interests center on membrane transport proteins, with particular emphasis on sugar symporters and voltage-dependent anion channels (VDACs). His work combines structural biology, biophysics, and biochemistry to understand the molecular mechanisms of transport, including conformational changes during transport cycles, substrate recognition, and regulation by membrane potential. His research has significant implications for understanding metabolic disorders, mitochondrial function, and potential therapeutic targets. Analysis of Dr. Abramson's publication record reveals a consistent focus on membrane protein structure-function relationships over the past two decades. His work demonstrates expertise in X-ray crystallography, cryo-electron microscopy, and functional assays to characterize transport proteins. Recent publications show increasing emphasis on mitochondrial biology, particularly VDAC structure and function, while maintaining his longstanding interest in sugar transport mechanisms. His research bridges fundamental biophysical principles with potential biomedical applications in metabolic diseases. Dr. Abramson has been awarded multiple NIH grants supporting his research, including the R35GM135175 grant titled 'Deciphering molecular details of cellular sugar transport and their roles in disease' (2020-2024), R01GM124783 'Functional and structural studies of unique pathogenic transporters involved in glycobiology' (2017-2021), and R01GM078844 'Structural and functional characterization of sugar transporters in health and disease' (2006-2020). As Principal Investigator, Dr. Abramson has mentored numerous graduate students and postdoctoral researchers. His laboratory has made significant contributions to understanding the structure-function relationships of membrane transport proteins through collaborations with researchers across multiple disciplines. The lab utilizes advanced techniques including X-ray crystallography, cryo-EM, electrophysiology, and computational modeling to address fundamental questions about membrane protein mechanisms. Dr. Abramson's laboratory is part of UCLA's broader research ecosystem focused on structural biology and membrane protein research. His work intersects with several research centers at UCLA including those focused on metabolic diseases and structural biology. The lab maintains active collaborations with researchers specializing in biophysics, computational modeling, and disease mechanisms to translate basic findings into potential biomedical applications.
Mahsan Nourani is a Research Assistant Professor at Northeastern University, specializing in intersections of human-computer interaction, artificial intelligence, and healthcare informatics. Their research focuses on explainable AI systems, user behavior in AI partnerships, and design of interactive machine learning tools. Current work explores cognitive biases in human-AI collaboration, predictive analytics in healthcare, and activity recognition in videos. Key research areas include user profiling in AI applications, trust dynamics in intelligent systems, and visual debugging tools for machine learning models. Notable projects include the HEART initiative for real-time healthcare analytics and development of the DETOXER explanation framework for temporal classification systems. Recent publications investigate nudge techniques for behavioral change (Romadoro project), anchoring bias effects in AI system trust, and evaluation of view rotation techniques in virtual reality navigation. Their work consistently bridges technical AI advancements with human-centered design principles. No academic awards are listed in the provided materials. Current affiliations include Northeastern University's research groups in AI ethics, human-computer interaction, and healthcare technology innovation.
Professor Katja Vogt is a distinguished faculty member in the Department of Philosophy at Columbia University's Faculty of Arts and Sciences. She serves as Professor of Philosophy, Director of the M.A. Program in Philosophy, and Chair of the Climate Committee. Additionally, she is an Affiliate of the Data Science Institute and has affiliations with Computing Systems for Data-Driven Science, Data, Media and Society, and Health Analytics. Professor Vogt joined Columbia University in 2002 after teaching at Humboldt University Berlin, both in the Philosophy Department and at the Charité Medical School. Professor Vogt specializes in ancient philosophy, ethics, and normative epistemology, with particular expertise in Plato, Aristotle, Stoicism, and Pyrrhonian skepticism. Her research explores fundamental questions that bridge ancient and contemporary philosophical discussions: What are values? What kind of values are knowledge and truth? What does it mean to want one's life to go well? She has developed significant work on the role of knowledge in ethics, generics and generalizations, and is currently finalizing a monograph entitled The Original Stoics . Her approach combines careful historical scholarship with contemporary philosophical analysis, creating dialogues between ancient texts and modern debates in metaethics, epistemology, and philosophy of action. Professor Vogt's scholarly output reveals consistent engagement with ancient philosophical frameworks while addressing contemporary concerns. Her recent work shows a particular focus on Stoic philosophy, with multiple papers examining Stoic logic, physics, and ethics. She also maintains a strong interest in skepticism, particularly Pyrrhonian approaches, and has made significant contributions to understanding how ancient philosophical concepts can inform current debates about generics, value theory, and the relationship between knowledge and virtue. Her collaborative work with Jens Haas on topics like ignorance, love, and hatred demonstrates her interdisciplinary approach that connects ancient philosophy with contemporary philosophical issues. Columbia Distinguished Faculty Award Class of 1932 Fellow in Classical Philosophy at Princeton University Fellowships from the Templeton Foundation, Maimonides Centre in Hamburg, Center for Advanced Studies in Munich, DFG (German Research Association), and Columbia University-Paris 1 Alliance Program Professor Vogt is actively involved in mentoring students and developing innovative educational approaches. She serves as academic sponsor for "Logic Made Accessible," a project mentored with Columbia College student Jonathan Tanaka that has reached students in over 30 countries. The project makes ancient logic freely accessible to learners of all ages, backgrounds, and interests. She has also served on numerous university committees including the Provost's Faculty Committee on Educational Innovation, Policy and Planning Committee, Committee on Instruction, and as Acting Director of the Center for the Ancient Mediterranean. Her grant work includes support from major foundations that have enabled her to pursue research at the intersection of ancient philosophy and contemporary epistemology. Professor Vogt collaborates with photographer and artist Jens Haas on the "On the Road" project, which combines artistic photography with philosophical reflection. She is also involved in "Movies and Morals," a collaboration with H8URS that provides philosophical commentary on contemporary film and television. These projects demonstrate her commitment to making philosophical inquiry accessible beyond traditional academic settings.
Brian Roberts is a Professor at Aston University's School of Psychology within the College of Health and Life Sciences. His primary research focuses on auditory perception, particularly auditory scene analysis and speech perception. He holds a PhD in Experimental Psychology (Auditory Perception) from the University of Cambridge (1989) and has held academic positions at the University of Birmingham (1993-2001) and Aston University since 2005. His work explores perceptual grouping mechanisms, cochlear implant listening, and the neural bases of auditory phenomena. Affiliations: Cognition & Neuroscience Research Group (CNRG), Centre for Vision and Hearing Research Employment History: Reader at University of Birmingham (2001), Senior Lecturer (1999), Lecturer (1993) Research interests include auditory stream segregation, formant analysis, and the effects of stimulus properties on perceptual organization. He has collaborated internationally, including visiting appointments at Macquarie University (2019) and the University of British Columbia (2011). Notable achievements include being elected a Fellow of the Acoustical Society of America (2009). Recent publications investigate factors influencing stream segregation (2024), asymmetric timbre effects (2023), and lexical bias in consonant identification (2022). Current projects explore sudden changes in auditory stimuli and their impact on perceptual grouping. Grants & Funding: Extensive research grants supporting auditory perception studies (details not explicitly listed) Supervised Work: 4 documented supervisees, though names not provided Labs/Teams: Active in the Auditory Perception Laboratory at Aston University, focusing on psychophysical and computational modeling approaches.
Yading Yuan, PhD is an Associate Professor of Radiation Oncology (Physics) at Columbia University Irving Medical Center and a member of the Data Science Institute. He holds a PhD in medical physics from the University of Chicago (2010) and completed clinical residency at Harvard Medical Physics Program (2013). His research focuses on AI-driven innovations in radiation oncology, including automated medical image analysis systems, federated learning frameworks for tumor segmentation, and data-driven approaches to personalized cancer treatment. He is certified by the American Board of Radiology and licensed in New York State. Education: PhD in Medical Physics (University of Chicago, 2010); Clinical Residency (Harvard Medical Physics Program, 2013). Research interests include: automated knowledge-based treatment planning, large-scale clinical AI systems, medical image reconstruction algorithms, and panomics integration for precision oncology. His work emphasizes translating data science advancements into clinical practice to improve patient outcomes. Key trends in his publications include federated learning for privacy-preserving medical AI, tumor segmentation in multi-modal imaging (PET/CT, MRI), and AI-driven prediction of treatment outcomes and recurrence risks. Recent work emphasizes decentralized learning architectures and cross-institutional collaboration systems. Scientific Awards: Distinguished Reviewers 2013 (selected by peer review committees) Advising/grants: No specific student names or grant details listed in provided text. His work is supported through institutional and collaborative research initiatives. Labs/teams: Active member of Columbia's Data Science Institute and Radiation Oncology department, contributing to interdisciplinary medical AI research groups.
Jian Tang is an Assistant Professor at HEC Montréal and a core member of the Montreal Institute for Learning Algorithms (MILA). His research focuses on graph representation learning, generative models, and their applications in drug discovery and material science. Prior to this, he was a postdoctoral researcher at the University of Michigan and Carnegie Mellon University, and a researcher at Microsoft Research Asia (2014-2016). He has received several prestigious recognitions, including the Canada CIFAR Artificial Intelligence Chairs (CCAI Chair) and best paper nominations at WWW’16. His work on LINE (WWW’15) was recognized as the most cited paper in its year. Tang’s research spans theoretical foundations and practical systems, such as GraphVite for scalable graph embedding and TorchDrug for drug discovery. Key research interests include geometric deep learning for molecular structures, generative models for protein design, and neural-symbolic reasoning for knowledge graphs. He actively collaborates with leading biological labs and leverages industry partnerships for GPU resources. Recent publications emphasize molecular property prediction, 3D conformation generation, and algorithmic reasoning frameworks. He has secured grants from IBM/MILA, Amazon, and the National Research Council Canada, supporting projects like molecular pretraining and geometric representation learning. Tang teaches courses on graph representation learning and deep learning, and mentors a vibrant team of PhD and master’s students. His lab has developed impactful software tools like LINE, PTE, and LargeVis, widely used in the research community.
An Verberckmoes is an Associate Professor at Ghent University in the Faculty of Engineering and Architecture, specifically within the Department of Materials, Textiles and Chemical Engineering. She is affiliated with multiple research units including the Biomolecules Center for Sustainable Chemistry, ChemTech Materials, and the Industrial Catalysis and Adsorption Technology group. Her research expertise centers on heterogeneous catalysis with a strong focus on sustainable chemical processes. Dr. Verberckmoes specializes in catalyst synthesis, particularly zeolite-based catalysts for bio-alcohol conversion and lignin valorization. Her work bridges fundamental catalyst design with practical applications in biomass conversion, aiming to develop more efficient and environmentally friendly processes for producing renewable chemicals and materials. Analysis of her recent publications (2024-2025) reveals a dominant research trajectory focused on lignin depolymerization technologies, with particular emphasis on catalytic approaches using noble and non-noble metals. She has made significant contributions to understanding reaction mechanisms in zeolite catalysis, especially for dehydration reactions of bio-alcohols to valuable chemicals like butadiene. Her work often combines experimental approaches with kinetic modeling to optimize both catalyst performance and process conditions. Dr. Verberckmoes collaborates extensively within Ghent University and with external partners on projects related to sustainable chemistry and biomass conversion. Her research group appears to focus on developing integrated approaches that combine catalyst design, process engineering, and advanced analytical techniques to advance lignin valorization and sustainable chemical production.
Professor Peter Wells is an Associate Professor at the University of Southampton, with a joint appointment at Diamond Light Source. His research focuses on operando spectroscopy, heterogeneous catalysis, and nanoparticle design. He coordinates the CHEM3054 module on Inorganic Materials Chemistry and holds a Fellow accreditation from the Higher Education Academy. Education: MChem in Chemistry (University of Surrey, 2003) PhD in tailored metal nanoparticle preparation and characterization (University of Southampton, 2007) His research integrates advanced X-ray techniques (e.g., X-ray absorption spectroscopy) with computational methods like DFT simulations to study catalyst dynamics. Key areas include stabilizing structural changes in palladium nanoparticles and designing nanoparticle catalysts for sustainable chemical production from waste biomass. He collaborates with the UK Catalysis Hub and serves on peer-review panels for Diamond Light Source and the Swiss Light Source. Active Research Projects (EPSRC): Core Equipment 2024 (£1.26M, PI) Nitridic and Carbidic Pd Nanoparticles for Directed Catalysis Peter supervises multiple PhD students in Chemistry and actively mentors researchers through collaborative grants. His work bridges experimental and theoretical approaches to catalysis, emphasizing real-time structural analysis under operational conditions.
Ivon Arroyo is a Professor in the Department of Teacher Education & Curriculum Studies (TECS) at the University of Massachusetts Amherst. Her research focuses on integrating novel technologies into math and computational thinking education, emphasizing affective and metacognitive states. She develops intelligent tutoring systems, such as COVES, which personalize learning in real-time and utilize facial expression recognition to enhance engagement. Her work on WearableLearning explores embodied, physically active multiplayer games for K-12 classrooms, leveraging mobile devices and wearable technologies to create immersive learning experiences. Dr. Arroyo holds an Ed.D. (2003) and M.S. (2000) from UMass Amherst and a B.S. from Universidad Blas Pascal in Argentina (1995). She has been recognized with multiple awards, including Best Paper Awards at the 2009 International Conference on Artificial Intelligence in Education and the 2010 Educational Data Mining Conference, a Fulbright Fellowship (1996), and a 1994 undergraduate prize for computer vision research. Her research interests span interdisciplinary areas such as Learning Sciences , Computer Science , Data Science , and Psychology . She prioritizes culturally responsive pedagogical agents and cross-cultural studies in educational technology, particularly in Argentina, India, and the U.S. Her projects often address challenges in developing countries, including localization of tutoring systems to Spanish. Advising and grants are central to her work, with grants like the NSF CAREER Award (2020) supporting embodied math classrooms. She collaborates on teacher dashboard frameworks and explores ethical AI integration in education. Her labs focus on creating tools that merge computational innovation with theoretical learning science principles, emphasizing real-world applications like the WearableLearning Cloud Platform.
Josh McDermott is a Professor in the Department of Brain and Cognitive Sciences at MIT and an Associate Investigator at the McGovern Institute. He holds roles as Associate Department Head and Principal Investigator of the Laboratory for Computational Audition. His work bridges psychology, neuroscience, and engineering to study auditory perception, with a focus on sound interpretation, hearing impairment treatments, and machine hearing systems. Education includes a B.A. from Harvard (summa cum laude), an MPhil from University College London, and a PhD from MIT. Postdoctoral training included NYU and the University of Minnesota. Research interests encompass computational principles of sound perception, natural sound statistics, music cognition, and machine hearing. Key areas include sound localization, auditory scene analysis, and the role of generative models in perception. Recent publications highlight advancements in auditory neural networks, cross-cultural music perception, and noise schema processing. Awards include the Troland Research Award, BCS Excellence in Advising, and NSF CAREER Award. Advising includes over 20 graduate students and postdocs, with notable contributions to auditory neuroscience and machine learning. Major grants support projects on auditory models and sensory systems. The lab develops tools like cochleagram generation and headphone screening software. The Laboratory for Computational Audition operates at MIT, focusing on biological and computational approaches to hearing. Collaborations span engineering, psychology, and neuroscience to advance understanding of auditory processing.
