Anna Grigolon is an Assistant Professor at the University of Twente , Netherlands, affiliated with the Transport Engineering and Management Research Group . Her research focuses on sustainable urban mobility , user-centric transport solutions , and travel behavior analysis using tools like discrete choice modeling , spatial analysis , and social psychology theories . Research Interests : Sustainable Urban Mobility Accessibility Modeling Travel Behavior Discrete Choice and Latent Class Modeling Spatial Analysis and GIS Shared Micromobility and Mobility Hubs Equity in Transport Planning Article Trends : Anna’s recent work (2025–2024) emphasizes mobility justice , 15-minute city transitions, and equity in transport access , particularly for marginalized communities like São Paulo favelas. She integrates digital tools (e.g., serious games, kiosks) and space-time metrics to evaluate mobility solutions. Projects : She currently leads the SmartHubs project and contributes to DREAMS and R-map , focusing on smart, equitable mobility systems in Europe and Saudi Arabia.
Jo Wood is Professor of Visual Analytics in the Department of Computer Science at City, University of London, where she has been employed since January 14, 2000. Her work bridges computer science, geographic information science, and human-computer interaction, focusing on innovative methods for visualizing complex spatial and behavioral data. Her research interests center on visual analytics , information visualization , and geovisualization , with applications in transportation, public health, crisis response, and citizen science. She investigates how interactive visual interfaces can support exploratory data analysis, decision-making, and storytelling, particularly through small multiples, faceted views, and sketch-based rendering techniques. The trends in her recent publications reflect a consistent focus on user-centered design , spatial data abstraction , and interactive exploration of multivariate datasets. Her work often integrates real-world behavioral data such as GPS tracks, cycling patterns, and crowd-sourced information to build meaningful visual narratives and support analytical reasoning. Throughout her career, Jo Wood has contributed significantly to the advancement of visual analytics through high-impact publications in top-tier venues such as IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum. Her collaborations with researchers like Jason Dykes and Aidan Slingsby highlight her role in a vibrant research community. She has supervised numerous research projects and mentored students in visualization and geospatial analytics, though specific names are not listed in the provided text. Her work has been supported by various research grants, particularly in domains involving urban mobility, energy modeling, and crisis informatics, though grant details are not specified here. Jo Wood has also contributed to the design of visual analytics systems for applications including disease spread modeling, bicycle-hire scheme monitoring, and persuasive technology for health and leisure, demonstrating a strong commitment to impactful, interdisciplinary research.
Stephen Marshall is Professor of Urban Morphology and Urban Design at The Bartlett School of Planning, University College London. He also served as Visiting Professor at the Department of Architecture and Urban Studies, Politecnico di Milano, Italy from 2019 to 2021. With over twenty-five years of experience in the built environment fields, initially in consultancy and subsequently in academia, Professor Marshall has established himself as a leading expert in urban morphology and design. His educational background includes a Doctor of Philosophy from University College London (2001), a Postgraduate Diploma from Edinburgh College of Art (1995), a Master of Science from the University of Leeds (1989), and a Bachelor of Engineering from the University of Glasgow (1988). Professor Marshall's principal research focuses on urban morphology and street layout, examining their relationships with urban formative processes including urban design, coding and planning. His work bridges urban design theory with practical applications, exploring how cities evolve through complex interactions of physical form, social processes, and planning interventions. He has written or edited several influential books including 'Streets and Patterns' (2005), 'Cities, Design and Evolution' (2009), and 'Urban Coding and Planning' (2011). His recent publications reveal a growing interest in applying complexity science to urban morphology, with particular attention to biological analogies for understanding self-organizing cities. He has pioneered research on digital participation methods in urban planning, exploring how online platforms can enhance public engagement in urban space design. His work consistently bridges theoretical urban morphology with practical applications for contemporary urban challenges like pandemic adaptation and sustainable transport. Professor Marshall has served as Chair of the Editorial Board of Urban Design and Planning from its launch to 2012, and is now co-editor of Built Environment journal. His editorial work has significantly shaped scholarly discourse in urban planning and design. He leads several significant research initiatives including the Incubators of Public Spaces project, which explores digital platforms for co-creating urban spaces, and the Self-Organising Built Environment project, which investigates biological analogies in urbanism. These projects reflect his interdisciplinary approach to understanding and shaping urban environments, connecting with Sustainable Development Goal 11 (Sustainable Cities and Communities).
Sarah Ita Levitan is an Assistant Professor in the Department of Computer Science at Hunter College, CUNY, and a member of the doctoral faculty in both Computer Science and Linguistics PhD programs at the CUNY Graduate Center. She previously served as a Postdoctoral Research Scientist at Columbia University, where she completed her PhD in Computer Science in 2019 under Dr. Julia Hirschberg. Research Focus: Spoken Language Processing Natural Language Processing Paralinguistic Analysis Trustworthiness and Deception Detection Acoustic-Procedic and Lexical Feature Extraction Online Radicalization and Misinformation Recent Publications demonstrate expertise in analyzing speech and text for trust cues, deception detection, and mental health prediction. Her awards include grants from NSF, Google, and Columbia University fellowships. She leads the Hunter Speech Lab , mentoring PhD, MS, and undergraduate students in computational linguistics research. Scientific Awards and Grants: NSF EAGER Grant (2023) Google Cyber NYC Grant (2023) NSF AI Institute Grant (2023) Air Force Office of Scientific Research Grant (2020) Brown Institute Seed Grant (2020) Knight News Innovation Fellowship (2018) Teaching: Courses include Natural Language Processing (undergraduate/graduate), Computational Linguistics, Computer Theory, and advanced topics in spoken language processing at both Hunter College and Columbia University.
Jaime S. Cardoso is an Associate Professor with Habilitation at the Faculty of Engineering of the University of Porto (FEUP) and a Senior Researcher in the 'Information Processing and Pattern Recognition' Area at INESC TEC's Telecommunications and Multimedia Unit. He has been serving as Research Coordinator since September 15, 1998, and is a Senior Member of IEEE as well as co-founder of ClusterMedia Labs. His educational background includes a Licenciatura in Electrical and Computer Engineering (1999), an MSc in Mathematical Engineering (2005), and a Ph.D. in Computer Vision (2006), all from the University of Porto. Cardoso's research focuses on three major areas: computer vision, machine learning, and decision support systems. His work spans medical image analysis, explainable AI, semantic audio-visual analysis, and pattern recognition. He has co-authored over 150 papers, with more than 50 published in international journals, and has accumulated over 6,500 citations. His recent publications demonstrate expertise in cell nuclei segmentation, ordinal regression for CNNs, semantic segmentation with ordinal relationships, face recognition using synthetic data, and explainable vision language models for medical applications. Honorable Mention in the Exame Informática Award 2011 for 'Semantic PACS' First Place in the ICDAR 2013 Music Scores Competition Cardoso has supervised numerous graduate students at UP-FEUP, with recent theses focusing on multimodal explanations, autonomous driving, medical diagnosis, and explainable AI. His research group works at the intersection of computer vision, machine learning, and practical applications in healthcare and autonomous systems.
Michael C. Frank is the Benjamin Scott Crocker Professor of Human Biology at Stanford University and Director of the Symbolic Systems Program. He leads the Stanford Language and Cognition Lab and has pioneered large-scale collaborative projects including Wordbank (open vocabulary data), MetaLab (developmental meta-analyses), ManyBabies (replication network), childes-db (language transcripts), and Peekbank (eye-tracking repository). His research examines children's language learning and its interaction with social cognition, utilizing computational modeling, large datasets, and open science frameworks. Key interests include: Mechanisms of early language acquisition Pragmatic inference in social contexts Cross-cultural variability in cognitive development Data-driven approaches to developmental science Reproducibility and meta-scientific innovation Recent publications (2022-2025) demonstrate strong emphases on: 1) Novel methods for measuring language environments and cognitive abilities, 2) Computational models of learning and perception, 3) Cross-cultural investigations of social cognition, and 4) Infrastructure for open developmental science. The majority employ multimodal data, meta-analytic techniques, and large-scale collaborations. He teaches courses including Experimental Methods, Developmental Psychology, and interdisciplinary seminars on language, cognition, and computation. His lab maintains active research teams across multiple continents through initiatives like ManyBabies and LEVANTE.
James Tung is an Associate Professor at the University of Waterloo’s Faculty of Engineering, Department of Mechanical and Mechatronics Engineering. His research focuses on assistive technology, rehabilitation engineering, and mobility solutions for individuals with disabilities. He leads the Neural and Rehabilitation Engineering (NRE) Lab, which develops wearable sensors, robotics, and machine learning tools to enhance mobility and monitor motor rehabilitation. He teaches courses including BME 355 (Physiological Systems Modelling), BME 540 (Neural and Rehabilitation Engineering), and ME/MTE engineering modules. The lab collaborates with clinical and industry partners to translate research into practical solutions, addressing real-world mobility challenges and aging demographics. His research spans real-world gait analysis, fall risk assessment, and prosthetic design, with a focus on pediatric neurodevelopmental disorders and elderly mobility. The NRE Lab emphasizes interdisciplinary work, combining biomechanics, robotics, and data science to improve healthcare outcomes. Lab Alumni: Includes researchers like Robin Murdock (Myant Inc.), Andrew Hart, and Raj Senthilkumar, contributing to prosthetics and gait analysis. Partnerships: Engages clinical and industry stakeholders for knowledge translation and commercialization. Current projects include developing smart rollators, biofeedback prosthetics, and sensor-based assessment tools to address mobility limitations in aging populations and individuals with disabilities.
Xia Ben Hu is a Professor in the Department of Computer Science at Rice University's Brown School of Engineering. He leads research in automated and interpretable machine learning algorithms with applications across social informatics, health informatics, and information security. His work has resulted in widely adopted systems including AutoKeras, TODS, and RLCard. Education: PhD from Arizona State University (supervised by Dr. Huan Liu) Master and Bachelor degrees from Beihang University Prof. Hu's research focuses on developing automated and interpretable machine learning algorithms for large-scale, networked, dynamic and sparse data. His work spans automated machine learning (AutoML), deep learning, fairness in AI, time series analysis, and interpretable AI. He has made significant contributions to neural architecture search, collaborative filtering, anomaly detection, and reinforcement learning in imperfect information games. His publication record shows a clear progression from foundational work in network embedding and collaborative filtering (2017) to more recent work on LLM optimization, quantization, and extending context windows (2024). A consistent thread throughout his research is the focus on making complex machine learning systems more accessible, efficient, and interpretable. Selected Awards: ACM SIGKDD Rising Star Award (2021) NSF CAREER Award (2018) Teaching + Research Excellence Award, Rice University (2023) Multiple Best Paper Awards at top venues including ICML, CIKM, and AMIA Prof. Hu has successfully mentored numerous graduate students, with recent graduates securing tenure-track positions at major universities. His research is generously supported by federal agencies including DARPA (XAI, D3M, NGS2), NSF (CAREER, III, SaTC), NIH, and industrial sponsors such as Adobe, Apple, Google, LinkedIn, and JP Morgan. He has served as General Co-Chair for WSDM 2020 and ICHI 2023, and Program Chair for AIHC 2024. He leads the DATA Lab at Rice University, which develops open-source systems for automated machine learning and reinforcement learning. The lab's AutoKeras system has over 8,000 GitHub stars and 1,000 forks, and their work has been integrated into TensorFlow, Apple production systems, and Bing production systems.
Deen Freelon is the Allan Randall Freelon Sr. Presidential Professor at the University of Pennsylvania's Annenberg School for Communication, where he leads research in digital politics and computational methods. His work centers on identity dimensions in social media, misinformation ecosystems, and political communication. Previously, he held tenured positions at American University and the University of North Carolina at Chapel Hill. Freelon earned a B.A. with honors from Stanford University (2002), followed by an M.A. (2008) and Ph.D. (2012) from the University of Washington. His endowed chair honors his great-grandfather, Allan Randall Freelon Sr., a Penn alumnus and prominent Philadelphia artist. Freelon's research explores intersections of technology and society with emphases on: Computational analysis of social media discourse Race, gender, and ideological asymmetry in online spaces Misinformation propagation and mitigation strategies Impact of personalized information environments on democracy His publications consistently address how digital platforms reshape political engagement and identity expression. Freelon has secured over $6 million in research funding from organizations including the Knight Foundation, Hewlett Foundation, Spencer Foundation, and US Institute for Peace. As a founding member of UNC Chapel Hill's Center for Information, Technology, and Public Life, he contributes to interdisciplinary efforts examining technology's societal impacts.
Somayeh Dodge is an Associate Professor of Spatial Data Science in the Department of Geography at the University of California, Santa Barbara (UCSB). She leads the MOVE Lab and serves as Co-Associate Director of the UCSB Center for Spatial Studies and Data Science. Her research focuses on computational movement analysis, spatiotemporal data science, and the application of these tools to study human and ecological systems. She holds editorial roles in major journals including Journal of Spatial Information Science and Geographical Analysis. Education: PhD in GIScience (University of Zurich, 2011), MS in GIS Engineering (K.N.Toosi University of Technology, 2005), and BS in Geomatics Engineering (2003). Postdoctoral work at The Ohio State University and University of Zurich. Prior faculty positions include University of Minnesota (2016–2019) and University of Colorado, Colorado Springs (2013–2016). Research interests include wildfire impact analysis, mobility patterns during disasters, environmental vulnerability modeling, and geovisualization techniques. Her NSF CAREER project explores movement responses to environmental disruptions. Teaching focuses on GIScience, movement analytics, and spatial modeling courses. Awards: 2021 NSF CAREER Award and 2022 AAG Emerging Scholar Award. Active in editorial boards for multiple journals and serves on the Board of Directors for the University Consortium for Geographic Information Science (UCGIS). Advising: Supervises 7 graduate students in mobility analytics and environmental modeling. Labs/Teams: MOVE Lab (https://move.geog.ucsb.edu/) focuses on computational movement ecology and human mobility studies.
Dongwook Yoon is an Associate Professor at the Department of Computer Science , University of British Columbia , and serves as Director of the SOCIUS Lab . He actively contributes to research in Human-Computer Interaction, Human-AI Interaction, and Virtual/Augmented Reality as a member of the Designing for People (DFP) and CAIDA research clusters. Education : PhD in Computer Science from Cornell University (2017), MS (2009) and BS (2007) in Computer Science from Seoul National University Research Focus : Designing socio-technical systems that bridge the gap between technology and human social processes, with innovations in AR/VR, multimodal interaction, and inclusive design Article Trends show his work spans: Temporal and bichronous learning environments AI self-clones and ethical implications Income inequality in virtual platforms Enhanced multimodal collaboration in VR Eyes-reduced interfaces for situational impairments Speculative participatory design for gig economy challenges Scientific Awards include: Google Academic Research Award (2024) Best Paper Award at CHI 2024 High Impact Award in Educational Technology (2024) CHCCS/SCDHM Graphics Interface Early Career Award (2023) Multiple Honorable Mentions at CHI, DIS, and CSCW Students & Collaborators range from active PhD candidates (Anika Sayara, Yuri Kim) to notable alumni (Thitaree Tanprasert, Ashish Chopra) across his SOCIUS Lab projects. His research receives funding from NSERC , KIST , Adobe , Microsoft , and Google grants.
Claudia Wagner is a full professor for Applied Computational Social Sciences at RWTH Aachen University and the Scientific Director of the Computational Social Science department at GESIS—Leibniz Institute for the Social Sciences. She is also an External Faculty member at the Complexity Science Hub Vienna. Her work bridges computer science and the social sciences to study algorithmic systems and their societal impacts. Her research focuses on socio-technical phenomena such as inequality, sexism, and perception bias in algorithmically infused societies. She investigates methodological challenges in using digital behavioral data to study human behavior, attitudes, and group dynamics. Her interests span computational social science, algorithmic fairness, network science, and AI ethics. The analysis of her recent publications reveals a strong emphasis on bias, fairness, and methodological rigor in digital data analysis. Her work spans AI psychometrics, gender inequality in online platforms, and validation frameworks for digital traces. She frequently publishes in top-tier venues such as Nature , Science , and AAAI conferences. DOC-fFORTE fellowship from the Austrian Academy of Sciences Four best paper awards at international conferences (ICWSM, CSCW, WWW, AAAI) Associate Editor, EPJ Data Science Steering Committee Member, International AAAI Conference on Web and Social Media Board Member, International Society for Computational Social Science Claudia Wagner has led and co-led substantial research projects funded by national and international agencies. She mentors a diverse group of PhD students working on topics like algorithmic bias, data quality, and dehumanization. She has organized training events such as the CSS Methods Summer School and delivered keynotes globally on inequality and computational social science. She leads the Computational Social Science department at GESIS and collaborates with interdisciplinary teams at RWTH Aachen and the Complexity Science Hub. Her group develops tools for measuring algorithmic impacts and visualizing disparities in socio-technical systems, such as the 'Planets of Disparity' dashboard.
Professor Matthew James Keeling is a distinguished academic at the University of Warwick, where he serves as Director of the Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research (SBIDER). He holds a professorship in the Department of Mathematics within the School of Science, specializing in mathematical modeling of infectious disease dynamics. His work bridges theoretical mathematics with practical public health applications, making significant contributions to epidemic prediction and control strategies. Professor Keeling's educational background includes a B.A. in Mathematics (1991), Master in Mathematics (1992), and PhD in Mathematical Modelling (1995). His career progression at Warwick shows steady advancement from Lecturer (2002) to Reader (2005) and finally to Professor (2007), supported by prestigious fellowships including the Royal Society University Research Fellowship (1998-2006) and Wellcome Trust Fellowship (1995-1998). His research focuses on mathematical models for infectious disease transmission, with particular expertise in network-based approaches to understanding how diseases spread through populations. Keeling has applied his modeling expertise to numerous outbreaks including the 2001 Foot-and-Mouth Outbreak, 2009 Swine flu pandemic, and most notably the COVID-19 pandemic. His work spans both human and animal diseases, covering pathogens such as influenza, measles, HPV, and various livestock infections. Analysis of Professor Keeling's publications reveals a strong emphasis on network theory applied to epidemiology, with significant contributions to understanding cattle movement networks, human social contact patterns, and spatial disease dynamics. His work consistently bridges theoretical mathematics with practical disease control applications, demonstrating how mathematical models can inform real-world policy decisions regarding vaccination strategies and outbreak control measures. Scientific Awards and Recognitions: Royal Society University Research Fellowship (1998-2006) Wellcome Trust Fellowship (1995-1998) Professor Keeling has been actively involved in advising government agencies during major disease outbreaks, including providing critical modeling input during the COVID-19 pandemic. His work on HPV vaccination cost-effectiveness directly influenced policy decisions regarding gender-neutral vaccination programs. He maintains an active research group focused on developing novel mathematical approaches to infectious disease modeling, with particular interest in household transmission dynamics and the impact of network structure on disease spread. The Zeeman Institute (SBIDER), which he directs, serves as a hub for interdisciplinary research connecting mathematical sciences with biological and medical applications.
Professor Brendan Choat is a leading plant physiologist and Professor at the Hawkesbury Institute for the Environment, Western Sydney University. With a distinguished career in plant hydraulics and water relations research, he has established himself as a global expert in understanding how plants respond to drought stress. His work spans both natural ecosystems and agricultural systems, with particular emphasis on Australian native forests and crop species. Choat's research focuses on the intricate relationship between plant water transport systems and environmental stressors, particularly drought. His work examines how the xylem tissue functions as a hydraulic system that must balance water delivery to leaves while avoiding cavitation (embolism) that can lead to plant mortality. His groundbreaking research has demonstrated that many woody plant species operate close to their physiological safety margins with respect to drought, making them vulnerable to future climate changes. His laboratory employs cutting-edge non-invasive imaging techniques, including X-ray Micro Computed Tomography (microCT) and Magnetic Resonance Imaging (MRI), to directly visualize xylem function in living plants. This approach has allowed his team to address fundamental questions about how cavitation forms and spreads through plant vascular systems during drought stress. Analysis of Professor Choat's extensive publication record reveals a consistent focus on plant drought responses, with particular emphasis on Eucalyptus species and mangrove ecosystems. His research has increasingly incorporated large-scale monitoring approaches, remote sensing data, and trait databases to understand vegetation responses to climate extremes across broader spatial scales. Clarivate Highly Cited Researcher (2018-2024) ARC Future Fellowship (2013) Humboldt Fellowship for Experienced Researchers (2010) Thomson Reuters Citation and Innovation Award (2015) Professor Choat leads multiple significant research projects examining tree dieback in Australian forests, particularly focusing on Eucalyptus species. His work with citizen scientists through the 'Dead Tree Detective' project has provided valuable data on drought impacts across diverse forest biomes. He maintains active collaborations with researchers across Australia and internationally, contributing to large-scale initiatives like the AusTraits plant trait database. His research has direct implications for forest management, conservation strategies, and predicting ecosystem responses to climate change.
Rebecca A. Kobrin serves as the Russell and Bettina Knapp Associate Professor of American Jewish History at Columbia University, actively contributing to scholarship and pedagogy as of 2025. Her research bridges immigration history, urban studies, and Jewish diaspora studies, with leadership in the award-winning Historical NYC Project that digitally reconstructs New York City's demographic evolution from 1850 to 1940. Her academic credentials include: Ph.D. from the University of Pennsylvania (2002) M.S. Ed. from University of Pennsylvania, School of Education (2000) M.A. from University of Pennsylvania (1995) B.A. from Yale University (1994) Professor Kobrin's research interrogates the socioeconomic dimensions of East European Jewish migration through interdisciplinary lenses, examining financial networks, urban spatial dynamics, and transnational philanthropy. Her work reveals how immigrant communities navigated economic vulnerability while maintaining diasporic connections, particularly through landsmanshaftn (mutual aid societies) and cross-border capital flows. Digital humanities methodologies enhance her analysis of urban settlement patterns and demographic shifts. Her scholarly output demonstrates consistent focus on Jewish immigrant economic agency, with recurring themes of financial failure, gendered household economies, and diaspora responses to geopolitical upheavals like the 1905 Russian Revolution. Publications frequently analyze Yiddish press representations of Eastern European cities and transnational philanthropy during interwar crises. Major recognitions include: Jordan Schnitzer Prize (2012) for Jewish Bialystok and Its Diaspora Columbia University’s Lenfest Distinguished Faculty Award (2015) American Jewish Historical Society’s Wasserstein Prize (2013) Shoah Foundation Teaching Award (2012) National Jewish Book Awards Finalist (2010) Professor Kobrin’s mentorship earned Columbia’s Lenfest Award for graduate student guidance, supported by fellowships from the American Philosophical Society, ACLS, and Fulbright programs. Her current flagship initiative—the Historical NYC Project—secures multidisciplinary funding to visualize urban transformation through interactive cartography. As principal investigator, she directs collaborative research integrating historical archives with spatial analysis. The Historical NYC Project team unites historians, data scientists, and cartographers in creating an acclaimed digital platform mapping New York City’s demographic metamorphosis across 90 years, revealing how immigrant communities reshaped urban landscapes through settlement patterns and institutional development.
