David Easley is the Henry Scarborough Professor of Social Science and Professor of Information Science at Cornell University, affiliated with the Department of Economics and the Department of Information Science. His research spans economics, finance, and network science, focusing on market microstructure, asset pricing, and the interplay between networks and economic behavior. Developed the VPIN metric for detecting flow toxicity in financial markets Co-authored the influential textbook "Networks, Crowds and Markets: Reasoning About a Highly Connected World" Collaborates extensively with computer scientists on network formation and trading dynamics His work combines economic theory with computational approaches to analyze market behavior and network structures. The research covers both theoretical foundations and practical applications in financial systems. Scientific awards include the William F. Sharpe Award for Scholarship in Financial Research (2017). He has co-developed innovative AI-centered courses at Cornell and contributes to the emerging field of computational social science that integrates economics, sociology, computing, and mathematics.
Jackelyn Hwang is an Associate Professor at the Department of Sociology, Stanford University, and Director of the Changing Cities Research Lab. Her work bridges urban sociology, racial inequality, and computational methodologies to study contemporary urban transformation. PhD in Sociology and Social Policy, Harvard University AM in Sociology, Harvard University BAS in Sociology and Mathematics, Stanford University Her research focuses on racialized urban change , gentrification dynamics , and computational social observation . Using tools like Google Street View imagery and computer vision, she examines neighborhood conditions, displacement patterns, and policy implications for equity. Recent publications analyze visible neighborhood conditions (2023), residential mobility during gentrification (2025), and ethnoracial property ownership patterns (2025). She has developed scalable measurement frameworks and advised policymakers on housing instability. Jane Addams Award for Best Article (2021) Recipient of NSF and Joint Center for Housing Studies grants Collaborations with Federal Reserve Bank and Oakland's Housing Department As lab director, she mentors PhD students in computational urban research. Her work appears in American Journal of Sociology , Demography , and Sociological Methodology , with policy briefs on rent control and homelessness prevention.
Sina Julia Blassnig is a Full Professor at the Institute of Digital Communication and Media Innovation (IDCMI), University of Fribourg. Her research focuses on digital journalism , populist communication , and news recommender systems . She explores intersections between media systems , AI ethics , and user behavior in digital environments. Research Interests: Digital media systems Political communication Populist rhetoric Algorithmic journalism AI in news production Media effects Projects: Generative Visual AI in Swiss Journalism (FNS-funded, 2026–2030): Examines AI-generated visuals in journalism. Gratis-Abos für Jugendliche (2024–2026): Evaluates free subscription models in Swiss media. Crowding Out (completed 2025): Analyzed SRF News' impact on private media. Labs/Teams: Affiliated with the Medialab and IDCMI , focusing on digital communication innovation.
Dr. Alpha Lee is a Winton Advanced Research Fellow at the Cavendish Laboratory, University of Cambridge, with affiliations to St Catharine's College. His research spans astrophysics and biological matter, supported by the TCM (Theory of Condensed Matter) Group. University of Cambridge Cavendish Laboratory TCM Group St Catharine's College Fellow Lee's work focuses on astrophysical data analysis, particularly Gaia mission datasets, while also exploring biological and soft matter interactions. His research includes celestial reference frames, stellar multiplicity, and diffuse interstellar band mapping. Recent publications highlight Gaia's contributions to extragalactic studies, chemical cartography, and binary star analysis. Lee has contributed to key Gaia data releases (DR3, EDR3) and specialized catalogs. Winton Advanced Research Fellow Fellow of St Catharine's College Lee's research group at Cavendish Laboratory collaborates on Gaia data processing pipelines and cosmic structure analysis, leveraging advanced computational astrophysics techniques.
Gabriel Draughon serves as an Assistant Teaching Professor in the Engineering Fundamentals department at Michigan Technological University, holding a PhD and MS in Civil Engineering/Intelligent Systems from the University of Michigan alongside a BS in Biosystems Engineering from the University of Kentucky. His academic profile bridges cutting-edge urban sensing research with innovative engineering education methodologies. PhD, Civil Engineering/Intelligent Systems, University of Michigan MS, Civil Engineering/Intelligent Systems, University of Michigan BS, Biosystems Engineering, University of Kentucky Draughon's research centers on computer vision applications for urban environments, with dual emphases on intelligent infrastructure monitoring and public health crisis response. His work in urban sensing spans multi-person tracking systems for public spaces, multimodal human activity mapping in social infrastructure, and autonomous methane emission monitoring at landfills. During the pandemic, he pivoted to develop computer vision frameworks for face mask compliance tracking and social distancing measurement, demonstrating remarkable adaptability of his core methodologies to emergent societal challenges. His educational research investigates self-efficacy and novel pedagogical approaches in engineering fundamentals. Analysis of his 2018-2022 publications reveals a cohesive research trajectory where computer vision and sensor technologies address increasingly complex urban challenges. Early work focused on environmental monitoring (landfill methane emissions), evolving toward sophisticated human behavior analysis in public spaces. The pandemic accelerated applications in public health surveillance, with consistent use of deep learning frameworks like DeepSORT. His research consistently bridges civil engineering infrastructure with intelligent systems, showing particular strength in adapting computer vision to real-world constraints of outdoor urban environments. Draughon maintains active engagement in student development through undergraduate mentoring (2020-2022), the Sensors in a Shoebox program (2018-2020), and Discover Engineering initiatives (2019, 2022). His teaching portfolio includes curriculum design for K-12 programs at The School at Marygrove and Jalen Rose Leadership Academy, plus graduate instruction at the University of Michigan, reflecting his commitment to engineering education across multiple levels. His collaborative research with Jerome Lynch and other colleagues forms a cohesive intelligent infrastructure research stream, though specific lab affiliations aren't detailed. Current work appears focused on scaling computer vision applications for smart city infrastructure while maintaining his educational research in engineering fundamentals pedagogy.
Owen Waygood is a Full Professor in the Department of Civil, Geological and Mining Engineering at Polytechnique Montréal. He holds a PhD in Transportation Behavior from Kyoto University (2009), an MA in Biomimicry from the University of Toronto (2005), and dual BSc degrees in Mechanical Engineering and Computer Science from the University of Saskatchewan (2001). His research spans transportation engineering, sustainable mobility, and the intersection of urban environments with social, environmental, and economic impacts on travel behavior. PhD in Transportation Behavior and Urban Management, Kyoto University, 2009 MA in Biomimicry, University of Toronto, 2005 BA in Computer Science and BE in Mechanical Engineering, University of Saskatchewan, 2001 Waygood’s work focuses on transport and well-being, traffic hazard assessment tools, sustainable development in transportation, and children’s mobility. He has developed machine learning techniques for traffic danger evaluation, studied carbon dioxide information framing in transport decisions, and analyzed pedestrian safety at urban intersections. His research often integrates public health, environmental psychology, and urban design. Recent publications examine autonomous taxi adoption, pedestrian risk factors, and household greenhouse gas emissions. He collaborates with institutions like CIRRELT and CIRODD, and has supervised 10 graduate students. Media engagements highlight his expertise in Montreal’s infrastructure challenges, including REM metro reliability, winter cycling adoption, and car ownership trends. He co-developed a hazard assessment tool for Montreal intersections and contributed to pandemic-era mobility studies. Owen leads projects like the Road Safety Research Network (RRSR) and participates in the Interdisciplinary Research Center for Operationalization of Sustainable Development (CIRODD) . His supervision includes studies on traffic danger analysis, park accessibility, and machine learning optimization. He has been featured in 98.5 FM, La Presse, CBC, and Le Devoir for insights on child pedestrian safety, sustainable transport, and urban planning.
Georgia Fargetta is a Research Fellow (RTD-A) in Computer Science at the Department of Mathematics and Computer Science, University of Catania, Italy. She holds a PhD in Computer Science (2022) and both Bachelor's (2017) and Master's (2019) degrees in Mathematics from the University of Catania. Current academic affiliation: Department of Mathematics and Computer Science, University of Catania Academic rank: Research Fellow RTD-A (INF/01) Research themes: Optimization, Machine Learning, Game Theory, and applications to supply chain networks and crowd evacuation modeling Research Interests Georgia's research spans multiple domains including: Optimization Game Theory Metaheuristic Algorithms Crowd Simulation Medical Supply Chain Her publications demonstrate expertise in applying these methodologies to diverse problems such as social media content competition, emergency evacuation planning, and medical supply allocation. The scientific awards section highlights: Young Women in Operations Research Award (EURO WISDOM, 2021) Young Women for Operational Research (2022) She actively participates in international conferences including ODS, EUROPT, and MIC. As member of IPLAB (Image Processing Laboratory), she contributes to research in Computer Vision and Multimedia.
Anna Wang is an Associate Professor at the University of New South Wales (UNSW) , based in the School of Chemistry within the Faculty of Science . Her interdisciplinary research bridges physics, chemistry, materials science, and astrobiology to explore the behavior of soft matter and the origins of cellular life . Dr. Wang holds a BSc (Advanced Hons I) from the University of Sydney (2009) , followed by an SM (2013) and PhD (2016) in Applied Physics from Harvard University . She was a NASA Postdoctoral Program Fellow in Astrobiology at Massachusetts General Hospital (2016–2018). Her research focuses on understanding how simple physical and chemical systems can give rise to life-like behaviors. Key research themes include: Self-assembly of lipid membranes and protocells Holographic microscopy for 3D tracking of soft matter Biophysical principles of membrane stability and dynamics Origins of cellular life and prebiotic chemistry Colloidal interactions and phase-separated systems Dr. Wang’s lab uses advanced imaging techniques such as digital holographic microscopy to study the 3D motion and interactions of colloidal particles, vesicles, and protocells. Her work has been published in high-impact journals including PNAS , Nature Communications , ACS Nano , and Soft Matter . Grants & Funding: Human Frontier Science Program (HFSP) Collaborative Research Grant (2020–2023) Australian Research Council Discovery Early Career Research Award (2021–2023) Alfred P. Sloan Foundation “Matter to Life” Grant (2023–2027) Gordon and Betty Moore Foundation Grant (2023–2027) Teaching & Supervision: Dr. Wang teaches courses such as CHEM2921 (Food Chemistry) , CHEM3061 (Chemistry of Materials) , and CDEV3000 (Practice of Work) . She actively supervises Honours, Masters, and PhD students interested in soft matter and origins of life research. Public Engagement: Dr. Wang has contributed to science communication through appearances on PBS Nova , ABC Catalyst , Vox Unexplainable , and public seminars. Her lab website is https://www.annawanglab.com .
Peter Van den Broeck is a Professor and Department Vice Chair in the Department of Civil Engineering at KU Leuven's Faculty of Engineering Technology. He holds multiple leadership roles including Head of the Structural Mechanics Division in Ghent, Contact Person for Structural Mechanics at Ghent and Aalst Campuses, and member of the Division Digital and Sustainable Civil Engineering. His institutional affiliations extend to the LISS – KU Leuven Institute of Sports Science. His research focuses on Structural Dynamics and Human-Structure Interaction , particularly in footbridge engineering. Key research areas include human-induced vibrations, dynamics of civil structures, vibration serviceability assessment, and pedestrian-bridge interaction phenomena. His work combines experimental validation with numerical modeling to address challenges in footbridge design under running and crowd loading conditions. Current research projects demonstrate his active grant portfolio: An integrated static-dynamic structural optimization approach for footbridge design (2023-2026, Co-promotor) Design methodology for contemporary footbridges including human-structure effects (2022-2026, Promotor) Numerical and experimental study of footbridge vibrations induced by running (2020-2025, Promotor) These projects reflect his focus on practical engineering solutions for vibration serviceability problems. His publication record shows a strong trend toward experimental validation of human-structure interaction phenomena, particularly regarding running-induced vibrations on footbridges. Recent work emphasizes full-scale measurements, load model development, and the impact of human-human interaction on structural response. His research bridges civil engineering and biomechanics through motion capture and force reconstruction techniques. Teaching responsibilities span multiple courses including Finite Element Method, Dynamics of Structures, Steel Structures, and various Engineering Projects. He supervises Master's Theses in Civil Engineering and Geomatics, with emphasis on structural mechanics applications. As part of the LISS institute, he contributes to interdisciplinary sports science research, particularly regarding human motion analysis and its structural implications. His work on the Eeklo Footbridge has established benchmark datasets for pedestrian-induced vibration studies.
Ting Li is an Assistant Professor of Computer Science at Emory University. She earned her PhD in Computer Science from the University of North Carolina at Charlotte in 2019 and holds a Bachelor's degree in Information Engineering from Xidian University (2012). Her research focuses on privacy-centric systems in mobile crowd sensing and edge computing, with applications in enhancing student experiences through bike-sharing algorithms and inter-campus matching solutions. Education: PhD in Computer Science (UNC Charlotte, 2019); B.Eng in Information Engineering (Xidian University, 2012) Her recent work analyzes stochastic matching, diversity-preserving selection, and privacy-preserving grouping in mobile crowdsensing environments, combining algorithmic innovation with distributed computing frameworks across 5 publications since 2020. Current projects explore incentive mechanisms and edge cloud architectures.
Marius Brachvogel is a Research Assistant and Doctoral Student at the Chair of Navigation (DLR) at RWTH Aachen University . His work focuses on Global Navigation Satellite Systems (GNSS), Low Earth Orbit (LEO) satellite applications, and robust signal processing for automotive navigation systems. His research explores: Signal integrity and interference mitigation in GNSS receivers Calibration and array processing for spatially distributed antenna systems LEO-based augmentation of GNSS constellations Spoofer detection in safety-critical automotive applications Wideband calibration techniques for multi-antenna arrays Recent publications highlight trends in GNSS security, automotive positioning resilience, and distributed antenna array design. Awards and grants are not explicitly mentioned in the provided text. Marius contributes to advancing robust navigation solutions through both theoretical analysis and practical implementation.
Yen-Chia Hsu is an Assistant Professor at the Informatics Institute, University of Amsterdam, where they teach courses in Information Visualization and Data Science. Previously, they served as a Postdoctoral Researcher at the Department of Sustainable Design Engineering, Faculty of Industrial Design Engineering, TU Delft, and as a Project Scientist in the CREATE Lab at Carnegie Mellon University (CMU). Their academic journey reflects a unique interdisciplinary background bridging computer science and architectural design. Dr. Hsu earned their Ph.D. degree in Robotics in 2018 from the Robotics Institute at CMU, where they conducted research on using technology to empower local citizens and communities. Prior to that, they received their Master's degree in tangible interaction design in 2012 from the School of Architecture at CMU, where they studied and built prototypes of interactive robots and wearable devices. Before CMU, they earned a dual Bachelor's degree in both architecture and computer science in 2010 at National Cheng Kung University, Taiwan. Dr. Hsu is a computer scientist with an architectural design background whose research focuses on Community-Empowered Artificial Intelligence (AI) , where they co-design, implement, deploy, and evaluate interactive AI systems that empower communities, especially in addressing environmental and social issues. Their work spans both social and technical aspects of community engagement with technology. On the social side, they have proposed an alternative framework called Community Citizen Science (CCS) , which extends traditional citizen science methods to a hyper-local scale, emphasizing continued community engagement after technology interventions. On the technical side, they investigate human feedback in AI pipelines and algorithms that enable machine learning models to incorporate different types of human input. Dr. Hsu's scholarly output demonstrates a consistent focus on applying computer vision, machine learning, and data science to environmental monitoring and community empowerment. Their recent work shows an evolution from developing specific tools for pollution monitoring toward more comprehensive frameworks for community engagement with AI systems. A notable trend is the increasing emphasis on empathy-centered design and policy implications of community-driven data collection systems. Their research bridges the gap between technical innovation and social impact, particularly in the domains of air quality monitoring and environmental justice. Outstanding Student Academic Achievement (2005, 2006, 2007) from Department of Architecture, National Cheng Kung University, Taiwan Third Prize, National Country House Design Competition (2008) from Ministry of the Interior, Taiwan Best New Artist, The National Golden Award for Architecture (2009), Taiwan Webby People's Voice Award, Best Use of Video or Moving Image (2014) Best Paper Honorable Mention Award (Top 5%) at ACM CHI Conference (2017) Best Paper Honorable Mention Award (Top 2.5%) at ACM IUI Conference (2019) Prize for Community Collaboration, The Constellation Prize (2020) Dr. Hsu has been actively involved in numerous research projects that bridge academia and community action. Their work on the Smell Pittsburgh platform, which allows citizens to report pollution odors to regulators, has been particularly influential in environmental advocacy. They have collaborated with organizations including ACCAN, PennEnvironment, GASP, Sierra Club, ROCIS, Blue Lens, LLC, PennFuture, Clean Water Action, and Clean Air Council. Their research has received support from the Heinz Endowments and has been featured in TIME, Pittsburgh Post-Gazette, PC Magazine, and other media outlets. Dr. Hsu also maintains an active open-source presence, with several tools and datasets released to support community-driven environmental monitoring. Dr. Hsu leads projects that focus on developing tools for community engagement at scale, including COCTEAU, an empathy-based tool for decision-making, and Project RISE, which recognizes industrial smoke emissions. Their work connects with the Multimedia Analytics Lab Amsterdam, where they contribute to data science education and research. Their approach emphasizes co-creation with communities rather than top-down technology deployment, positioning them at the forefront of human-centered AI research with real-world social impact.
Dr. John A Greenwood is a MRC Career Development Fellow at the Department of Experimental Psychology, University College London . His research focuses on the mechanisms of visual perception and clinical disorders of vision , particularly amblyopia. He leads the Eccentric Vision Lab ( eccentricvision.com ), which investigates crowding effects, spatial vision topologies, and cortical processing idiosyncrasies. Key Research Themes: Visual crowding, interocular suppression, orientation selectivity, and neural correlates of perception Methodologies: fMRI adaptation, psychophysical experiments, and computational modeling His work reveals that crowding is a regularization process altering object appearance, and that binocular treatments for amblyopia improve compliance without reducing suppression. He has published extensively in Scientific Reports , Journal of Vision , and Investigative Ophthalmology & Visual Science . Scientific Awards: MRC Career Development Fellow
Sarah Rauscher is an Assistant Professor at the University of Toronto Mississauga (UTM), primarily affiliated with the Department of Chemical and Physical Sciences and also holding a cross-appointment in the Department of Chemistry. Her research focuses on molecular dynamics simulations of biomolecular systems, with a particular emphasis on intrinsically disordered proteins, protein-protein interactions, and enzyme allostery. She employs advanced computational methods to study structural ensembles, biomolecular condensates, and the impact of mutations on protein function. Her work integrates computational biophysics with biochemical experimentation, addressing topics such as viral protease dynamics, oncogenic mutations in cancer proteins, and the structural basis of elastic biomaterials like elastin. Recent projects include investigating PEG-mCherry interactions under crowding conditions, electric-field effects on protein crystals, and the role of STAT5B mutations in oncogenesis. Rauscher’s publications span over two decades, demonstrating expertise in force field development (e.g., CHARMM36m), water-mediated allostery, and protein self-assembly mechanisms. Her research bridges fundamental biophysics with translational applications in drug design and biomaterials science.
AnHai Doan is the Vilas Distinguished Achievement Professor and Gurindar S. Sohi Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. He leads research in data integration, entity matching, and data science, focusing on end-to-end systems like Magellan. His work integrates machine learning, scalable data management, and human-in-the-loop approaches. Education details are not explicitly provided in the text but his academic roles suggest advanced degrees in computer science. Research interests include data cleaning, entity matching, and cloud/crowd services. He co-founded GreenBay Technologies (acquired by Informatica) and contributed to the School of Computer, Data, and Information Sciences at UW-Madison. Key awards include the ACM Doctoral Dissertation Award (2003) and NSF CAREER Award (2004). He teaches data science courses (CS 638 DS, CS 774) and served on strategic initiatives for UW-Madison’s computing growth. His service includes roles on SIGMOD’s advisory board and co-chairing SIGMOD-2020.
