Mark S. Handcock is a Distinguished Professor in the Department of Statistics and Data Science at the University of California, Los Angeles (UCLA), where he leads research at the intersection of statistical methodology and applied problems in social sciences, epidemiology, and environmental science. His work bridges theoretical statistics with real-world challenges through innovative methodological development. His primary research interests encompass statistical models for social networks, network inference, methodology for hard-to-reach population surveys, spatial processes, demography, and environmetrics. Handcock has pioneered advances in exponential-family random graph models (ERGMs) and developed foundational R packages like ergm and tergm within the statnet suite, enabling sophisticated network analysis across disciplines. Analysis of his recent publications (2023-2025) reveals three dominant research thrusts: (1) Antarctic sea ice modeling using Bayesian reconstruction and temporal variability analysis, (2) epidemiological modeling of infectious disease transmission dynamics (particularly COVID-19), and (3) methodological innovations in network inference and causal analysis over stochastic networks. His work consistently integrates advanced computational statistics with domain-specific applications in climate science, public health, and social systems.
Scott L. Diamond is the Arthur E. Humphrey Professor of Chemical and Biomolecular Engineering and Bioengineering at the University of Pennsylvania's School of Engineering and Applied Sciences. He serves as Director of the Penn Center for Molecular Discovery, Director of the Penn Biotechnology Masters Program (one of the largest in the country with over 130 students), and Associate Director of the Institute for Medicine and Engineering (IME). His laboratory is located in the Roy and Diana Vagelos Laboratories at 3340 Smith Walk, 1020 Vagelos Research Laboratories, Philadelphia, PA. Diamond's research spans multiple interconnected fields in blood biology and biotechnology. His work focuses on mechanobiology, thrombolysis, coagulation, bioadhesion, gene therapy, drug/device development, proteomics, drug discovery, systems biology, and microfluidics. His laboratory has developed numerous specialized microfluidic devices for studying blood clotting under various flow conditions, including 8-channel devices for high-throughput clotting assays, side-view devices for clot structure analysis, stenosis devices for high shear clotting assays, and impingement-post devices for studying von Willebrand factor fibers. Diamond's research group has pioneered approaches to model and predict blood function using systems biology principles. His team has developed computational models that integrate reaction-transport phenomena with platelet signaling networks to predict thrombus formation under flow. These models have enabled the development of 'virtual blood' computer simulations that can predict the effectiveness of anticoagulation drugs for individual patients, contributing significantly to personalized medicine approaches in hemostasis and thrombosis. His extensive publication record demonstrates a consistent focus on understanding the fundamental mechanisms of blood clot formation and dissolution. Recent work has emphasized microfluidic approaches for point-of-care diagnostics, patient-specific modeling of platelet function, and the development of novel therapeutic strategies for thrombotic disorders. His research bridges engineering principles with clinical hematology to address significant challenges in cardiovascular medicine. NSF National Young Investigator Award NIH FIRST Award American Heart Association Established Investigator Award AIChE Allan P. Colburn Award George Heilmeier Excellence in Research Award Elected Fellow of the Biomedical Engineering Society (BMES) Diamond has secured significant research funding, including a $2.8 million NIH grant for 'Blood Systems Biology' and a $9.5 million NIH grant for the Penn Center for Molecular Discovery. His laboratory has developed numerous microfluidic devices for blood analysis and has collaborated extensively with clinicians and industry partners. Diamond has served on advisory committees for NSF, NIH, AHA, and NASA, and has consulted extensively for industry and government. With over 180 publications and patents, his work has significantly advanced the understanding of blood clotting mechanisms and the development of diagnostic and therapeutic approaches for thrombotic disorders.
Sudin Bhattacharya is an Associate Professor at the BioMolecular Science Gateway, Michigan State University, with affiliations in the Genetics & Genome Sciences Program and Cell & Molecular Biology Program. His research bridges computational biology and toxicology to understand complex biological systems. Email: sbhattac@msu.edu Research Interests Dr. Bhattacharya specializes in systems toxicology, focusing on computational modeling of gene regulatory networks, single-cell transcriptomics, and molecular dynamics in response to environmental toxicants. His work examines how chemical exposures disrupt cellular pathways and contribute to disease mechanisms. Article Trends His recent publications emphasize: Single-cell and single-nucleus RNA sequencing for toxicological profiling Computational models of circadian rhythms and intercellular communication Dose-dependent responses to environmental chemicals like TCDD and heavy metals Mechanistic studies of adipose tissue remodeling and hypertension Applications of machine learning in chemical risk assessment Integrative approaches to liver metabolism and disease modeling Scientific Contributions Dr. Bhattacharya has pioneered multiscale modeling of biological systems, particularly in hepatic and vascular contexts. His work on the aryl hydrocarbon receptor and PPARα signaling networks has advanced predictive toxicology frameworks.
Cécile Mailler is a Reader in Probability at the University of Bath, where she is a member of the probability group Prob-L@B. She has held significant research positions including an EPSRC postdoctoral fellowship (2018-2021) titled "Random trees: analysis and applications" and previously worked as a postdoc at Prob-L@B (2013-2016) as part of Peter Mörters' EPSRC project "Emergence of Condensation in Stochastic Networks". She earned her PhD under the supervision of Brigitte Chauvin and Danièle Gardy at the Laboratoire de Mathématiques de Versailles. Her research focuses on probability theory with emphasis on branching processes, random trees, reinforcement mechanisms, Pólya urns, stochastic approximation, random networks, and statistical physics. She has made significant contributions to understanding preferential attachment models, zero-range processes, and random Boolean trees. Her work bridges theoretical probability with applications in statistical physics and combinatorics. Analysis of her recent publications shows a strong focus on random tree structures, branching processes, and reinforcement learning algorithms, with applications spanning from network theory to statistical mechanics. Her research demonstrates sophisticated mathematical techniques applied to complex stochastic systems, particularly those with reinforcement mechanisms and memory effects. Associate Editor of the Applied Probability Trust (since October 2020) Associate Editor of Stochastic Processes and Their Applications (since March 2022) Author of a general introduction to Pólya urns for the LMS Newsletter (November 2020) Co-organizer of the "Random Walks: Applications and Interactions" conference at CIRM (January 2026) She actively supervises PhD students working on topics including the multi-city ants process, Pólya urns with growing initial composition, large deviations for the Monkey walk, and competing growth processes. She has secured research funding through EPSRC fellowships and has been involved in multiple collaborative projects with prominent researchers in probability theory. Mailler regularly teaches mini-courses on advanced probability topics at international summer schools and workshops, demonstrating her commitment to knowledge dissemination in the field.
Cornelia Kleinitz is a Senior Lecturer at the Institute of Archaeology, Humboldt University of Berlin , specializing in Northeast African Archaeology and Cultural Studies. She is also a Research Associate at the German Archaeological Institute (KAAK) and Honorary Research Associate at the McDonald Institute for Archaeological Research, University of Cambridge . Her work focuses on Sudanese archaeology, Meroitic studies, rock art, digital humanities, and critical heritage management. PhD in Archaeology from University College London (2005) MA in Archaeology (African Archaeology, Ethnoarchaeology) from UCL (1994) Magister in History and Archaeology from Freie Universität Berlin/Humboldt University (1998) Research and Teaching Her research spans Sudan archaeology , with leadership roles in the Musawwarat Project since 2016 and the Meroe Pyramids Graffiti Project (2015-2016). She pioneered the Musawwarat Graffiti Archive (2011-present), an open-access platform for digital documentation of ancient graffiti. Teaching includes seminars on Meroitic material culture, archaeological interpretation, and community heritage. Scientific Awards and Grants Petrie-Prize for best MA thesis at UCL DAAD, AHRB, and UCL Graduate School funding for PhD Leadership and Collaborations Kleinitz co-directs the Humboldt University Archaeological Mission to Musawwarat es-Sufra and contributes to UNESCO World Heritage site management. She collaborates with institutions like the Spanish National Research Council (CSIC) and UCL Qatar , integrating participatory GIS and digital methods in heritage studies.
Sharryn M. Kasmir serves as Professor of Anthropology at Hofstra University, where she conducts critical research on labor, capitalism, and working-class communities through ethnographic fieldwork in Spain's Basque region and the U.S. South. Her institutional affiliation centers within the Department of Anthropology, though the specific school/college structure isn't explicitly stated in available materials. Her academic credentials include: PhD from CUNY Graduate School and University Center MPhil from CUNY Hunter College BA from University of Massachusetts Amherst Professor Kasmir's research program critically interrogates Global Capitalism's impact on working-class lives, with specialized focus on Labor and Working Classes, Nationalist Movements and Identity, and Popular Culture across Western Europe and North America. Her fieldwork at Mondragon's worker cooperatives challenged idealized narratives through working-class perspectives, while her Saturn factory research exposed how auto workers navigate perpetual plant closure threats and economic insecurity. As co-editor of the seminal volume Blood and Fire: Toward a Global Anthropology of Labor , she established foundational frameworks for contemporary labor anthropology that bridge ethnographic detail with macro-political economic analysis. Her publication trajectory since the 1990s reveals persistent engagement with labor anthropology's core questions: analyzing worker cooperatives as contested sites within global capitalism (1996-2016), documenting working-class dispossession amid industrial restructuring (2008-2016), and developing theoretical tools like 'unevenness' for cross-cultural labor studies (2016). This body of work consistently synthesizes cultural anthropology, political economy, and critical theory to center workers' lived experiences within broader capitalist transformations. Available documentation contains no references to scientific awards, research grants, student advising activities, laboratory facilities, or collaborative research teams.
Thomas C. M. Lee is a Distinguished Professor of Statistics and Associate Dean of the Faculty in Mathematical and Physical Sciences at the University of California, Davis, within the College of Letters and Science. He holds a prominent position in the Department of Statistics and serves as a key academic leader at UC Davis. Education: B.App.Sc. (Math) from University of Technology, Sydney, Australia (1992) B.Sc. (Hons) (Math) with University Medal from University of Technology, Sydney, Australia (1993) Ph.D. from Macquarie University and CSIRO Mathematical and Information Sciences, Sydney, Australia (1997) Professor Lee's research spans multiple areas of statistics with a focus on developing innovative methodologies. His work particularly emphasizes nonparametric and semiparametric modeling , statistical learning , and statistical image and signal processing . He has made significant contributions to applying statistical methods across various scientific disciplines, demonstrating the versatility and power of statistical approaches in solving complex real-world problems. His research often bridges theoretical developments with practical applications, creating methodologies that are both mathematically sound and practically useful. Scientific Awards and Honors: Elected Fellow of the American Association for the Advancement of Science (AAAS, 2019) Elected Fellow of the American Statistical Association (ASA) Elected Fellow of the Institute of Mathematical Statistics (IMS) Elected Senior Member of the IEEE Professor Lee has held significant editorial roles including serving as Editor-in-Chief for the Journal of Computational and Graphical Statistics (2013-2015) and currently as Review Editor for the Journal of the American Statistical Association. From 2015 to 2018, he chaired the Department of Statistics at UC Davis. He has taught numerous statistics courses including STA 13 (Elementary Statistics), STA 131C (Introduction to Mathematical Statistics), STA 243 (Computational Statistics), and STA 401 (Statistical Consulting). His leadership extends beyond research to academic administration, where he has shaped statistics education and departmental direction at UC Davis.
Charless Fowlkes is a Professor in the Department of Computer Science at the University of California, Irvine (UCI). His research focuses on computational vision, spanning human visual system understanding, machine vision systems, and applications in biomedical informatics and forensic science. He holds a Ph.D. from UC Berkeley (2005). His work integrates techniques from computer vision, AI, and applied mathematics to address challenges in automated biological data analysis, morphology, and spatial gene expression. Key research areas include forensic science (e.g., shoeprint matching via 3D reconstruction), biomedical applications (e.g., heart function mapping and pollen classification), and AI-driven systems for scene understanding. Recent projects include a $20M forensic science center funded by the National Institute of Justice. His publications emphasize geometric reasoning, 3D reconstruction, and adaptive learning algorithms. Notable contributions include developing algorithms for 3D human pose estimation with scene constraints, automated pollen identification via CNNs, and frameworks for cross-domain forensic analysis. His work bridges theoretical computer vision with real-world applications in forensics, healthcare, and environmental science.
Ken Forbus is the Walter P. Murphy Professor of Computer Science and Professor of Education at Northwestern University. He earned his Ph.D. in Artificial Intelligence from MIT in 1984, along with S.M. and S.B. degrees in Computer Science from the same institution. Current research focuses on qualitative reasoning , analogical reasoning , spatial reasoning , sketch understanding , and the Companion cognitive architecture . He has made foundational contributions to qualitative physics , compositional modeling , and cognitive simulation through systems like CyclePad and Companions . His work spans AI, cognitive science, and education technology with applications in intelligent tutoring systems , educational software , and interactive entertainment . Awards and Fellowships: Humboldt Research Award AAAI Fellow Cognitive Science Society Fellow ACM Fellow AAAS Fellow Herbert A. Simon Prize recipient Research trends in recent publications include analogical reasoning frameworks, normative modeling, pretense simulation, qualitative spatial representations, and applications in education and cognitive systems. Articles frequently address intersections between AI, cognitive science, and human-computer interaction. Teaching activities include core courses like Cognitive Science 207 , Design of Problem Solvers , and Conversational AI . He co-developed the open-source Freeciv game framework for AI research in strategy games.
Christopher Storie is a Professor of Geography at the University of Winnipeg, specializing in GIS, Remote Sensing, and Urban Geography. He holds an office in Lockhart Hall (5L03) and teaches courses such as Introduction to GIS, Remote Sensing, and Urbanization in the Developing World. His research focuses on Deep Learning applications for automated land use/land cover mapping, informal settlement mapping, and urban-rural fringe detection. Key research interests include leveraging neural networks for geospatial analysis, urban dynamics in regions like Mexico City, and collaborative international fieldwork. He has contributed to over 20 peer-reviewed articles since 2000, emphasizing satellite imagery analysis and environmental monitoring. His work bridges technical geospatial methods with socio-environmental challenges in urban and developing regions.
Yang Kaidi is an Assistant Professor in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS), affiliated with the Institute of Operations Research and Analytics (IORA) within NUS’s Smart Nation Research Cluster. Their research focuses on intelligent transportation systems, traffic control, shared mobility, and machine learning applications in mobility. Key interests include connected and automated vehicles, privacy-preserving data sharing, and reinforcement learning for traffic optimization. Research highlights include developing parameter privacy-preserving strategies for mixed-autonomy platoons, enhancing safety in autonomous driving via transformer-based trajectory prediction, and optimizing traffic signal timing using connected vehicle data. Their work bridges theoretical control systems with practical urban mobility challenges, addressing issues like ridesourcing-public transit integration, modular transit service operations, and weaving section management in mixed traffic environments. Recent publications emphasize real-time control frameworks, cooperative safety mechanisms, and data-driven solutions for urban and highway systems. Yang’s interdisciplinary approach integrates robotics, optimization, and cybersecurity to advance smart transportation infrastructure. Their contributions are particularly notable in privacy-preserving techniques for traffic state estimation and federated learning applications. While no specific awards or grants are listed, their research aligns with Singapore’s Smart Nation initiatives through IORA’s strategic focus areas. Yang’s work has implications for future traffic management systems, autonomous vehicle coordination, and sustainable urban mobility solutions.
Prof. Müge AKKAR ERCAN is a Professor in the Department of City and Regional Planning at Middle East Technical University (METU), Ankara. She holds a PhD in Urban Design from the University of Newcastle, UK, alongside B.Sc. and M.Sc. degrees in City and Regional Planning from METU. Her academic roles include teaching courses on urban design studios, planning strategies, and thesis supervision. She specializes in urban design, public space analysis, urban regeneration, and sustainable community development with a focus on historic neighborhoods in Turkey and post-industrial cities. **Education:** B.Sc., City and Regional Planning (METU, 1994) M.Sc., Urban Policy Planning and Local Governments (METU, 1997) Ph.D., Urban Design (University of Newcastle, 2003) **Research Interests:** Her work investigates evolving roles of public spaces in post-industrial cities, challenges in balancing community needs with conservation policies, and sustainable urban regeneration strategies. Notable projects include studies on Ankara’s Gençlik Park, Istanbul’s historic neighborhoods, and walkability models for urban revitalization. She contributes to international journals like Journal of Urban Design and Urban Design International , and co-edits books on heritage valuation and urban planning discourses. **Recent Research Trends:** Her publications (2010–2020) emphasize spatial inclusivity in public spaces, heritage-led regeneration, and micro-scale urban interventions. Recent work explores place-making roles in China’s heritage contexts and EU-funded projects on underground cultural heritage and middle-class housing. **Grants & Projects:** Currently involved in EU-funded projects CA18110 (underground heritage valorization) and CA18137 (European middle-class housing analysis). Her work bridges academic research with policy implementation in Turkey and globally. **Labs/Teams:** Leads METU’s urban design research through her department’s studios and collaborates internationally on heritage conservation and urban dynamics initiatives.
David Wooten is the Alfred L. Edwards Collegiate Professor of Marketing and a University Diversity and Social Transformation Professor at the University of Michigan’s Stephen M. Ross School of Business. He holds a PhD (1992), MBA (1987), and BBA (1985) from the University of Michigan and Georgia State University, respectively. His research explores consumer behavior through social psychology and micro-sociological theories, focusing on gift-giving, word-of-mouth, and the impact of racial/stigmatized identities on marketplace dynamics. He has published extensively in journals like Journal of Consumer Research and served as Editor-in-Chief of the Journal of Consumer Psychology . Notable awards include the 2022 Taylor & Francis Distinguished Scholar Award and the 2015 AMA Multicultural Mentoring Award. Wooten’s work bridges theory and practice, addressing topics such as racial identity in consumer research, the presenter’s paradox in service interactions, and the role of ambient lighting in prosocial behaviors. He has led editorial roles and mentored doctoral students through forums like the AMA-Sheth Doctoral Consortium (2013) and SCP Doctoral Symposium (2023). His research also emphasizes equity and social transformation, advocating for inclusive consumer research frameworks.
Carolina Osorio is a Professor at HEC Montréal, holding the Scale AI Research Chair in Artificial Intelligence for Urban Mobility and Logistics. She is affiliated with the Department of Decision Sciences and is a member of the Group for Research in Decision Analysis (GERAD) and the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT). Her research focuses on transportation optimization, urban mobility, and data-driven simulation-based methods. She has been recognized among the world’s most influential researchers in 2023 and 2024. Education: Ph.D. in Mathematics, École Polytechnique Fédérale de Lausanne (EPFL) M.Sc. in Statistics, University College London (UCL) Bachelor’s in Engineering, École nationale supérieure d'informatique et de mathématiques appliquées de Grenoble (ENSIMAG) Research Interests: Her work emphasizes scalable transportation modeling, simulation-based optimization, and AI applications for urban logistics. She develops methods for large-scale network analysis, traffic demand estimation, and sustainable urban mobility solutions. Key areas include traffic signal optimization, car-sharing service design, and high-dimensional stochastic systems. Publications: Recent articles highlight advancements in scalable traffic demand estimation, Bayesian optimization for transportation systems, and simulation-based toll optimization. Her work addresses challenges in global highway networks, urban congestion dynamics, and multi-city calibration. Awards: Scale AI Research Chair (Artificial Intelligence for Urban Mobility and Logistics) Recognition as a world-leading researcher in transportation science Advising & Grants: Osorio collaborates on projects funded by Scale AI and leads research initiatives through GERAD and CIRRELT. Her supervision activities include teaching courses such as Decision Analysis and Sample Efficient Optimization at HEC Montréal. Labs & Teams: She contributes to interdisciplinary teams at GERAD and CIRRELT, focusing on integrating advanced analytics into urban transportation systems.
Ruonan Xu is an Assistant Professor in the Department of Economics at Rutgers University, specializing in Econometrics. She joined the department in Fall 2020. Her research focuses on finite population inference, spatial correlation, and causal inference methodologies. Education: Ph.D. in Economics, Michigan State University, 2020 B.A. in Mathematical Economics, Fudan University, 2015 Research Interests: Dr. Xu’s work emphasizes econometric methodologies for addressing complex data structures, including spatial correlation, clustered data, and interference effects. She has contributed to instrumental variable estimation with binary endogenous variables and developed design-based approaches for spatial analysis. Her recent focus includes robustness considerations in econometric models and multidimensional clustering techniques. Publications & Work in Progress: Her published work includes studies in The Econometrics Journal and Economics Letters . Current projects explore distributionally robust average treatment effects and difference-in-differences with interference mechanisms. A working paper on multidimensional clustering has been submitted to the Journal of Econometrics . Advising & Grants: No formal advisees or grants explicitly listed in the provided materials.
