Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Eric V. Mazumdar is an Assistant Professor at the California Institute of Technology (Caltech), jointly appointed in the departments of Computing and Mathematical Sciences and Economics. He holds a B.S. from MIT (2015) and a Ph.D. from UC Berkeley (2021), co-advised by Michael Jordan and Shankar Sastry. His research bridges machine learning and economics, focusing on deploying algorithms into societal systems through theoretical and practical lenses. Key areas include strategic classification, multi-agent reinforcement learning, and distributionally robust optimization, with applications in healthcare, online markets, and intelligent infrastructure. Education: B.S., Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2015 Ph.D., Electrical Engineering and Computer Science, University of California, Berkeley, 2021 Research Interests: Mazumdar’s work emphasizes understanding learning algorithms in strategic environments, including min-max optimization, game theory, and multi-agent systems. He explores how algorithms interact with human and algorithmic agents in dynamic systems, with practical applications in healthcare delivery, e-commerce, and autonomous systems testing. Awards: NSF CAREER Award (2023) Simons Institute Research Fellowship in Learning in Games Grants & Funding: Supported by NSF, DARPA, Amazon, and other organizations. His NSF CAREER grant focuses on strategic interactions in societal-scale systems. Teaching: Courses include Networks: Structure & Economics (CMS/CS/EE/IDS 144) and Topics in Learning and Games (CMS/Ec 248). At UC Berkeley, he contributed to courses like Data, Inference, and Decisions (DS 102). Students & Postdocs: Current students: Lauren Conger, Tinashe Handina, Yizhou Zhang Postdocs: Zaiwei Chen, Laixi Shi, Kishan Panaganti (co-advised with Adam Wierman)
John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.
Bryan H. Choi is an Associate Professor of Law at the University of Colorado Law School , where he bridges law and computer science to address software and AI safety. His work on software liability has influenced national cybersecurity strategy discussions. As an Adviser for the ALI Principles Project on Civil Liability for Artificial Intelligence , he shapes legal frameworks for emerging technologies. Education : JD and AB in Computer Science from Harvard University; clerkships with U.S. Court of Appeals judges Leonard I. Garth and William C. Bryson. Roles : Former joint appointment at Ohio State University Law School and Computer Science Department; Faculty Fellow at UPenn's CTIC; Director of Law and Media at Yale's ISP. Research Focus : Choi's scholarship examines software liability , AI accountability , and privacy law through interdisciplinary lenses. He critiques institutional approaches to software safety and advocates for empirical legal frameworks over participation-based models. Recent Articles address AI malpractice , NIST software standards , and forensic tool validation , reflecting trends in AI regulation and cyber-physical system liability . His 2021 NSF grant funded technical-legal methods for safety-critical systems. Awards & Grants : National Science Foundation (NSF) Grant (2021) Adviser, ALI Principles Project on Civil Liability for Artificial Intelligence Community Engagement : Active in Law and Computer Science communities , serving on committees for the ACM Symposium , Cybersecurity Law and Policy Scholars Conference , and co-organizing the AAAI Bridge Program on AI and Law .
Rainer Watermann is a Full Professor for Empirical Research in Education at the Free University of Berlin since 2011, previously serving as Full Professor for Education and Empirical Research in Schools at Georg-August University of Göttingen (2005-2011). His academic career includes significant research positions at the Max Planck Institute for Human Development in Berlin (1997-2005). Watermann earned his Diploma in Educational Science from the University of Münster (1996), followed by a Dr. phil (2002) and Habilitation (2005), both from Freie Universität Berlin. His educational background established the foundation for his extensive research in educational transitions and disparities. His research focuses on educational transitions, particularly from primary to secondary school and into higher education, examining motivational factors, social background influences, and achievement goal development. Watermann's work consistently addresses how social disparities affect educational opportunities and outcomes, with particular attention to gender differences and longitudinal developmental patterns. His methodological expertise includes latent class analysis, structural equation modeling, and large-scale assessment design. Watermann's publication portfolio reveals consistent research trajectories examining motivational frameworks (particularly expectancy-value theory), educational transitions, social disparities in education, and political socialization. His work spans both theoretical development and practical applications for educational policy and practice, with increasing focus on intervention effectiveness in recent years. As an active member of the academic community, Watermann serves on multiple editorial boards including the Swiss Journal for Educational Sciences and Empirical Educational Science , and regularly reviews for major educational and psychological journals. He has also contributed to significant research centers, including serving as spokesman for the Center for Empirical Research on Teaching and Learning in Schools (ZeUS) at the University of Göttingen (2008-2010). Watermann maintains an active research program with numerous collaborations across Germany and internationally, evidenced by his consistent publication record through 2025. His work bridges educational psychology, sociology of education, and policy-relevant research, maintaining strong connections between theoretical frameworks and practical educational contexts.
Nathaniel D. Daw serves as the Huo Professor in Computational and Theoretical Neuroscience and Professor of Neuroscience and Psychology at Princeton University, based at the Princeton Neuroscience Institute. His research integrates computational modeling with experimental neuroscience to investigate fundamental mechanisms of learning and decision-making. Daw's research focuses on computational and theoretical neuroscience, specializing in reinforcement learning, memory systems, and decision-making processes. He examines how neural circuits represent value, update beliefs through experience, and balance model-based versus model-free control strategies. His work frequently bridges theoretical frameworks with behavioral and neural data to explain phenomena ranging from habitual behavior to flexible cognitive control. Analysis of his 2025 publications reveals dominant themes in neural replay mechanisms, individual differences in learning trajectories, and clinical applications to eating disorders. His work increasingly incorporates large language models for psychological assessment while maintaining core focus on interpretable cognitive architectures and hierarchical planning. Daw maintains active research operations through the Princeton Neuroscience Institute, an interdisciplinary hub fostering collaboration between computational modelers, neuroscientists, and psychologists to advance understanding of neural mechanisms underlying cognition.
Angela Crow is an Associate Professor at James Madison University (JMU) in the School of Writing, Rhetoric and Technical Communication, where she has served since 2012. Her research bridges literacy studies, design, and urban mobility, focusing on how communities advocate for car-free infrastructure and equitable public spaces. She explores the role of digital communication in fostering feminist interventions, particularly around cycling advocacy and street design. Her work intersects with gender studies, urban studies, and rhetorical theory. Educated at the University of Kansas (Ph.D., 1997) and Point Loma College (B.A., 1987), she has authored books on writing programs and composition studies, including Aging Literacies (2006) and Field of Dreams (2002). Recent publications analyze surveillance, privacy in digital contexts, and transportation equity. Her research often highlights marginalized voices in shaping public discourse. Research Interests: Her current projects examine embodied literacies in mobility advocacy, social media practices of grassroots movements, and the rhetoric of urban infrastructure. She critiques car-centric planning through feminist and critical frameworks, emphasizing accessibility and safety for non-car users. Her work also addresses aging populations’ digital literacies and the intersection of technology with social inequality. Publications: Her articles span rhetorical analysis of social movements, educational assessment frameworks, and the sociotechnical dimensions of writing. Recent trends include collaborations on privacy in big data and participatory design for community mobility.
Michael D. Smith is a Professor of Information Technology and Public Policy at Carnegie Mellon University, with joint appointments at Heinz College and Tepper School of Business. His research employs economic and statistical methods to analyze digital markets, focusing on firm and consumer behavior in online environments. Education: B.Sc. in Electrical Engineering (Summa Cum Laude), University of Maryland M.Sc. in Telecommunications Science, University of Maryland Ph.D. in Management Science and Information Technology, MIT Research Interests: Professor Smith investigates the economics of digital information markets, consumer behavior in online platforms, and policy implications of technological disruption. His work spans copyright enforcement, digital advertising, and the impact of piracy on legal media consumption. Publications: His recent studies examine AI’s role in copyright policy, effectiveness of anti-piracy measures, and market dynamics in digital streaming. Articles often bridge economics, computer science, and public policy. Awards: National Science Foundation CAREER Award Multiple Best Teacher Awards at CMU Recognized as a Top 100 Emerging Engineering Leader (NAE, 2020) Best Paper Runner-Up (Information Systems Research, 2006) Editorial and Industry Roles: Served as Senior Editor at Information Systems Research and Associate Editor at Management Science . Prior to academia, he worked in telecommunications at GTE and Booz Allen Hamilton, earning a patent for AI applications in network design. Contact: mds@cmu.edu | Office: 4800 Forbes Avenue, Hamburg Hall 2204, Pittsburgh PA 15213
Jan Borchers is a full professor of computer science and head of the Media Computing Group, an endowed Chair in the Computer Science Department at RWTH Aachen University. He serves as deputy member of the Faculty Council for Mathematics, Computer Science and Natural Sciences (2024-2026) and previously headed the Computer Science Department's Examination Board from 2015 until February 2025. Borchers established his research group in 2003, pioneering modern HCI academic research and teaching in Germany, and opened Germany's first Fab Lab in 2009. Borchers received his PhD 'summa cum laude' in computer science from Darmstadt University of Technology in 2000. Before joining RWTH Aachen, he held faculty positions at Stanford University and ETH Zurich. His PhD thesis, 'A Pattern Approach to Interaction Design,' became the first book to bring design patterns to HCI. His research focuses on Human-Computer Interaction with particular interest in new user interfaces for soft robotics, textile user interfaces, 3D printing and personal fabrication, augmented reality, wearable and tangible computing, interfaces for software development, deceptive patterns, and interactive guides and exhibits. He is a member of ACM, SIGCHI, SIGCHI Germany, and GI, and introduced the Interactivity format to the CHI conference in 2005. Recent publications reveal a strong emphasis on deceptive patterns/dark patterns in UI design, textile interfaces, and the impact of generative AI on creative teamwork. His work spans from fundamental research in interaction techniques to practical applications in smart homes, accessibility, and children's interfaces, with a consistent focus on usability and user-centered design. IDC 2025 Best Work in Progress: 'If They Have No Choice, They'll Accept!' CHI'25 Student Games Competition Winner: 'The Deceptive Dungeon' RWTH-Wissenschaftsnacht 2024 Best Science Slam: 'Usability: 4 Prinzipien guter User Interfaces' Multiple CHI/UIST Honorable Mentions and Best Paper awards spanning two decades Author of influential books including 'A Pattern Approach to Interaction Design' and 'Arduino In A Nutshell' Borchers has provided extensive consulting, training, and user interface design services to major clients including AirBus, Apple, ARD, Bayer, Children's Museum Boston, Daimler, Handelsblatt, OTIS, Scout24, TEDx, and Deutsche Telekom. He actively organizes the Computer Science Department's weekly Faculty Lunch since 2003 and coordinates the department's public relations and web presence since 2010. He leads the Media Computing Group, which has become a leading German lab in terms of archival publications at CHI, the top international conference in HCI. Since March 2025, he serves as faculty patron for TechLabs Aachen, a student initiative providing practical digital skills training.
Daniel Schnurr holds the Chair of Machine Learning, especially Uncertainty Quantification at the University of Regensburg since August 2022, where he conducts research at the intersection of artificial intelligence, data economics, and digital market regulation. Previously, he headed the Data Policies research group at the University of Passau, building his expertise in the economic and regulatory aspects of digital markets. His educational background includes a doctorate in business informatics from the Karlsruhe Institute of Technology (2016), where he also worked for three years as a research associate at the Institute for Information Systems and Marketing. He completed his undergraduate and master's studies in Information Systems at KIT (2007-2013), with international experience at Concordia University in Canada and Singapore Management University. Professor Schnurr's research focuses on the technical, economic, and social implications of new machine learning methods and data as a decisive competitive factor and driver of innovation in digital markets. His work examines how data functions as both an economic asset and regulatory challenge, particularly in contexts of market power, competition policy, and AI governance. He investigates uncertainty quantification in machine learning systems while considering their broader economic and societal impacts. His publication portfolio demonstrates consistent output in top-tier journals including Management Science, Journal of Information Technology, and Journal of Competition Law & Economics, with recent work increasingly focusing on AI regulation, data access remedies, and uncertainty-aware AI systems. The trajectory shows evolution from telecommunications infrastructure research to contemporary digital market and AI regulation issues. As a Research Fellow at the Centre on Regulation in Europe (CERRE) since 2022, he has authored numerous policy reports addressing regulation of cloud computing services, digital platforms, and data economy frameworks. His policy contributions bridge academic research with practical regulatory implementation, particularly regarding the European AI Act and Digital Services Act. His research program involves experimental approaches to understanding data markets, human-AI interaction dynamics, and regulatory effectiveness. Through his work at CERRE and collaborations with international scholars, he contributes to shaping evidence-based digital policy in the European context while maintaining strong connections to academic research communities in information systems and economics.
Andy Lamey is an Associate Teaching Professor in the Department of Philosophy at the University of California, San Diego (UCSD). He holds a PhD in Philosophy from the University of Western Australia (2011). His research focuses on applied ethics, political philosophy, and animal ethics, with notable works addressing topics like refugee rights, freeganism, and the ethics of food consumption. Lamey is the author of Duty and the Beast (2019) and Frontier Justice (2011), and co-creator of Justice: The Game , an educational role-immersion game for teaching political philosophy. His teaching includes courses on ethics, political philosophy, and free expression. Recent courses at UCSD include Phil 28 (Ethics & Society II) on free speech and Phil 172 (Topics in Political Philosophy) analyzing Robert Nozick’s Anarchy, State, and Utopia . Lamey’s work bridges philosophical theory with contemporary issues, including immigration policy, animal rights, and literature. Key contributions include analyses of refugee rights, critiques of jurisdictional arguments for immigration control, and explorations of animal ethics through figures like Temple Grandin. He has published over 25 peer-reviewed articles and book chapters, and his writings engage with thinkers like Plato, G.A. Cohen, and J.M. Coetzee.
Pietro Ortoleva is a Professor of Economics and Public Affairs at Princeton University , affiliated with the Department of Economics and the School of Public and International Affairs. His research spans Decision Theory , Behavioral Economics , Experimental Economics , and Political Economy , with a focus on understanding deviations from traditional economic models. Education: PhD in Economics, New York University (2009); BA in Economics, Università degli Studi di Torino (2004). Professional Roles: Coeditor of the American Economic Review (since 2021), former Editor of the Journal of Economic Theory (2018–2020), and editorial board member for multiple journals. His work investigates stochastic choice , ambiguity aversion , and reference-dependent preferences , often through incentivized experiments. Recent studies include the role of social norms in vaccine uptake , cautious utility models , and non-Bayesian belief updating . He has secured multiple National Science Foundation grants for projects on behavioral economics and decision-making under uncertainty. His 15 most recent publications reveal trends in behavioral decision theory , with emphasis on randomization preferences , time lotteries , cognitive biases , and political behavior . These studies frequently bridge economics, psychology, and public policy.
Mark Burris is the Herbert D. Kelleher Professor in the Department of Civil & Environmental Engineering at Texas A&M University's College of Engineering, where he also serves as Division Head of Transportation & Materials Engineering. He is additionally a Research Engineer with the Texas A&M Transportation Institute, demonstrating his dual commitment to academic research and practical transportation solutions. With a career spanning over two decades since joining Texas A&M in 2001, Burris has established himself as a leading expert in transportation economics and traveler behavior. Burris's research focuses on the intersection of transportation economics, behavioral psychology, and infrastructure management. His work primarily investigates traveler responses to pricing mechanisms, particularly value pricing and high-occupancy toll (HOT) lanes. He has pioneered research combining traditional transportation engineering with behavioral economics to understand seemingly irrational traveler choices, such as paying to use express lanes that are sometimes slower than toll-free alternatives. His research has significantly advanced the understanding of travel time value, reliability valuation, and how psychological factors influence transportation decisions. Analysis of Burris's recent publications reveals a strong trend toward integrating behavioral economics with transportation engineering, with increasing attention to equity considerations in road pricing, the impacts of emerging technologies like autonomous and connected vehicles, and innovative methods for measuring traveler responses. His work consistently addresses practical transportation challenges while advancing theoretical understanding of travel behavior. Burris has served in prominent leadership roles, including a six-year term as chair of TRB's transportation economics committee. He has advised numerous federal agencies, serving on NCHRP panels and participating in FHWA expert forums on road pricing. His expertise is widely recognized in both academic and professional transportation circles. As an educator, Burris has advised over 60 graduate students and numerous undergraduates, teaching core courses including CVEN 307 (Introduction to Transportation Engineering), CVEN 454 (Urban Planning for Engineers), and CVEN 632 (Transportation Engineering: Economics). His research portfolio includes substantial funding from FHWA, NCHRP, and various state transportation agencies, with recent projects focusing on behavioral economics applications to managed lanes, vehicle miles traveled fee equity, and the impact of emerging mobility technologies.
Meredith E. David is an Associate Professor of Marketing in the Foster Business and Innovation school at Baylor University, where she conducts research on consumer behavior, marketing strategy, and strategic management. Her interdisciplinary work bridges psychology and marketing, with a focus on how interpersonal dynamics and digital habits influence consumer decisions. PhD in Marketing, University of South Carolina (2013) MBA, Wake Forest University (2008) BSBA in Marketing, University of South Carolina (2006) Her research interests include consumer attitudes and decision-making, smartphone use and social media's impact on well-being, interpersonal attachment styles in marketing contexts, and strategic planning. She explores how digital behaviors like phubbing affect relationships and how emotional and psychological factors shape consumer preferences and advertising responses. Her recent publications reveal a strong trend in integrating psychological theories—particularly attachment theory and social exclusion—into marketing science. She frequently publishes in top-tier journals such as Journal of Advertising , Psychology & Marketing , and Journal of Social and Personal Relationships , often examining how technology mediates human interaction and consumer choices. A recurring theme is the intersection of personal relationships and consumer behavior, especially in digital environments. Meredith David is a coauthor of Pearson’s globally adopted Strategic Management textbook (17th and 18th editions), used by over 500 institutions. This collaboration with Fred R. David and Forest David has significantly influenced both academic and corporate strategic planning education. Her work has been featured in major media outlets including ABC News, CNN, TIME Magazine, Wall Street Journal, and Washington Post, highlighting the public relevance of her research. She is actively involved in pedagogical innovation, providing tools such as the free Excel Student Template for strategic analysis and contributing to Pearson MyLab resources. While no formal advisees are listed, her leadership in curriculum development and case-based learning suggests a strong mentoring role. She also contributes to academic-practice integration through her textbook’s application in real-world business strategy. Meredith David is affiliated with the David Strategic Management team, which maintains the author website www.strategyclub.com , offering teaching aids, videos, and updates. This collaborative platform supports global instructors and students in mastering strategic management concepts.
Stephen E. Still is a Professor of Practice in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (UB), affiliated with the Institute for Sustainable Transportation and Logistics. His roles include teaching applied transportation planning and technology courses, advising students, and collaborating across disciplines between the School of Engineering and Applied Sciences and the School of Management. Prior to academia, he served as founder and managing director of Seabury Airline Planning Group and Diio, LLC, specializing in aviation consulting and IT. With over 30 years of industry experience, he held leadership roles at US Airways and United Airlines, focusing on strategic route planning, fleet management, and alliance development. Dr. Still holds a PhD in Civil Engineering and Operations Research from Princeton University, with a focus on transportation systems and economics, and a BS in Engineering (magna cum laude) from UB with a concentration in transportation planning. He has also completed advanced coursework in demand modeling at MIT. His research interests emphasize sustainable transportation systems and logistics, integrating engineering principles with operational efficiency. While his academic contributions primarily reside in transportation engineering, his interdisciplinary work incorporates wearable technology and sensor-based solutions for health monitoring, as evidenced by his extensive publication record in smoking cessation and behavioral health research. Scientific awards and grants are not explicitly mentioned in the provided information. Dr. Still’s advising and teaching focus on fostering student engagement in transportation innovation and real-world problem-solving. His professional experience bridges academia and industry, reflecting a commitment to practical applications of engineering and logistics principles.
