Kathleen M. Carley is a full professor at Carnegie Mellon University's School of Computer Science with courtesy appointments in Engineering and Public Policy, Heinz School, and Electrical and Computer Engineering. As director of the Center for Computational Analysis of Social and Organizational Systems (CASOS) and the Center for Informed Democracy and Social-Cybersecurity (IDeaS) , she leads interdisciplinary research at the intersection of network science, cognitive modeling, and cybersecurity. Ph.D. in Sociology from Harvard University SB degrees in Economics and Political Science from MIT Her research focuses on Dynamic Network Analysis (DNA) and Social-Cybersecurity (SC) , developing tools like ORA (network analysis), AutoMap (semantic mining), Construct (influence simulation), and BotHunter (bot detection). She has over 400 publications and 15+ active research projects addressing disinformation, cognitive security, and organizational resilience. Recent work examines LLM-powered bots , multi-platform misinformation dynamics , and public health analytics . As an IEEE Fellow, she contributes to standards in computational social science while teaching courses on network analysis and complex socio-technical systems.
Aniket 'Niki' Kittur is a Professor in the Human-Computer Interaction Institute at Carnegie Mellon University's School of Computer Science. His research focuses on AI-augmented cognition, exploring how human and machine intelligence can collaborate to enhance creativity, decision-making, and innovation. He leads projects like the Semantic Reader and Skeema browser extension, aiming to reduce cognitive overload through intelligent systems. Education: BA in Psychology & Computer Science from Princeton University; PhD in Cognitive Psychology from UCLA. His work bridges HCI, crowdsourcing, and cognitive science, with 100+ publications and 17 best paper awards. He advises industry partners including Google, Microsoft, and Toyota while maintaining a lab focused on real-world impact. Research interests center on accelerating knowledge acquisition via systems that scaffold sensemaking (e.g., Selenite for web exploration) and fostering analogical innovation through crowdsourced/AI hybrid approaches. Notable contributions include CrowdForge (human-machine workflows) and Kinetica (touch-based data visualization). Awards include NSF CAREER Award, Allen Newell Award, and CHI Academy membership. His lab's Skeema tool has achieved 79% 30-day retention in beta, reflecting impactful user-centered design principles. Current projects emphasize LLM integration for composite cognition, aiming to create systems where 'LLMs + Humans > Either Alone.' Funding来自NSF, NIH, ONR, and industry partners like Bosch and Wikimedia. Teaching includes PhD bootcamps and user-centered research courses. Over 100 students have contributed to his projects, many advancing to tech leadership roles.
Yan Huang is an Associate Professor of Business Technologies at the Tepper School of Business, Carnegie Mellon University. She holds a Ph.D. in Information Systems and Management from Carnegie Mellon University (2013) and a B.Sc. (with honors) in Information Systems and Management from Tsinghua University, Beijing, China (2009). Prior to joining Carnegie Mellon University, she served as an Assistant Professor of Technology and Operations at the University of Michigan–Ann Arbor, Ross School of Business (2013-2018). Her educational background includes: B.Sc. (with honors) in Information Systems and Management, Tsinghua University, Beijing, China (2009) Ph.D. in Information Systems and Management, Carnegie Mellon University, Pittsburgh, United States (2013) Dr. Huang's research examines the economic and social impacts of technologies and identifies effective designs and policies for technology-enabled markets and platforms. She employs economic theories, structural modeling, statistical modeling, machine learning methods, and an understanding of the underlying technologies in her research. Her recent work focuses on the economics of artificial intelligence (AI) and machine learning (ML), with particular attention to algorithmic fairness, transparency, and collusion. She is among the first to bring economic and social perspectives to research on fair ML. Additionally, she studies digital platforms and online markets, examining how firms can leverage data-driven strategies to optimize pricing, personalization, and user engagement. Her recent publications demonstrate a strong focus on the intersection of AI/ML with economic principles, particularly in areas like algorithmic bias, pricing strategies, and platform regulation. A significant portion of her work examines how machine learning algorithms impact financial lending decisions, housing markets, and content creation platforms. Her research methodology frequently combines structural econometric modeling with empirical analysis of real-world data, providing both theoretical insights and practical implications for platform design and policy. Dr. Huang has received several prestigious awards for her scholarly contributions: AIS Senior Scholar Best Publication of 2023 Award for "Algorithmic Transparency with Strategic Users" Runner Up, Best Paper Published in Information Systems Research for 2021 for "Crowds, Lending, Machine, and Bias" INFORMS Information Systems Society Sandy Slaughter Early Career Award Finalist, Best Student Paper Award, CIST 2021 for "Human-Algorithmic Bias: Source, Evolution, and Impact" Pounds Fellowship As an active member of the academic community, Dr. Huang serves on various committees at CMU including the MSBA Curriculum Review Committee and the Tepper School Strategic Plan Task Force. She has also held editorial positions for Management Science, Information Systems Research, and the International Conference on Information Systems. Her teaching portfolio includes courses on Human and Algorithmic Bias, Modern Data Management, and PhD-level instruction at the Tepper School.
Tridas Mukhopadhyay is the Deloitte Consulting Professor of e-Business at Carnegie Mellon University's Tepper School of Business, where he has served on the faculty since 1986. His academic journey at CMU progressed from Instructor of Information Systems (1986-1987) to Assistant Professor (1987-1993), Associate Professor (1993-1997), Professor (1998-present), and Deloitte Consulting Professor of e-Business (2000-present). He also served as Director of the MS in Electronic Commerce program from 1999-2004. Ph.D. in Computer and Information Systems, University of Michigan–Ann Arbor, 1987 M.B.A. in Computer and Information Systems, Indian Institute of Management Calcutta, 1981 B. Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1978 Professor Mukhopadhyay's research spans multiple critical areas in information systems and technology management. His work on strategic IT use examines how organizations derive business value from information technology investments. He has conducted extensive research on business-to-business commerce, particularly focusing on e-procurement systems, web-based marketplaces, and electronic intermediation models. His cybersecurity research investigates the economic aspects of cyber security, including liability mechanisms and patch release strategies. In software engineering, he has studied productivity, quality metrics, and offshore software development contracts. His most recent publications reveal several key trends in his research trajectory. There's a growing focus on digital platform economics, examining advertising models, virtual currency systems in gaming, and sharing economy dynamics. His work increasingly incorporates behavioral aspects, studying how users respond to personalized content and how backers exert control in crowdfunded projects. Methodologically, his research employs sophisticated analytical approaches including hierarchical Bayesian models, structural equation modeling, and natural experiment designs. CART Research Frontier Award, Carnegie Mellon, 2005 Distinguished Ph.D. Alum, Michigan Business School, 2004 Best Paper, International Conference on Information Systems, 2001 Best Paper, MIS Quarterly, 1995 Xerox Research Chair, Tepper School of Business, 1988-1989 Information Systems Society Distinguished Fellow, 2012 Professor Mukhopadhyay has served on numerous editorial boards including Information Systems Research (1994-2003), Management Science (1999-2003), and MIS Quarterly (1997-1999), demonstrating his significant contributions to the field. His consulting work with major organizations including Alcoa, Chrysler, Ford, General Motors, IBM, and governmental agencies like the United States Post Office and Pennsylvania Turnpike has provided practical insights that inform his academic research. He has been actively involved in university governance through committee service including the Business Technology Faculty Search Committee and the CMU Faculty Senate. His research has been supported through various industry partnerships and academic grants, though specific grant details aren't provided in the source material. His teaching focuses on Business Computing and Strategic IT courses, reflecting his expertise in both foundational information systems concepts and strategic applications of technology in business contexts.
Tyler Malloy is a Research Fellow in the Department of Social and Decision Sciences at Carnegie Mellon University's Dietrich College of Humanities and Social Sciences. His work focuses on the intersection of cybersecurity, cognitive science, and artificial intelligence. He investigates how human decision-making processes can be modeled computationally, particularly in adversarial environments like cyber defense scenarios. His research also explores the application of generative AI to understand user behavior and improve cybersecurity training. Key research areas include cognitive models of decision-making under uncertainty, adversarial machine learning, and the development of frameworks to measure human-AI interaction in cybersecurity contexts. He has contributed to studies on human-autonomy collaboration in cyber defense teams, detection of generative AI-generated social engineering attacks, and reinforcement learning in multi-agent systems. Malloy's publications highlight trends in leveraging cognitive architectures to address modern cybersecurity challenges, such as simulating attacker-defender dynamics and evaluating the effectiveness of training programs against evolving threats. His work bridges computational models with real-world applications, emphasizing both theoretical advancements and practical security solutions. His research has been supported by grants focusing on AI-driven cybersecurity solutions and human factors in technology. Collaborations involve interdisciplinary teams from computer science, behavioral economics, and cognitive neuroscience departments. Malloy is affiliated with CMU's social computing initiatives and contributes to developing next-generation cyber defense strategies through his postdoctoral research.
Peter Brusilovsky is a Professor of Information Science and Intelligent Systems at the University of Pittsburgh's School of Computing and Information. He directs the Personalized Adaptive Web Systems (PAWS) Lab and the Learning Technologies Lab (LTL), focusing on adaptive educational systems, user modeling, and intelligent interfaces. His roles include Associate Editor-in-Chief of IEEE Transactions on Learning Technologies and board memberships in journals like User Modeling and User-Adapted Interaction. Brusilovsky earned his PhD from Moscow State University and has held visiting positions at institutions worldwide, including Carnegie Mellon University. He is a recipient of prestigious awards, including the Alexander von Humboldt Fellowship and NSF CAREER Award, and holds an honorary doctorate from the Slovak University of Technology. His research spans adaptive web systems, social computing, and e-learning, with contributions to intelligent tutoring systems and student modeling. Over 20 years, he has authored numerous papers and books on adaptive hypermedia and the adaptive web. Professional service includes roles with ACM SIGWEB and IEEE, and leadership in User Modeling Inc. Brusilovsky's grants include NSF-funded projects, and his work emphasizes learner control, explainable AI, and the integration of educational technologies. His labs develop tools like QuizGuide and Progressor, advancing personalized learning and open social student modeling.
Wenqi Zhou is an Associate Professor of Information Systems & Technology at Duquesne University's Palumbo-Donahue School of Business. Affiliated with CMU CASOS, CMU IDeaS, Duquesne VIBE, and the Grefenstette Center, they hold the Inaugural David Warco Faculty Fellowship (2021–2024). Their research focuses on AI, tech ethics, healthcare IS, and e-commerce/social media analytics. Zhou teaches undergraduate courses in information systems and graduate behavioral analytics. Educations: Ph.D. from George Washington University School of Business. Research interests include leveraging computational methods to address business and societal challenges, with publications in Journal of MIS , PLoS ONE , Decision Support Systems , and IEEE TIFS . Active in editorial roles for journals like Information & Management and CMOT . Grants & Awards: 2025 Duquesne School of Business Primary Areas Summer Research Grant Multiple Dean's Awards for Research and Teaching (2020–2024) Paluse Faculty Research Grant (2022–2023) Advising & Mentorship: Founded Duquesne's IST Mentorship Program connecting students with industry leaders. Served on editorial boards and conference committees. Labs & Teams: Affiliated with ethics-focused centers like the Grefenstette Center and VIBE, emphasizing interdisciplinary tech ethics research.
Param Singh is the Carnegie Bosch Professor of Business Technologies and Marketing at Carnegie Mellon University's Tepper School of Business, where he also serves as Associate Dean for Research since July 2024. He holds a courtesy appointment as Professor at Carnegie Mellon University's Heinz College. Dr. Singh earned his PhD in Information Systems from the University of Washington in 2008 and has established himself as a leading scholar at the intersection of economics, machine learning, and artificial intelligence. His research program focuses on developing algorithms that address economic inequality, algorithmic bias, and the societal impacts of AI. Dr. Singh employs sophisticated machine learning techniques to investigate critical business questions across multiple domains, including pricing algorithms, financial technology, housing markets, and labor economics. His work consistently bridges theoretical rigor with practical business applications, examining how AI systems affect consumer welfare, market competition, and socioeconomic outcomes. Dr. Singh's publication portfolio reveals a clear trajectory of impactful research exploring how AI and machine learning transform business practices and economic outcomes. His recent articles demonstrate particular expertise in algorithmic pricing dynamics, where he examines how personalized ranking systems affect pricing algorithms and consumer welfare. He has also made significant contributions to understanding the socioeconomic implications of automated valuation models in housing markets and the role of physical appearance in career progression through large-scale machine learning analysis. INFORMS Information Systems Society Distinguished Fellow award (youngest recipient) PhD Distinguished Alumnus by the University of Washington (2022) Carnegie Bosch Institute Chair Sandy Slaughter Early Career Award Finalist for Best Paper in Management Science 2019-2022 Finalist for Don Morrison Long Term Impact Award in Marketing 2023 2017 Adobe Data Science Research Award As a thought leader in his field, Dr. Singh serves as Senior Editor for Information Systems Research and Associate Editor for Management Science. He actively shapes research directions through committee service including the Tepper Marketing Committee, Business Technology Faculty Search Committee, and Strategic Planning for Research Committee. His teaching portfolio includes courses on Generative AI, Digital Marketing, and Data Visualization, reflecting his commitment to preparing students for the AI-driven business landscape. Dr. Singh also contributes to industry through his role as Director at PNC Financial Services' Center for Financial Services Innovation.
Rahul Telang is a Professor of Information Systems at Heinz College, Carnegie Mellon University, with a courtesy appointment at the Tepper School of Business. He has been at Heinz College since 2002 and is currently the director of the PhD program at the Heinz College. Professor Telang is also co-director of the Initiative for Digital Entertainment Analytics (IDEA) and part of Cylab and the Institute for Infrastructure Protection (I3P). Professor Telang's research broadly focuses on how Information and Communication Technologies (ICTs) and digitization impact consumers, businesses, and policies. His work spans two major domains: Digital Media Industry and Economics of Information Security and Privacy. In the Digital Media domain, he examines how digitization and piracy affect content providers, distributors, and users, with the aim of shaping optimal copyright and intellectual property policy. In the security domain, he investigates the incentives of various parties (users, firms, and hackers), market failures, and policy frameworks for information security. His recent research shows a strong focus on bug bounty programs, vulnerability disclosure economics, data breach impacts on consumer behavior, digital media consumption patterns, and the economic implications of AI on copyright policy. His work combines empirical analysis with economic modeling to provide actionable insights for both industry and policymakers, often using randomized field experiments and large-scale data analysis. Sloan Foundation Industry Study fellowship Multiple Google Faculty awards NSF CAREER award for work on economics of information security Senior editor positions at Management Science, Information Systems Research, and MIS Quarterly Professor Telang has secured extensive external funding from the National Science Foundation, National Security Agency, and industry partners for his research. He has worked extensively with industry and policymakers on media digitization issues, consulting with major entertainment companies like Disney and Warner Brothers on streaming strategies. As deputy director of the "living analytics" (LARC) project, he directs research on digital and social media analytics in collaboration with Singapore Management University. Professor Telang co-directs the IDEA center for digital entertainment analytics and contributes to Cylab's research on cybersecurity economics. His work on the Security Behavior Observatory has created infrastructure for long-term monitoring of client machines to understand security behavior, providing valuable insights into user security practices and vulnerabilities.
Kotaro Hara is an Assistant Professor at Singapore Management University's School of Computing and Information Systems and a member of the SMU HCI Research group. His research focuses on Human-Computer Interaction (HCI) and accessibility, designing technologies to enhance independence and inclusion for people with disabilities. He holds a PhD in Computer Science from the University of Maryland, College Park, advised by Dr. Jon Froehlich, and a BEng from Osaka University, advised by Dr. Fumio Kishino. Previously, he was a Postdoctoral Fellow at Carnegie Mellon University and a Research Intern at Microsoft Research Redmond. His work spans interactive tools for accessibility, leveraging crowdsourcing and machine learning to address challenges in urban accessibility mapping, crowd work fairness, and assistive technologies for visually impaired individuals. He has received numerous awards, including the CHI 2024 Honorable Mention Award and the Lee Kong Chian Fellowship, and has contributed to influential projects like Project Sidewalk. Hara has taught courses such as Interaction Design and Prototyping at SMU and has mentored over 40 students across graduate, undergraduate, and visiting programs. His grants total over $1.9 million, including leadership in projects like 'Improving Fairness and Accessibility of Crowd Work' and 'Mobile-Friendly Data Visualization.' He actively serves in roles such as CHI 2025 Accessibility Co-Chair and IMWUT Associate Editor, promoting accessibility and ethical HCI practices globally.
