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Fei Fang is an Associate Professor in the Software and Societal Systems Department at Carnegie Mellon University (CMU) , where she explores the intersection of artificial intelligence and multi-agent systems . Her work integrates machine learning with game theory to address challenges in security , sustainability , and mobility , aligning with the AI for Social Good mission. Ph.D. in Computer Science, University of Southern California (2016) B.Eng. in Electronic Engineering, Tsinghua University (2011) Recent research focuses on reinforcement learning , large language models (LLMs) , and human-AI collaboration . Her team’s work has been recognized with 15+ awards across prestigious venues like IAAI, AAAI, and IJCAI. Notable accolades include the 2023 Allen Newell Award , 2022 Sloan Fellowship , and NSF CAREER Award (2021) . She actively contributes to educational initiatives , including teaching "Demystifying AI for Everyone" at CMU, and has sought part-time teaching assistants for course development. Her research spans 15+ domains , including AI ethics , cyber defense , traffic optimization , and public health .

• Artificial Intelligence
• Multi-Agent Systems
• Machine Learning
• +5 more

Nihar B. Shah is an Associate Professor at Carnegie Mellon University with joint appointments in the Machine Learning and Computer Science departments within the School of Computer Science. His research focuses on developing theoretically grounded algorithms for evaluating scientific work, with applications in peer review, fairness, and human-AI collaboration. His work has impacted over 100,000 research papers and grant evaluations. Education: Ph.D. in EECS, UC Berkeley M.E. in Telecommunications, Indian Institute of Science B.Tech. in Electronics, NIT Karnataka Research Interests: Shah's group investigates the science of evaluation through machine learning, optimization, and large-scale experiments. Key areas include peer review systems, algorithmic fairness, LLM applications in science, and human-AI collaboration frameworks. Research addresses fundamental questions about research validity, funding allocation, and equitable assessment. Publication Trends: Recent work focuses on improving peer review through randomized controlled trials, security against collusion, LLM-based review systems, and bias mitigation. Publications consistently appear in premier venues (NeurIPS, PLOS ONE, AAAI) with growing emphasis on real-world deployments. Awards & Honors: Young Alumnus Medal (IISc 2024) NSF CAREER Award (2020-2025) Google Research Scholar Award (2021) Multiple best paper awards (HCOMP, ICLR) Research Group & Funding: Leads a focused research team with NSF, Google, and JP Morgan support. Alumni hold positions in academia and industry. Current projects involve large-scale evaluations of scientific work and algorithmic fairness.

• Machine Learning
• Peer Review Systems
• Algorithmic Fairness
• +4 more

Golan Levin is Professor of Electronic Art at Carnegie Mellon University's School of Art, with courtesy appointments in the School of Design, School of Architecture, School of Computer Science, and Entertainment Technology Center. From 2009 to 2022, he served as Director and Co-Director of CMU's Frank-Ratchye STUDIO for Creative Inquiry, a laboratory dedicated to supporting atypical, anti-disciplinary research at the intersection of arts, science, technology, and culture. Levin's research spans interactive art, digital fabrication, information visualization, and generative design. He explores the critical potential of visualization, generative computation for expressive form, and how abstraction connects to realities beyond language. His practice engages interactive gestural robotics, nonverbal interaction aesthetics, and tactical applications of personal digital fabrication through responsive artifacts and media provocations that highlight human-machine relationships. His publications reveal consistent innovation in real-time audiovisual systems, interactive fabrication interfaces, and pedagogic tools for artists. Key trends include slit-scan video techniques, tangible augmented-reality performance, and noise-based visualizations, demonstrating his commitment to expanding human action vocabulary through digital media while bridging artistic expression with computational systems. Levin's work has received significant recognition: Permanent collection inclusion at Museum of Modern Art (MoMA) Whitney Biennial exhibition "50 Designers Shaping the Future" by Fast Company (2012) Competitive grants from National Endowment for the Arts, National Endowment for the Humanities, Creative Capital, and Rockefeller MAP Fund As an educator, Levin teaches "studio courses in computer science" on interactive art, experimental capture, and generative design, emphasizing computation as a medium for critical inquiry. His research funding from major cultural institutions supports interdisciplinary exploration at the arts-technology nexus. The Frank-Ratchye STUDIO for Creative Inquiry, which he directed for 13 years, remains a vital hub for anti-disciplinary collaboration, continuing his legacy of fostering creative agency through technology-infused artistic practice.

• Interactive Art
• Digital Fabrication
• Information Visualization
• +4 more

Andrew Li is an Associate Professor of Operations Research at Carnegie Mellon University's Tepper School of Business since 2024, previously serving as Assistant Professor since 2018. His research bridges statistics, optimization, and machine learning with applications to healthcare operations and retail management. Current teaching: Optimization, Business Analytics Capstone, and Topics in Optimization and Statistics PhD from MIT's Operations Research Center (2018), BS in Operations Research/Applied Mathematics from Columbia University (2012) Research Focus: Dr. Li develops data-driven decision frameworks for complex systems. Key areas include: Experience-based learning models with fairness constraints (organ allocation) Anomaly detection in low-rank matrices (retail inventory accuracy) Nanoparticle-based diagnostic systems for CAD and Alzheimer's Nonstationary demand forecasting in supply chains Publication Trends: Recent work combines bandit algorithms with healthcare applications (split liver transplants, CAD detection) and retail operations (inventory accuracy). Theoretical contributions include regret-optimal policies and entrywise anomaly detection guarantees. Scientific Honors: INFORMS Nicholson Award (2018) INFORMS Pierskalla Award (2021) NSF CAREER Award (2023) Professional Leadership: Active in INFORMS and CMU committees including MBA Analytics Curriculum, Thompson Award, and ENAiBLE AI-driven retail collaborative co-founder since 2021.

• Statistics
• Optimization
• Machine Learning
• +3 more

John R Anderson is the Richard King Mellon University Professor of Psychology and Computer Science at Carnegie Mellon University (CMU), affiliated with the Department of Psychology within the Dietrich College of Humanities and Social Sciences. His research focuses on understanding higher-level cognition, particularly mathematical problem-solving, through the development of the ACT-R cognitive architecture—a computational framework simulating human cognitive processes. This architecture integrates behavioral, neural, and educational data to model learning and decision-making. Anderson’s work bridges cognitive science, neuroscience, and educational technology. He investigates how brain imaging (e.g., fMRI, EEG) can reveal the temporal dynamics of cognitive processes and improve instructional methods. His research emphasizes analyzing brain activity time courses to uncover underlying mechanisms of problem-solving and skill acquisition. Key Research Themes: Cognitive architectures, neural correlates of learning, computational models of memory, and intelligent tutoring systems. Notable Contributions: Development of the ACT-R architecture, integration of neuroimaging with cognitive modeling, and studies on skill transfer and learning strategies. Anderson’s publications include seminal books like Cognitive Psychology and Its Implications and How Can the Human Mind Occur in the Physical Universe? His work has advanced understanding of associative memory, strategic decision-making, and the application of cognitive models in educational technology. His lab, the ACT-R Research Group, collaborates across disciplines to model complex cognitive tasks and their neural foundations. Current projects analyze real-time brain activity to refine educational interventions and improve human-machine interaction.

• Cognitive Neuroscience
• Cognitive Science
• Computational Psychology
• +3 more

John Miller is a Professor of Economics and Social Science at Carnegie Mellon University (CMU) and a Research Professor at the Santa Fe Institute. His work focuses on complex adaptive systems, computational modeling, and social dynamics. He holds a Ph.D. in Economics from the University of Michigan (1988) and has held academic positions since 1990. Miller’s research explores emergent patterns in social systems through agent-based models, experimental economics, and nonlinear dynamics. His research interests span complex adaptive systems, game theory, auction markets, and behavioral economics. Notable contributions include foundational work on computational social science, the Standing Ovation Problem, and cooperative behavior analysis. Miller has authored influential books such as Complex Adaptive Systems: An Introduction to Computational Models of Social Life and A Crude Look at the Whole . He has received awards including the Elliot Dunlap Smith Award for Teaching Excellence and has led initiatives like the Open Learning Initiative. Miller’s academic leadership roles include Director of Graduate Studies at CMU and Faculty Director of the Omidyar Fellows Program at Santa Fe Institute. His work bridges economics, computer science, and interdisciplinary complexity research.

• Complex Adaptive Systems
• Economic Theory
• Game Theory
• +4 more

Nica Ross is an Associate Professor of Video & Media Design and Director of The Frank-Ratchye STUDIO for Creative Inquiry at Carnegie Mellon University's School of Drama in Pittsburgh, Pennsylvania. With a background in cinema and advanced photographic studies, Ross brings a unique interdisciplinary approach to their work, blending technology, performance, and critical theory to explore how social constructions are reinforced by technology and performance. Ross holds a B.A. in Cinema from San Francisco State University and an M.F.A. in Advanced Photographic Study from The International Center of Photography-Bard College program. Their educational background has informed their practice as both an artist and educator, with a focus on critical applied learning and transdisciplinary collaboration. Through humor and play, Nica Ross creates participatory video installations and games that challenge social constructions reinforced by technology and performance. Their creative research focuses on “social machines” that reveal and interrogate cultural constructs, with particular attention to queer theory, gender non-conforming experiences, and the politics of visibility. Ross emphasizes liveness, human connection, and critical examination of tools and contexts in their teaching and artistic practice. Ross's recent work shows a trajectory moving from traditional video and media design toward increasingly interactive and participatory forms that engage audiences directly in questioning social constructs. Their projects increasingly incorporate game mechanics, queer theory, and critical examinations of surveillance technologies, often using RGB color systems and immersive environments to challenge perceptions of reality. Ross has received notable recognition including the Frank-Ratchye Fund for Art @ the Frontier, the Lighthouse Fellowship, and residency at Baxter Street CCNY. These awards support their innovative work at the intersection of technology, performance, and social critique. As Director of The Frank-Ratchye STUDIO for Creative Inquiry, Ross connects with researchers and creators across Carnegie Mellon University, fostering transdisciplinary practice and critical engagement with technology. Their leadership in this space has created opportunities for collaborative projects that challenge conventional boundaries between art, technology, and social inquiry. Ross's work often involves collaborative teams and labs, including partnerships with musicians like Geo Wyeth, artists like Ginger Brooks Takahashi, and technical collaborators at Carnegie Mellon's Panoptic Dome. These collaborations result in immersive installations, interactive games, and critical explorations of technology's role in shaping social reality.

• Video Art
• Media Design
• Interactive Installations
• +7 more

Shuangning Li is an Assistant Professor of Econometrics and Statistics at the University of Chicago's Booth School of Business. He holds a Ph.D. from Stanford University's Department of Statistics, advised by Professors Emmanuel Candès and Stefan Wager, and a Bachelor of Science from the University of Hong Kong. Prior to his current role, he was a postdoctoral fellow in Statistics at Harvard University. His research focuses on causal inference, machine learning, and statistical methodology with applications in econometrics, networks, and genomics. **Education:** Ph.D. in Statistics, Stanford University (Advisors: Emmanuel Candès, Stefan Wager) Bachelor of Science, University of Hong Kong **Research Interests:** Causal inference in complex systems (e.g., networks, high-dimensional data) Statistical methods for experimental design and robustness Machine learning applications in genomics and reinforcement learning Randomization-based testing and knockoff filters **Recent Work Trends:** His articles emphasize methodological innovations in causal effect estimation, network interference modeling, and transfer learning. Recent work addresses challenges in stochastic congestion, multi-environment analysis, and cooperative learning frameworks. His 2024 paper advances covariate shift correction for conditional randomization tests, while his 2023 studies explore robustness in model-X inference and dyadic reinforcement learning dynamics. **Advising & Academic Background:** His doctoral training under Candès and Wager shaped his focus on rigorous statistical foundations. He has not yet listed advising relationships in available materials, but his research collaborations span academia and industry.

• Econometrics
• Statistics
• Machine Learning
• +5 more

Peter Schwardmann is an Associate Professor at Carnegie Mellon University's Department of Social and Decision Sciences within the Dietrich College of Humanities and Social Sciences. He previously served as an assistant professor at the University of Munich (LMU) and holds a Ph.D. in Economics from Toulouse School of Economics. Education : Ph.D. in Economics (Toulouse School of Economics), Undergraduate (University of Cape Town) His research focuses on biased belief formation and its implications for market outcomes and communication dynamics. Key areas include: Motivated reasoning in political polarization Mental health stigma and treatment demand Consumer misperceptions about carbon emissions Self-deception and strategic overconfidence Gender differences in social networks Recent work explores cross-partisan communication effects, climate policy targeting, and psychological drivers of economic behavior. His experimental methodology combines laboratory and field experiments to test theoretical predictions about belief dynamics. Pioneer Award (BAdW): Recognizing innovative research in behavioral economics As Director of Undergraduate Studies, he leads academic program development while maintaining active collaborations with institutions like the Bavarian Academy of Sciences and European Economic Review researchers. Current projects examine policy implications of biased belief updating in social interactions and consumer decision-making.

• Behavioral Economics
• Belief Formation
• Motivated Reasoning
• +6 more

Paolo Pedercini is an Associate Professor of Art at Carnegie Mellon University's School of Art, where he teaches experimental game design, creative coding, and animation. His work under the project name 'molleindustria' produces socially conscious games addressing environmental justice, labor rights, and ideological critique. Notable projects include Oiligarchy , Phone Story , and Every Day the Same Dream , which have gained international acclaim through exhibitions at venues like the Sundance Festival, Victoria & Albert Museum, and ZKM. Education: B.A. in Integrated Media Arts from Rensselaer Polytechnic Institute, New York (2007). Born in Northern Italy, he migrated to the U.S. in 2007 after studying in Milan. Research focuses on the intersection of digital media, critical theory, and activism. His games critique capitalist structures, consumerism, and technological ethics while exploring narrative and interactive forms. Exhibitions span museums, galleries, and digital platforms, blending art, education, and social commentary. Likelike, a space he runs, fosters experimental game development and alternative media practices. Pedercini frequently lectures globally, including at the Game Developers Conference, Ars Electronica, and academic institutions, advocating for socially engaged media creation. Grants and collaborations are integral to his work, though specific funding details are not listed. His projects often intersect with media activism, digital folk art, and interdisciplinary art-science initiatives. Personal projects include Guilty Smells , a multisensory game, and Three Sided Football , a participatory installation exploring collective dynamics. He maintains a prolific online presence through blogs, talks, and social platforms like Skeet.

• Experimental Game Design
• Digital Art
• Social Issues in Media
• +3 more

Aydin Mohseni is an Assistant Professor in the Department of Philosophy at Carnegie Mellon University , where he is also a core member of the Institute for Complex Social Dynamics . His work bridges Philosophy of Science Formal Epistemology Evolutionary Game Theory Bayesian Statistics AI Alignment Research Interests : Mohseni explores the formal, social epistemology of science through computational models, focusing on Epistemic norms and statistical reform Networks and conformity bias in belief polarization Principal-agent problems in AI alignment Inequity emergence in social dynamics Evolutionary models of cooperation and communication His research also intersects with existential risk , global catastrophic risk , and methodological challenges in the human sciences. He previously held postdoctoral positions at the University of Pennsylvania and the University of Pittsburgh , following a doctorate at University of California, Irvine . Scientific Awards : Not listed in available information. Collaborations : He has worked with scholars including Cailin O’Connor , Travis LaCroix , Simon Huttegger , and Kyle Stanford .

• Philosophy of Science
• Formal Epistemology
• Evolutionary Game Theory
• +5 more

Kevin Zollman is the Herbert A. Simon Professor of Philosophy and Social and Decision Sciences at Carnegie Mellon University, with affiliations as an associate fellow at the University of Pittsburgh's Center for Philosophy of Science and a visiting professor at the Munich Center for Mathematical Philosophy. His work bridges game theory, agent-based modeling, and the philosophy of science. Education: Ph.D. and M.A. in Philosophy, University of California, Irvine B.S. in Philosophy, Kansas State University His research focuses on the intersection of strategic reasoning and social epistemology, including evolutionary dynamics in scientific communities, signaling theory in biological and academic contexts, and computational methods in philosophy. Recent publications examine hybrid equilibria in signaling games, incentives in peer review, and the epistemic consequences of stochasticity. Kevin actively engages in public outreach, co-authoring the popular science book The Game Theorist's Guide to Parenting and contributing to discussions about applying game theory to real-world challenges. Leadership: Director, Institute for Complex Social Dynamics

• Game Theory
• Agent-Based Modeling
• Philosophy of Science
• +5 more

Joshua Schwartz serves as Assistant Professor at the Carnegie Mellon Institute for Strategy and Technology (CMIST) within Carnegie Mellon University's Dietrich College of Humanities and Social Sciences. His interdisciplinary work bridges political science, security studies, and technology policy through rigorous empirical analysis. Dr. Schwartz's research centers on three interconnected domains: military technology proliferation (particularly armed drones and reconnaissance strike systems), public opinion dynamics regarding military force and weapons of mass destruction, and gendered dimensions of international crisis bargaining. His innovative methodologies include large-N statistical analysis, survey experiments across multiple countries, and creative applications of pop culture to teach complex security concepts. His publication record reveals strong trends in nuclear deterrence theory (evident in 2024's When Foreign Countries Push The Button ), drone warfare effectiveness (2022 drone counter-terrorism study), and gender-politics intersections (2020-2023 work on female leaders). Recent articles increasingly incorporate experimental designs across international contexts, with growing emphasis on climate security linkages. 2022 APSA David Naveh Founders Award for Best Graduate Student Paper 2019 TESS Special Competition for Young Investigators award Publications in International Security , International Organization , and Security Studies Dr. Schwartz actively mentors students through courses like An Introduction to Technology and War (84-274/674) and Popcorn and Politics , while securing research funding through fellowships at Harvard, MIT, and Notre Dame. His current book project Dovish Reputation Theory: When Backing Down Makes Sense challenges conventional wisdom about military credibility.

• Military Technology Proliferation
• Public Opinion on Military Force
• Effectiveness of Military Force
• +5 more

Stuart Candy serves as an Associate Professor in the School of Design at Carnegie Mellon University and directs Situation Lab. An internationally recognized foresight practitioner, artist, and educator, his work bridges strategic futures exploration with creative media practices, resulting in globally exhibited projects featured in The Economist, Wired, and the Discovery Channel. Research Interests: Candy pioneers experiential futures methodologies through hybrid media forms including design fiction, guerrilla theater, and live action role playing. His practice-centered approach transforms abstract future scenarios into tangible social experiences, focusing on democratizing futures literacy through participatory engagement. This work critically examines how narrative, embodiment, and play can reshape collective anticipation of possible futures. Awards: While explicitly described as "award-winning" for his innovative contributions to futures practice and design, specific honors are not enumerated in available materials. Advising and Grants: Current documentation provides no details regarding graduate student supervision or externally funded research grants. Leadership: As Director of Situation Lab, Candy leads a creative research studio producing immersive futures experiences deployed in museums, public spaces, and academic contexts worldwide. The lab functions as an experimental platform for developing new methodologies in applied foresight and participatory futures.

• Strategic Foresight
• Design Fiction
• Experiential Futures
• +3 more

Michael Ian Shamos is a Distinguished Career Professor at Carnegie Mellon University's School of Computer Science, with appointments in the Language Technologies Institute and Software and Societal Systems Department. His career spans academia, law, and technology entrepreneurship, with expertise in experimental mathematics, artificial intelligence, and legal aspects of technology. Dr. Shamos earned his educational credentials through an impressive multidisciplinary path: A.B. in Physics from Princeton University (1968) under John Wheeler M.A. in Physics from Vassar College (1970) M.S. in Technology of Management from American University (1972) M.S. and M.Phil. in Computer Science from Yale University (1973-1974) Ph.D. in Computer Science from Yale University (1978) J.D. from Duquesne University (1981) His research interests bridge multiple domains with exceptional depth. In experimental mathematics, he develops computational systems that automatically generate and prove novel mathematical theorems, particularly in number theory, having contributed hundreds of new results to the field. As a leading expert in electronic voting security, he has examined over 120 voting systems for seven states and testified before Congress multiple times. His work uniquely integrates legal expertise with technical knowledge, especially regarding intellectual property in the digital age. He directs the M.S. in Artificial Intelligence and Innovation program at CMU, advising 74 students in this cutting-edge field. His publication trajectory reveals an evolution from foundational computational geometry (co-authoring the seminal "Computational Geometry: An Introduction") to contemporary issues in voting security and experimental mathematics. The consistent thread is applying computational methods to solve real-world problems with careful attention to legal and societal implications. His notable recognitions include: Industry Service Award of the Billiard and Bowling Institute of America (1996) Black and White Scotch Achiever's Award for contributions to bagpipe musicography (1991) As an educator and mentor, Dr. Shamos directs the M.S. in Artificial Intelligence and Innovation program and teaches courses including "AI & Future Markets" and "The Law of Computer Technology." He has served as an expert witness in over 360 legal cases involving computer technology and has been a statutory examiner of computerized voting systems for Pennsylvania since 1980. His extensive industry experience includes founding technology companies and serving as General Counsel for an AI company. Dr. Shamos is actively involved with the Universal Library project, which has scanned over 1.5 million books. He also serves as faculty advisor to the Carnegie Mellon Pool Team and is Curator of The Billiard Archive, reflecting his deep commitment to preserving billiards history alongside his academic pursuits.

• Experimental Mathematics
• Artificial Intelligence
• Legal aspects of technology
• +4 more