Vincent Conitzer
Faculty, PI
Vincent Conitzer is a Professor of Computer Science (with affiliate/courtesy appointments in Machine Learning, Philosophy, and the Tepper School of Business) at Carnegie Mellon University. He directs the Foundations of Cooperative AI Lab (FOCAL) at CMU, whose goal is to create foundations of game theory appropriate for advanced, autonomous AI agents -– with a focus on achieving cooperation. (More detail at the FOCAL site.) Vince has also done early work on aligning (narrow) AI systems, and has various other recent interests related to the alignment of future AI systems such as the shutdown problem, aligning AI that understands the world more deeply than we do, what LLMs tell us about ourselves, and even AI consciousness.
Aran Nayebi
Faculty
Aran Nayebi is an Assistant Professor at Carnegie Mellon University’s Machine Learning Department, a core faculty member of the Neuroscience Institute, and holds a courtesy appointment in the Robotics Institute. His lab, the NeuroAgents lab, works at the intersection of neuroscience & AI to reverse-engineer
animal intelligence and build the next generation of autonomous agents, safely and responsibly.
Aydin Mohseni
Faculty
Aydin Mohseni is a scientific philosopher and assistant professor in the Department of Philosophy at Carnegie Mellon University. His research centers on two questions: how scientific communities produce knowledge, and how agents represent the world, value outcomes, and act. His work on agency focuses especially on artificial intelligence, including the foundations of AI safety, agency, and alignment. He uses Bayesian inference, decision and game theory, network theory, and agent-based modeling to study problems ranging from scientific funding and reform to causal reasoning and value learning in artificial agents. He is a member of CMU’s Institute for Complex Social Dynamics and the center for Conceptual Foundations of Safe AI.
Sven Neth
Faculty
Sven Neth is Assistant Professor of Philosophy at the University of Pittsburgh. He works on decision theory and formal epistemology with applications to AI safety, for example modeling what happens when we optimize proxy utility functions.
Simon DeDeo
Faculty
Simon DeDeo is a Professor in Social and Decision Sciences and leader of Proofs & Reasons.
Proofs and Reasons asks basic questions about one of our most long-running and fundamental human activities: mathematics, mathematical thinking, and mathematical proof. What is mathematics? How do we do it? How will AI change it?
Proofs in Practice: the cognitive science of how humans discover and make sense of mathematical proofs. How do we prove things?
Transcendental Structures: the formal study of mathematical proof itself (complexity, type theory, metamathematics, logic). What is the space of mathematical truth?
Cyborg Proofs: the use of AI to discover and verify proofs, with and without human aid. What tools can we build, and how will they alter mathematics?
Nihar Shah
Faculty
Nihar B. Shah is an Associate Professor in the Machine Learning and Computer Science Departments. His research is on evaluation of science, including safety and alignment of autonomous AI scientist systems.
Bryan Wilder
Faculty
Bryan Wilder is an Assistant Professor in the Machine Learning Department at CMU, where he leads the Lab for AI and Social Impact. The lab develops foundations for safe AI systems and collaborates with partners like governments and health systems on their deployment and evaluation. A recent focus of his work is developing a "behavioral science" for AI models: understanding how models form beliefs, make decisions, experience incentives, and so on, and how these dispositions contribute to safety-relevant behaviors.
Derek Leben
Faculty
Derek Leben is Teaching Professor of Business Ethics at the Tepper School of Business. He teaches courses on ethics and technology, including the undergraduate course "Ethics of Emerging Technologies" and the MBA course "Ethics and AI." Dr. Leben's research focuses on principles of fairness and safety, and how organizations can make use of traditional ethical theories to develop and justify standards for responsible usage of AI. He is author of the books Ethics for Robots (Routledge, 2018) and AI Fairness (MIT Press, 2025). Course syllabi and samples of published work can be found at: derekleben.com.
Ida Mattsson
PhD Student
Ida Mattsson is a PhD student in the Philosophy department; Logic, Computation and Methodology program. She is interested in questions of alignment and safety from the perspective of how AI systems shape interactions and collective functions. She also helps organize the Carnegie AI Safety Initiative.
Alexander Heckett
PhD Student
Alexander Heckett is a PhD student in the Computer Science department studying under Vincent Conitzer. He studies scalable oversight over graphical models, working towards an understanding of how the structure of graphical representations of arguments influences the performance of debate protocols over them. He also studies multi-agent incentive structures in AI-for-math domains.