Luke Muehlhauser |   Executive Director
Luke Muehlhauser is MIRI’s Executive Director. He has written dozens of articles and papers on metaethics, intelligence explosion theory, and the cognitive science of rationality and human motivation, including “Intelligence Explosion: Evidence and Import” and “A Crash Course in the Neuroscience of Human Motivation.” Previously, he studied psychology at the University of Minnesota.
Louie Helm |   Deputy Director
Louie Helm supports organizational development, strategic planning, and talent recruitment at MIRI. He has written several articles to help guide future donors and researchers including “How to Save the World” and “Recommended Courses for MIRI Researchers.” He also co-authored “Intelligence Explosion and Machine Ethics” with Luke Muehlhauser, which appears in the academic volume Singularity Hypotheses (Springer, 2013). Louie holds a Masters in Computer Science from the University of Texas at Austin and has published peer-reviewed research in applied mathematics, quantum computing, and machine ethics.
Malo Bourgon |   Project Manager
Malo Bourgon works as a dedicated Project Manager, MIRI’s Volunteer Manager, and the primary contact for new job applicants, potential interns, visiting fellows and other interested individuals. Malo holds a Masters in Engineering from the University of Guelph.
Alex Vermeer |   Management Analyst
Alex Vermeer works to improve MIRI’s operations and output by measuring useful data, identifying inefficiencies, and improving processes. Alex also handles MIRI’s web development and manages MIRI’s document production team. Alex holds an Engineering degree from the University of Guelph.
Eliezer Yudkowsky |   Research Fellow
Eliezer Yudkowsky is the foremost researcher on Friendly AI. In 2001 he published the first analysis of motivationally stable goal systems, with his book-length Creating Friendly AI. He has since written many other papers, including two chapters in the edited volume Global Catastrophic Risks (Oxford, 2007): “Cognitive Biases Potentially Affecting Judgment of Global Risks” and “AI as a Positive and Negative Factor in Global Risk.” He is also well known for his writings on rationality, including “An Intuitive Explanation of Bayes’ Theorem,” the Less Wrong Sequences, and Harry Potter and the Methods of Rationality.
Benja Fallenstein |   Research Fellow
Benja Fallenstein does mathematical research on Friendly AI, including problems of self-reference and issues in decision and game theory when an AI reasons about future versions of itself or about other, similarly powerful agents in its environment; models of logical uncertainty, i.e., uncertainty about what mathematical statements are true; models of anthropic reasoning; and the specification of safe AI goals. Benja is also interested in formal verification and in programming languages with integrated proof checkers. Benja holds a Bachelors in Mathematics from University of Vienna.
Nate Soares |   Research Fellow
Nate Soares is broadly interested in Friendly AI research, specifically reflective trust, decision theory, game theory, and goal specification. He has undergraduate degrees in computer science and economics, and often studies mathematical logic, probability theory, category theory, and type theory. Nate previously worked for Google.
Katja Grace |   Research Assistant
Katja Grace’s research at MIRI focuses on social and historical questions related to artificial intelligence outcomes. She recently wrote Algorithmic Progress in Six Domains. She is sometimes a PhD student in Logic, Computation & Methodology at Carnegie Mellon University. She writes the blog Meteuphoric.
Rob Bensinger |   Research Assistant
Rob Bensinger focuses on attempts to relate human categories and preferences to physical phenomena. He has a BA in Philosophy and a certificate in History and Philosophy of Science, both from Indiana University. His research interests include consciousness studies, value theory, and the psychology of moral, religious, and broadly theory-dependent reasoning.
Alex Altair |   Research Associate
Alex Altair researches trusted reasoning formalisms for autonomous systems. He published “A Comparison of Decision Algorithms on Newcomblike Problems” and co-authored the “Intuitive Explanation of Solomonoff Induction.” He graduated from the Maine School of Science and Mathematics, and studied physics and mathematics at university.
Mihaly Barasz |   Research Associate
Mihaly Barasz is interested in functional languages and type theory and their application in formal proof systems. He cares deeply about reducing existential risks. He has an MSc summa cum laude in Mathematics from Eotvos Lorand University, Budapest and currently works at Google.
Paul Christiano |   Research Associate
Paul Christiano recently finished an undergraduate degree in mathematics at MIT and is now a graduate student at UC Berkeley. His research on algorithms and cryptography has been presented at top conferences in theoretical computer science. In 2008 he was one of six students to represent the U.S. at the International Mathematics Olympiad. He is also the lead author of MIRI research paper “Definability of Truth in Probabilistic Logic.”
Daniel Dewey |   Research Associate
Daniel Dewey works on the theory of artificial general intelligence. His current research focuses on optimality notions for physically implemented AGI, motivated self-deception, and goal safety. Daniel has a BSc in Computer Science from Carnegie Mellon University. You can find more of his work at danieldewey.net.
Marcello Herreshoff |   Research Associate
Marcello Herreshoff has worked with MIRI on the math of Friendly AI from time to time since 2007. In high school, he was a two time USACO finalist and he published a novel combinatorics result, which he presented at the Twelfth International Conference on Fibonacci Numbers and Their Applications. He holds a BA in Math from Stanford University. At Stanford he was awarded two honorable mentions on the Putnam mathematics competition, and submitted his honors thesis for publication in the Logic Journal of the IGPL. His research interests include mathematical logic and its use in formalizing coherent goal systems.
Bill Hibbard |   Research Associate
Bill Hibbard is an Emeritus Senior Scientist at the University of Wisconsin-Madison Space Science and Engineering Center, currently working on issues of AI safety and unintended behaviors. He has a BA in Mathematics and MS and PhD in Computer Sciences, all from the University of Wisconsin-Madison. He is the author of Super-Intelligent Machines, “Avoiding Unintended AI Behaviors,” and “Decision Support for Safe AI Design.”
Patrick LaVictoire |   Research Associate
Patrick LaVictoire is interested in the mathematics of decision theory: when different algorithms can read one anothers’ source code before choosing actions, there are some Gödelian strategies that provably do better than causal decision theory. Patrick has an AB in Mathematics from the University of Chicago and a PhD in Mathematics from the University of California at Berkeley, and is currently a Van Vleck Visiting Assistant Professor of Mathematics at the University of Wisconsin-Madison.
Kaj Sotala |   Research Associate
Kaj Sotala is interested in the strategic questions related to AI risk. He has authored and co-authored several papers on the topic, including “Responses to Catastrophic AGI Risk: A Survey,” “How We’re Predicting AI — or Failing To,” “Advantages of Artificial Intelligences, Uploads, and Digital Minds,” and “Coalescing Minds: Brain Uploading-Related Group Mind Scenarios.” Kaj holds a BA in Cognitive Science from the University of Helsinki, where he is currently studying Computer Science.
Nisan Stiennon |   Research Associate
Nisan Stiennon is interested in formal decision theory—the mathematical study of the way abstract agents behave, and what this implies about the values and behavior of humans. Nisan has a PhD in mathematics from Stanford and works with the Center For Applied Rationality.
Pennsylvania State University
Global Catastrophic Risks Institute
University of Oxford
Future of Humanity Institute
Massachusetts Institute of Technology
George Mason University
Economic Growth Given Machine Intelligence
Fundamentals of Whole Brain Emulation
Rational Artificial Intelligence for the Greater Good
Massachusetts Institute of Technology
Foundational Questions Institute
University of Louisville
Artificial Intelligence Safety Engineering
Vice President of Engineering
Chief Executive Officer
Chief Executive Officer
Chief Science Officer
Machine Intelligence Research Institute