Database

Nicole Ruiz is a non-resident fellow at the Foundation for American Innovation and director of The Third Oikos, a publication exploring how technology reshapes family life and the household. She is also a visiting fellow at the Institute for Family Studies and previously invested in frontier technology startups at seed stage as a venture capitalist at Compound.

Subhojeet Pramanik is a researcher at Softmax with an MSc from Alberta’s RLAI lab whose work focuses on reinforcement learning and representation learning. He introduced the Recurrent Linear Transformer (AGaLiTe, TMLR 2024), previously worked at IBM Research, and is the author of OmniNet, a unified architecture for multi-modal multi-task learning.

Ondrej Bajgar is a DPhil student in Bayesian machine learning at the University of Oxford, supervised by Michael A. Osborne, Alessandro Abate, and Konstantinos Gatsis. He studied mathematics at the University of Warwick and subsequently spent three years as a Research Scientist at IBM Watson, working on machine learning for text understanding and dialogue systems. He then joined the Future of Humanity Institute at Oxford as a Senior Research Scholar, where he worked on AI safety for approximately two years before beginning his doctorate. His current research focuses on active inverse reinforcement learning, developing methods to align AI decision-making with human preferences by strategically selecting informative demonstrations. He has also published work on negative human rights as a principled framework for long-term AI safety and regulation, co-authored with Jan Hořeňovský in the Journal of Artificial Intelligence Research. He received LTFF funding to support his AI safety PhD at Oxford.

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Technical AI risk analyst at ORCG and systems engineer from Universidad de los Andes, co‑founder of AI Safety Colombia, focusing on advanced AI safety and mechanistic interpretability.

Thomas Moynihan is an intellectual historian and author based in the UK, specialising in the history of ideas about existential risk, extinction, and future-oriented thought. He holds a DPhil from Oriel College, Oxford, where he researched how concerns about human extinction became a serious object of philosophical and scientific inquiry. He is a Research Affiliate at the Centre for the Study of Existential Risk at the University of Cambridge, a Visiting Research Fellow at St Benet's Hall, Oxford, and a Berggruen Fellow at the Berggruen Institute. His 2020 book X-Risk: How Humanity Discovered Its Own Extinction (MIT Press/Urbanomic) traces the intellectual history of existential risk from the Enlightenment to the present day. He received a Long-Term Future Fund grant to write a book on the philosophy and history of longtermist thinking, which is forthcoming as The History of Contingency and Future-Oriented Thought (Cambridge University Press, 2026). His writing has appeared in BBC Future, The Guardian, Aeon, Noema Magazine, New Scientist, and other publications.

Senior Marketer at Probably Good with a master’s degree in Communication Science and ongoing master’s studies in Philosophy; serves as a Marketing Advisor for Effectief Geven and has previously worked for Amnesty International, the United Nations, and advised think tanks, government bodies, and tech companies on communication strategy and impact.

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Niko McCarty is a molecular bioengineer, writer, and Fellow at Astera Institute whose work focuses on biophysics, metascience, and visual tools for explaining complex ideas. He previously worked as a data journalist, founded and serves as founding editor of the biotechnology magazine Asimov Press, and is writing a book on cell biology titled “Biology is a Burrito & Other Essays.”

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Glauber De Bona is a Brazilian computer scientist and assistant professor in the Department of Computer Engineering and Digital Systems (PCS) at the Escola Politécnica, University of São Paulo (USP). He holds a Bachelor's in Computer Engineering from the Aeronautics Institute of Technology (ITA, 2006), a Master's in Computer Science from USP (2011), and a PhD in Computer Science from USP (2016), with his doctoral dissertation focused on measuring inconsistency in probabilistic knowledge bases. He conducted postdoctoral research at University College London (2017) and USP (2018). His academic research spans probabilistic logic, inconsistency measurement and localization in knowledge bases, epistemic argumentation, and formal epistemology, with publications in venues such as AAAI and the Journal of Artificial Intelligence Research. He has described his broader research interest as mitigating existential risks posed by AI, and has been active on the Alignment Forum under the handle glauberdebona, where he has posted work on computational complexity arguments about the alignment problem. He received a 6-month stipend from the Long-Term Future Fund to transition to independent research on AI safety.

Amritanshu Prasad is an AI safety researcher and policy writer based in the United Kingdom, focused on AI evaluations, AI governance, and the intersection of nuclear risk with emerging AI. He received an upskilling grant to study the AGI Safety Fundamentals Alignment Curriculum, and has since built a career in technical AI safety work, including a research engineering role at Equistamp where he helped UK AISI develop ControlArena, an infrastructure project for evaluating protocols for controlling unaligned frontier LLMs. He has contracted with METR for baselining and model interaction tasks, and facilitated courses on AI governance and transformative AI through BlueDot Impact. He is a member of the working group on international AI governance at the Alva Myrdal Centre for Nuclear Disarmament at Uppsala University, co-authoring work on the influence of nuclear governance frameworks on AI governance. He also completed a research fellowship at Pivotal Research and is founding Suav Tech, a for-profit AI safety evaluations organization. He writes the Substack newsletter The Next Frontier, covering AI evals, AI policy, and nuclear risk.

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Assistant Professor of Computer Science at the University of Virginia who leads the Responsible AI for Science and Engineering (RAISE) group, focusing on foundational challenges in artificial intelligence, privacy, safety and the intersection between machine learning and optimization.

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Andrei Alexandru is an AI safety researcher and machine learning engineer currently working at iGent AI on Maestro, an autonomous agentic coding agent. He holds an MPhil in Machine Learning from the University of Cambridge, where his dissertation examined the inductive biases of shallow neural networks, funded by a Long-Term Future Fund grant. He previously worked on the dangerous capability evaluations team at OpenAI and at Atla, where he was first author on the Atla Selene Mini paper introducing a state-of-the-art small language model-as-a-judge. Earlier in his career he participated in the SERI MATS program under Evan Hubinger's mentorship and the ML for Alignment Bootcamp at Redwood Research. His research interests include mechanistic interpretability, AI evaluations, and understanding deceptive alignment, and he maintains the blog inwaves.io where he writes about AI safety topics.

Curriculum Developer & Instructor at the Center for Applied Rationality. Jack studied psychology and gender and has previously worked in roles including event planning, data research, and legal assistance, and is especially interested in gaming, structured analysis, and deep conversations about culture and identity.

Peter Barnett is a researcher at the Machine Intelligence Research Institute (MIRI), where he works on the Technical Governance Team focusing on international coordination and governance strategies to prevent catastrophic outcomes from advanced AI. He holds a Master's degree in Physics from the University of Otago in New Zealand, where he conducted research in quantum optics and quantum fluids. He transitioned into AI safety work through the first cohort of the MATS (ML Alignment Theory Scholars) program and subsequently worked at the Center for Human-Compatible AI on reward learning before joining MIRI in December 2022, initially on technical alignment and later shifting to technical governance. His governance research includes verification mechanisms for international AI agreements, distributed training oversight, and AI capability red-lines. He has authored a book on AI x-risk aimed at policymakers and the general public, and is active on LessWrong and the Alignment Forum under the handle peterbarnett.

Nicholas Kees Dupuis is an AI alignment researcher and entrepreneur who co-founded Mosaic Labs, a nonprofit R&D organization developing AI-facilitated group deliberation tools, where he serves as CEO alongside co-founder and CTO Sofia Vanhanen. He holds a Master's degree in Artificial Intelligence from the University of Groningen (2022), where his thesis focused on theory of mind for multi-agent coordination. He conducted research at EleutherAI under Kyle McDonell and Laria Reynolds, studying how finetuning methods can cause alignment failures analogous to those in reinforcement learning, and has published academic work on computational social choice including the paper "Condorcet Markets" (2023). He is best known in the AI safety community for his influential "Cyborgism" essay on the Alignment Forum (February 2023), which proposed a strategy of using human-in-the-loop systems to safely accelerate alignment research by empowering human agency rather than outsourcing it; he subsequently led the Cyborgism track at AI Safety Camp 2023. He received a $120,000 one-year grant from the Long-Term Future Fund to continue developing his research agenda on making LLMs directly useful for alignment research without advancing capabilities. His personal website is lovedoesnotscale.com and he maintains a Substack under the same name.

Co-founder and co-director of Geodesic Research, leading technical AI safety work within the Meridian Cambridge community.

Connor Dunlop is a researcher and strategist working at the intersection of AI governance, compute security, and geopolitics, with experience spanning frontier AI policy research, hardware‑enabled verification, foresight, and institutional design.

Journalism executive and philanthropy leader who serves as chair of the Hudson Institute Board of Trustees and previously ran business operations at Commentary magazine; she also sits on the board of the Flourishing Future Foundation, which supports research on controlling advanced AI to ensure a safe and flourishing future.

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Nick Corvino is a Tarbell AI Journalism Fellow and writer for ChinaTalk. He holds an M.A. from the Yenching Academy of Peking University, where he studied Chinese philosophy and religion, and a B.A. in philosophy and international relations from Northwestern University.

James Lester leads the Oxford AI Safety Initiative and has written about AI safety topics on the Effective Altruism Forum.

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Geoffrey Miller is an evolutionary psychologist and associate professor of psychology at the University of New Mexico. He is known for his research on sexual selection and human nature and for books such as The Mating Mind and Spent, and in recent years he has become an active public commentator on AI risk and other existential threats.

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Zachary Peck is an Assistant Professor of Philosophy at Ramapo College of New Jersey, where he joined the faculty in Fall 2025. He completed his PhD in Philosophy at the University of Cincinnati, where his dissertation was titled "Group Agency and AI," arguing that artificial systems are best understood as components embedded in cyborgian group agents rather than as independent agents. He holds an M.A. in Philosophy from Georgia State University (2018), an M.S. in Artificial Intelligence from the University of Georgia (2021), and a B.S. in Philosophy, Psychology, and History from East Tennessee State University (2015). His research sits at the intersection of philosophy of technology, philosophy of mind, cognitive science, and the ethics of AI, with a particular focus on how insights from the biological and social sciences can inform risk mitigation for digital technologies. He received a small grant to attend a CFAR (Center for Applied Rationality) workshop in Prague, reflecting engagement with the rationality and x-risk community.

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Travis Moore is the Founder and Executive Director of TechCongress, a nonpartisan nonprofit that recruits, trains, and places technologists in Congress through the Congressional Innovation Fellowship and related programs. He previously spent six years on Capitol Hill as Legislative Director to Rep. Henry A. Waxman, former chair of the House Energy and Commerce Committee, where he focused on technology policy. Moore launched initiatives including Congress’s first digital communications training program, its first Congressional staff conference, and the Congressional Digital Service Fellowship, and he co‑founded #CongressToo, a network of former Congressional staffers that helped bring the #MeToo movement to Capitol Hill. He holds a BS in Marketing from Miami University (OH) and a master’s degree in Contemporary European Politics from the University of Bath.

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Kai Sandbrink is a DPhil candidate in computational cognitive neuroscience at the University of Oxford's Department of Experimental Psychology, based at Lady Margaret Hall. He is co-supervised by Professor Christopher Summerfield at Oxford and Professor Wulfram Gerstner at EPFL, where he is also an invited guest researcher. Prior to Oxford, he completed an MS in Neural Systems and Computation at ETH Zurich and an MA in China Studies at Peking University. His research uses deep reinforcement learning as a task-driven model of human behavior, with a focus on learning dynamics, cognitive flexibility, and exploration-exploitation trade-offs. His AI-safety-relevant work includes improving deep learning's understanding of uncertainty and designing safer, more interpretable reward functions for reinforcement learning algorithms. He is an affiliate at Concordia AI and has an interest in East-West cooperation on AI safety and governance. He received a Long-Term Future Fund grant in 2021 for starting funds and moving costs related to his DPhil project.

James Payor is an independent AI alignment researcher based in Australia. He worked as Research Staff at the Machine Intelligence Research Institute (MIRI) in Berkeley from January 2018 to April 2022, and has since been pursuing independent AI alignment research. Before MIRI, he was co-founder and CTO of Draftable, a document comparison software company based in Melbourne, from 2015 to 2017. His research focuses on agent foundations, proof-based cooperation, corrigibility, and building AI systems that maintain robust alignment with human input. He is notable for developing a method for proof-based cooperation that does not require Löb's theorem, and has published work on modal fixpoint cooperation on the AI Alignment Forum. More recently he has been working on better foundations for theorem proving, computer-assisted mathematics, and dependently-typed programming languages. In his youth he represented Australia at the 2013 International Olympiad in Informatics, earning a silver medal.

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David Duvenaud is an Associate Professor at the University of Toronto and Canada CIFAR AI Chair whose research spans machine learning, AI safety and AI governance. He co-directs the Schwartz Reisman Institute for Technology and Society, co-founded the Vector Institute for Artificial Intelligence, and previously led the Alignment Evaluations team at Anthropic. He also serves as a director of The AI Safety Foundation and has advised AI companies such as Cohere.

Nora Ammann is an AI safety researcher and field-builder currently serving as Technical Specialist for the Safeguarded AI programme at ARIA (UK's Advanced Research & Invention Agency), a ~£59M R&D initiative focused on building technical foundations for independently verifiable AI safety guarantees. She co-founded and directed PIBBSS (Principles of Intelligent Behaviour in Biological and Social Systems) from 2021 until Spring 2024, a research initiative that raised over $2M and supported approximately 50 research fellows by drawing on parallels between intelligent behavior in biological, social, and artificial systems to advance AI alignment. She continues her involvement with PIBBSS (now rebranded as Principles of Intelligence) as President of the Board. Her research background spans political theory, complex systems, and philosophy of science; she is a PhD student in Philosophy and AI with the Alignment of Complex Systems group at Charles University and a Foresight Fellow. She previously worked as a Research Manager at the Future of Humanity Institute at the University of Oxford and as a Research Affiliate at the Alignment of Complex Systems research group.

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Pooja Tope-Puranik is an AI researcher and machine learning engineer working primarily in healthcare, specializing in early breast cancer detection with AI; she has held ML roles at organizations such as Omdena and AI Directions and serves as a UAE ambassador for women-in-tech communities, promoting women’s participation in STEM.

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Christine A. Parlour is Professor of Finance and the Sylvan C. Coleman Chair in Finance and Accounting at Berkeley Haas. Her research focuses on institutionally complex areas such as market microstructure, banking, payment systems, fintech, and decentralized finance, and she serves as co-director of the Berkeley Center for Responsible, Decentralized Intelligence (RDI).