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David Girardo is a researcher and engineer with a background in mathematics, theoretical neuroscience, and computational biology. He holds a degree in mathematics from MIT, where he also taught courses in functional programming, computation theory, and neuroscience through MIT's Educational Studies Program. He worked as an Associate Computational Biologist at the Broad Institute of MIT and Harvard, and has held positions at New Science, Gauntlet AI, and MIT before becoming an AI Engineer at Emerald Cloud Lab in Austin, Texas. In 2019, he received a $30,000 grant from the Long-Term Future Fund for independent deconfusion research in AI safety, specifically working on a research agenda connecting the internal and external views of value synthesis. His approach drew on type theory, category theory, differential geometry, and theoretical neuroscience to elucidate ontological primitives for representing hierarchical abstractions. His work was endorsed by MIRI researcher Tsvi Benson-Tilsen.

Charlotte Monico is Chief Executive Officer of Founders Pledge. A long-time member of the organization, she previously served for around six years as Chief Operating Officer and has worked in close partnership with founder David Goldberg since 2019, bringing strong strategic and operational leadership as the organization scales.

Pranav Pant is a software and quantitative developer at Graviton Research Capital and an IndiaAI Fellow of the Government of India, with a B.Tech in Computer Science and Engineering from IIT Jodhpur and research experience in deep learning and multimodal AI.

Founder of CEEALAR (formerly the EA Hotel). He has a background in astrophysics and Earth system modelling and previously ran a 3D-printing/open-source hardware business, which he pursued with an eye toward supporting effective altruism.

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Yoshua Bengio is Co-President and Scientific Director of LawZero and a full professor of computer science at Université de Montréal. A pioneer of deep learning and one of the world’s most-cited scientists, he received the 2018 ACM A.M. Turing Award, founded Mila – Quebec AI Institute, and now focuses his research and public work on mitigating catastrophic risks from advanced AI, including leading LawZero’s Scientist AI approach to safe-by-design systems.

Michael T. Parker, Ph.D. is an Assistant Dean at Georgetown University's College of Arts and Sciences in Washington, D.C., where he oversees biology and chemistry majors and advises over 200 students. He holds a B.S. in Biology from Millersville University of Pennsylvania and both an M.S. and Ph.D. in Immunobiology from Yale University. Before joining Georgetown, he served as an assistant professor of immunology at McDaniel College in Westminster, Maryland. His research focuses on domestic biosecurity policy, particularly the history of U.S. select agent regulations governing the possession, use, and transfer of dangerous biological agents and toxins. He leads a team of undergraduate researchers studying the Select Agent Regulations and created the Collection of Biothreat Risk Assessments (COBRA), an open online archive enabling scholars to track and evaluate historical trends in biothreat risk assessment. He has received funding from the Long-Term Future Fund to catalog the history of U.S. high-consequence pathogen regulations, evaluate their performance, and chart a path forward.

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H. Akın Ünver is an associate professor of international relations at Özyeğin University and a fellow in the Carnegie Endowment’s Digital Democracy Network, where his research explores how emerging technologies, disinformation, and computational methods shape conflict, diplomacy, and democratic politics.

Philip L is the creator of the AI Explained YouTube channel, and he also runs AI Insiders, a community of more than 1,000 professionals working in generative AI across 30 industries, while authoring the Signal to Noise newsletter on high-signal AI developments.

External Advisor to the Transformative Futures Institute whose research spans several areas relevant to longtermism and is currently focused primarily on AI governance; previously a Senior Research Scholar at the Future of Humanity Institute and holder of a PhD in Materials Science and Engineering from UCLA.

Abram Demski (legal first name Daniel) is an independent AI alignment researcher specializing in agent foundations. He joined MIRI (Machine Intelligence Research Institute) full-time in 2017 as part of the Agent Foundations team, a position he held until summer 2024 when MIRI pivoted toward governance, policy, and outreach. He is best known for co-authoring the "Embedded Agency" sequence with Scott Garrabrant and for his foundational contributions to the development of Logical Induction. His research focuses on deconfusion work around core concepts in AI safety including agency, optimization, trust, embedded world models, and computational uncertainty. He received a $30,000 grant from the Long-Term Future Fund in November 2019 for independent research on agent foundations, building on work developed during MIRI's Summer Fellows Program in 2017 and 2018. Since leaving MIRI he has continued independent research, currently supported through Patreon and serving as a mentor in the MATS (Machine Learning Alignment Theory Scholars) program.

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Akbir Khan is a Member of Technical Staff at Anthropic, where he works on the Horizons team focused on building safe superintelligence. He completed his PhD at the UCL DARK Lab under the supervision of Tim Rocktäschel and Edward Grefenstette, with prior academic training in Mathematics and Physics at UCL and Computer Science at Cambridge. His research centers on Scalable Oversight techniques — particularly the use of multi-agent debate to elicit truthfulness from AI systems — as well as AI control protocols and alignment auditing. His work on LLM debate, exploring whether weaker models can assess the correctness of stronger models, received a Best Paper Award at ICML 2024 for the paper "Debating with More Persuasive LLMs Leads to More Truthful Answers." Before his PhD, he co-founded Spherical Defence Labs, an AI-powered API security startup, and also worked as a Research Analyst at Cooperative AI and a Senior Researcher at Tractable.

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Kelly Anthis co-founded Sentience Institute and served as its executive director for the organizations first three years, helping to establish it through grantwriting, conference presentations, website development, and hiring and managing staff alongside co-founder Jacy Reese Anthis. Her background includes serving as Director of Communications at Sentience Politics, co-organizing a grassroots animal advocacy group, working as a front-end software engineer, and volunteering her design skills and time to multiple animal advocacy organizations.

Research Editor at ILINA, responsible for reviewing research outputs, preparing them for publication, and supporting the program’s editorial work; she is also a researcher in animal law and ethics at the International Centre for Animal Rights and Ethics.

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Daniel Colson is the co-founder and executive director of the AI Policy Institute (AIPI), a think tank that researches and advocates for government policies to mitigate extreme risks from frontier artificial intelligence technologies. His work focuses on how autonomous weapons systems and other advanced AI capabilities could affect military strategy and global political stability. Before founding AIPI, he co-founded the fintech company Reserve, which provides financial services in high-inflation currency regions, and later founded the executive assistant recruiting firm CampusPA.

Hannah Erlebach is an AI safety researcher based in the UK, currently pursuing an MSc in Machine Learning at University College London (started 2024). She graduated from the University of Cambridge with a degree in mathematics (2018-2021) and subsequently founded and ran the Cambridge AI Safety Hub as its full-time organizer until summer 2023. She was a Summer Research Fellow at the Center on Long-Term Risk in 2023, working on cooperative AI. Her technical research focuses on reinforcement learning, goal misgeneralization, and cooperative AI: she co-authored "Welfare Diplomacy: Benchmarking Language Model Cooperation" (2023), which introduced a general-sum variant of Diplomacy to benchmark cooperative capabilities of language models, and co-authored "Mitigating Goal Misgeneralization via Minimax Regret" (RLC 2025), which demonstrates that minimax regret objectives are more robust to goal misgeneralization than maximum expected value objectives. She has received multiple grants from the Long-Term Future Fund to support her independent AI safety research, including funding to complete a goal misgeneralization project for an ICLR submission.

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Jessica Cooper (also known professionally as Jessica Rumbelow) is the founder and CEO of Leap Laboratories, an AI interpretability startup based in London. She holds a PhD in model-agnostic AI interpretability, an MSc in Advanced Computer Science, and a BA in Fine Art, all from the University of St Andrews, where she also worked as a Research Scientist applying deep learning to digital pathology. She participated in the MATS (ML Alignment & Theory Scholars) Autumn 2022 cohort, during which she co-authored the widely-cited "SolidGoldMagikarp" paper with Matthew Watkins, discovering anomalous tokens that cause failure modes in GPT-2 and GPT-3 models. She subsequently worked at Aligned AI and the Stanford Existential Risks Initiative before founding Leap Laboratories in 2023, which received seed funding from the AI Risk Mitigation Fund to develop a model-agnostic interpretability engine. She serves on the Advisory Board of the London Initiative for Safe AI (LISA) and is an Affiliated Lecturer at the University of Cambridge, where she co-taught a course on Explainable AI. In March 2022, she received LTFF funding to trial a new London organisation aimed at significantly increasing the number of AI safety researchers.

Lawyer based in Spain specialising in technology regulation and AI governance, with an LL.M. in the field from the University of Edinburgh and experience in Brussels at the Center for Democracy and Technology Europe and other organisations; joined AI Standards Lab to contribute legal and policy expertise to CEN-CENELEC JTC21 standards supporting the EU AI Act.

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Charlie Rogers-Smith is Chief of Staff at Palisade Research, an organization that studies dangerous AI capabilities to better understand misuse risks and advises policymakers on AI risks. He holds an MSc in Statistics from the University of Oxford and a BSc in Mathematics from the University of St Andrews, and has conducted research at Aalto University, Imperial College London, and the Future of Humanity Institute at Oxford. He previously worked as an instructor at the Center for Applied Rationality (CFAR) and has done predoctoral ML research at Oxford and Cambridge, including interpretability work with Adrian Weller. His published research includes co-authoring the 'Badllama' paper demonstrating that safety fine-tuning can be removed from Llama 2-Chat 13B for under $200, and epidemiological work on COVID-19 intervention effectiveness. He received a $7,900 grant from the Long-Term Future Fund in September 2020 to support a research period at Oxford while applying to AI alignment PhD programs, and has written an influential career guide on pursuing technical AI alignment research.

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Sumaya Nur Adan is a DPhil candidate at the University of Oxford researching decentralized AI security infrastructure and its role in enabling trustworthy and beneficial AI deployment globally. She previously served as an AI Risk Analyst at the UK Department for Science, Innovation and Technology working on AI risk assessment, is a research affiliate at the AI Governance Initiative leading work on the Global AI majority, and has contributed to international initiatives including the ITU AI for Good Summit 2025 and the African Commission’s work on AI and human rights.

Founder and Executive Director of CARMA with over two decades of experience in machine learning and AI, focused on advanced AI safety since 2010 and also serving part‑time as Principal AI Safety Strategist at the Future of Life Institute.

Co-founder and research lead at Simplex, with extensive experience in experimental and computational neuroscience. He earned his PhD from Caltech and has over a decade of work investigating the neural basis of intelligent behavior, most recently as a researcher at Stanford, and now focuses on developing principled methods for controlling and aligning increasingly advanced AI systems.

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Jason Hoelscher-Obermaier is the Director of Research and former co-director at Apart Research, where he focuses on accelerating AI safety progress through research sprints, fellowships, and safety evaluations of large language models and other advanced AI systems.

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