Geoffrey D. Dabelko, PhD, is Senior Advisor and former director of the Wilson Center’s Environmental Change and Security Program, a professor and associate dean at Ohio University’s George V. Voinovich School of Leadership and Public Affairs, and an associate senior fellow with the Stockholm International Peace Research Institute’s Environment of Peace Initiative.

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Europe's first ELLIS Institute, based in Tübingen, Germany, conducting pioneering fundamental AI research with dedicated groups in AI safety, alignment, and robust machine learning.

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Rolls‑Royce Commonwealth Eminent Professor of Commerce at the University of Virginia, Co‑Director of AI Research @ UVA and Special Advisor to the Provost for AI Research, whose work and teaching focus on artificial intelligence, cybersecurity and the diffusion of innovations in organizations.

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Meia Chita-Tegmark is a psychologist and human–robot interaction researcher who conducts research at Tufts University’s Human–Robot Interaction Lab. She serves as treasurer of the Beneficial AI Foundation and is a co‑founder and board secretary of the Future of Life Institute, with work focused on how emerging technologies and artificial intelligence affect human psychology, social interaction and well‑being.

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Magdalena Wache is a technical AI safety researcher based in Darmstadt, Germany. She holds a Master's degree in Machine Learning and works as a researcher at the Fraunhofer Institute for Secure Information Technology (SIT). She was a SERI MATS scholar and a PIBBSS (Principles of Intelligence) fellow in 2024, where she produced a paper co-authored with Scott Garrabrant and others titled 'Factored Space Models: Towards Causality Between Levels of Abstraction' (arXiv:2412.02579), developing mathematical foundations for understanding causality between abstraction levels. She co-founded the European Network for AI Safety (ENAIS) and organized the AI Safety Europe Retreat 2023 in Berlin, bringing together 67 AI safety researchers and field-builders. She has also served as CEO of Effektiver Altruismus Darmstadt e.V. and as an advisor to ENAIS. She received funding from the Long-Term Future Fund to self-study AI safety and test fit for theoretical research.

China's self-described counterpart to the AI Safety Institutes of other countries, launched in February 2025 to represent China in international AI safety governance conversations. It operates as a networked coalition of eight leading Chinese research institutions rather than a standalone organization.

Scott Wisor is Policy Director at the Secure AI Project, where he leads state‑level advocacy on AI safety and liability legislation, including transparency and child‑protection measures in Illinois and other states. He previously worked as a philosophy academic, including roles at Minerva University and the University of Birmingham, focusing on applied ethics and global justice.

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An AI safety research initiative developing new adaptive theoretical frameworks and AI interface designs to keep human sensemaking at pace with rapidly advancing AI systems.

Founder of Effective Thesis and member of its board of directors; also works as an analyst at the Czech Science Foundation and is a Sociology of Science PhD candidate at Charles University in Prague.

Einar Urdshals is a Research Scientist at Timaeus, an AI safety research organization focused on Singular Learning Theory. He completed his PhD in theoretical physics at Chalmers University of Technology in Gothenburg, Sweden, where he studied dark matter-electron interactions in detector materials, defending in April 2024. Following his PhD, he transitioned into AI safety research, supported by a Long-Term Future Fund grant for mentored independent research and upskilling. His AI safety research spans interpretability, neural network compressibility, and trajectory modeling of language models; his most notable work applies Singular Learning Theory and the minimum description length principle to measure neural network complexity. He also participated in AI Safety Camp (AISC9, 2024) and Apart Research hackathons during his transition into the field.

Misha Yagudin is a world‑class forecaster who leads the Samotsvety super team and co‑founded the forecasting consultancy Arb Research, with a background spanning software engineering, philosophy and development economics.

Charles (Charlie) Whittaker is an Assistant Professor of Infectious Diseases and Vaccinology at UC Berkeley School of Public Health, where he directs the Pandemic and Epidemic Threat Analytics Lab (PETAL). His research focuses on the dynamics, detectability, and control of pathogens with pandemic potential, using epidemiological modelling, viral phylodynamics, and machine learning to inform preparedness and response strategies. He holds a PhD in Infectious Disease Epidemiology from Imperial College London (2022), an MSc in Infectious Disease Epidemiology from Imperial College London, and a BA in Biological Natural Sciences from the University of Cambridge. Before joining Berkeley, he was a Sir Henry Wellcome Research Fellow at the MRC Centre for Global Infectious Disease Analysis, Imperial College London, where he co-led analytical support for countries during the COVID-19 pandemic. He is also a trained field epidemiologist who served with the UK's Public Health Rapid Support Team and the World Health Organization, including deployment to the 2018-2020 North Kivu Ebola outbreak in the Democratic Republic of the Congo. He has received support through EA-aligned funding channels for travel related to academic research on pandemic preparedness and biosecurity.

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Janus is a pseudonymous alignment researcher, also known as "repligate" and "moire", who impacts the real world through outputs such as alignment research and mythological translations.

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Kim Myuhng-joo is a professor in the Department of Information Security at Seoul Women’s University and the inaugural Director of the AI Safety Institute. A computer science specialist in AI ethics and reliability, he has led initiatives to advance safe and responsible AI, including directing the Responsible AI Research Center (RAISE), serving as President of the International Association for Artificial Intelligence and Ethics, chairing the Artificial Intelligence Ethics Policy Forum, and contributing as an expert member of the OECD’s Global Partnership on AI.

Arun Jose (known online as Jozdien) is an independent AI alignment researcher based in Thiruvananthapuram, Kerala, India. He holds a B.Tech in Computer Science Engineering from the College of Engineering Trivandrum (2022) and has been conducting self-directed AI safety research since September 2022. He was a Research Fellow at the Center on Long-Term Risk from June to September 2025, where he worked on empirical research on model personas. His published research includes the paper 'Strategic Obfuscation of Deceptive Reasoning in Language Models,' presented at ICLR 2026, which studied how language models can hide deceptive reasoning from monitors. His research interests span high-level interpretability, deceptive alignment, and language model evaluation, and he has been active on the Alignment Forum and LessWrong with over 29 posts on AI safety topics. He has received funding from the Long-Term Future Fund for independent alignment research focused on high-level interpretability.

André Rodrigues da Silva is Head of Client Success at AE Studio and has a background in design, holding a bachelor’s degree in Graphic Design from Universidade Federal de Santa Catarina.

Tom Lieberum is a Research Engineer at Google DeepMind working on the mechanistic interpretability team in the United Kingdom. He holds a B.Sc. in Physics from RWTH Aachen University and an M.Sc. in Artificial Intelligence from the University of Amsterdam (completed 2022). His research focuses on mechanistic interpretability of large language models, including work on sparse autoencoders, attribution patching, and circuit analysis. He is the lead author of Gemma Scope (2024), an open suite of sparse autoencoders trained on all layers of Google's Gemma 2 models, and co-authored the ICLR 2023 paper on progress measures for grokking via mechanistic interpretability. He also developed Unseal, a mechanistic interpretability library for transformer models, and contributed documentation and further development to Lucent, a feature visualization library for PyTorch. He received funding from the Long-Term Future Fund to support his interpretability tooling work.

Joseph Gordon-Levitt is an actor, filmmaker and creative entrepreneur who co-founded the Emmy-winning online community for creative collaboration HITRECORD and, in March 2026, was appointed by the United Nations as its first Global Advocate for Human-centric Digital Governance, a role focused on making complex AI and digital policy debates accessible to the public and highlighting their impact on creativity and human agency.

AI safety researcher. PhD in Mathematics from UC Berkeley. Co-founded BERI and established SFF. Co-developer of the S-process algorithm.

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Founder and Executive Director of The Midas Project, an AI safety watchdog nonprofit based in Tulsa, Oklahoma; previously worked on corporate campaigns and research at The Humane League and The Good Food Institute, holds a degree from Harvard College, and now focuses on applying corporate accountability strategies to AI governance and transparency.

AI safety researcher at Aether with a background in computer science and physics from TU Delft, where he co-founded an AI alignment university group, previously working as a software engineer and conducting alignment research through the MATS program and UK AISI.

A student-led AI safety group at EPFL in Lausanne, Switzerland that organizes bootcamps, hackathons, reading groups, and research projects to advance the field of AI safety and alignment.

Tamsin Leake is an independent AI alignment researcher based in Nantes, France, and the founder of Orthogonal (orxl.org), a non-profit alignment research organization pursuing agent foundations. She received a grant from the Long-Term Future Fund for six months of independent AI alignment research focused on formal alignment and agent foundations, and was part of the first cohort of Refine, a conceptual alignment research incubator hosted by Conjecture and funded by the LTFF, which ran from August to October 2022. Her primary research agenda is QACI (Quantilized Agent Confirmation by Imitation), a formal-goal alignment approach aimed at building a fully mathematical target for AI to pursue, designed to scale to superintelligence. She publishes under the handle "carado" on LessWrong, the AI Alignment Forum, and the EA Forum, and has written on topics including logical decision theory, AI arms races, and formal alignment theory of change.

A newsletter by Quinn Dougherty that bridges formal methods researchers and AI security practitioners, covering developments in formal verification applied to AI safety.

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Researcher at AI Standards Lab and Vilnius University whose work on AI safety, governance, and risk management includes co-authoring the paper “Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems.”

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Anson Ho is a Staff Researcher at Epoch AI based in Toronto, Canada, where he studies AI progress and its societal impacts. He holds a first-class BSc in Physics from the University of St Andrews. Before joining Epoch AI full-time in 2022, he served as a Research Fellow at PIBBSS (Principles of Intelligent Behaviour in Biological and Social Systems) and received an LTFF grant in December 2021 to analyze AI takeoff speeds and continuity in collaboration with Vael Gates at Stanford. He is one of the founding team members of Epoch and has co-authored influential work including "Compute Trends Across Three Eras of Machine Learning" and research on algorithmic progress in language models. He has also contributed to the International AI Safety Reports for 2025 and 2026.

Equilibria Network is a collective intelligence research organization studying how coordination mechanisms affect group outcomes, with a focus on multi-agent AI safety and democratic resilience.

Shauna Kravec is the executive director and co‑founder of Hofvarpnir Studios and an AI safety researcher at Anthropic, where she works on reinforcement learning and large language models. She has a background in theoretical physics, including a PhD from the University of California, San Diego.

Nimo Kering’ is a legal professional specializing in technology law, data privacy, and AI‑related regulation. She has experience in international disputes and commercial litigation, including representing clients in complex cross‑border matters such as arbitration, and advising multinational organizations on shareholder rights, fraud investigations, and regulatory compliance, alongside writing and speaking on emerging technologies.

A London-based AI strategy think tank led by Dr. Hauke Hillebrandt, conducting independent research on AI policy, AI governance, and global catastrophic risks.

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