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Tegan McCaslin is a generalist researcher working at the intersection of AI forecasting, AI strategy, and AI governance. She began her research career at AI Impacts in 2018, where she studied neuroscience topics relevant to AI timelines, including brain architecture and neuron counts across species. She received multiple Long-Term Future Fund grants (2019, and subsequently) to pursue independent research into AI forecasting and strategy questions, exploring topics such as whether AI capability development parallels biological evolution and the tractability of long-term forecasting. She went on to join the Forecasting Research Institute (FRI) as a core founding team member alongside Phil Tetlock, focusing on improving the quality and decision-relevance of forecasting questions and the challenges of forecasting on long timescales. She co-authored FRI's report on Conditional Trees as a method for generating informative AI risk forecasting questions, and served as a mentor for the Epoch and FRI mentorship program for women and non-binary people interested in AI forecasting. More recently, she has expanded into AI governance work, contributing to the STREAM (ChemBio) framework at the Centre for the Governance of AI (GovAI), a standard for transparently reporting AI model evaluations of chemical and biological capabilities.
Assistant Professor of Law at the University of Houston whose research investigates how law and legal institutions can reduce catastrophic and existential risks from advanced AI systems; he also serves as executive co-director of the Center for Law & AI Risk, law and policy advisor to the Center for AI Safety, visiting senior fellow at the Institute for Law & AI, senior visiting scholar at Forethought, and contributing editor at Lawfare.
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Physics student, EA Austria Community Builder (10h/week)
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The Power Law is a Substack newsletter by Peter Wildeford (also known as Peter Hurford) covering AI forecasting, AI policy, national security, and emerging technology.
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Stanford HAI is an interdisciplinary university institute advancing AI research, education, and policy with a focus on AI that benefits humanity and augments human capabilities. It is best known for publishing the annual AI Index Report.
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Director Partnerships & Philanthropy USA for ETH Zurich Foundation USA, serving as the primary contact for U.S.-based donors and partners.
Serial tech entrepreneur and Founding Partner at Fifty Years. She previously founded the software company Applicake, co-founded Base (later acquired by Zendesk), organized large developer events in Europe, became a partner at VC fund Innovation Nest, and is a Y Combinator alum who moved to the U.S. in 2014.
SPAR is a part-time, remote research fellowship that pairs aspiring AI safety and policy researchers with experienced mentors for 3-month research projects. It is one of the largest AI safety research fellowships by participant count.
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Working title - “Compositionality and Ambiguity: Latent Co-occurrence and Interpretable Subspaces”
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Leadership coach and Program Manager for RAISEimpact, supporting people tackling pressing global challenges. Previously led software development teams at major tech companies including Amazon and Bloomberg for over a decade, and now coaches Effective Altruist managers and founders on leadership, people management, and building high-performing teams.
Zenna Tavares is a co-founder and director of Basis Research Institute, where he leads work on universal reasoning systems and causal probabilistic programming. His research focuses on how humans derive knowledge from observing and interacting with the world, and on building computational and statistical tools for causal reasoning, probabilistic programming, and scientific model discovery. He previously served as the inaugural Alan Kanzer Innovation Scholar at Columbia University’s Zuckerman Institute and Data Science Institute, completed a postdoctoral fellowship at MIT CSAIL in Joshua Tenenbaum’s group, and holds a PhD in Cognitive Science and Statistics from MIT.
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Timur Burkhanov is a Research Assistant at the Odyssean Institute with a background in cybersecurity and an interest in complex civilisational problems and conflict dynamics, particularly in the MENA and Eurasia regions. He holds an MSc in cybersecurity from Ufa State Aviation Technical University and has applied machine-learning and data-science techniques to social-impact projects, including Omdena initiatives on psychometric assessment of soft skills from meeting recordings and a chatbot to support interview preparation.
This is a small grant buying a large increase in high-quality Francophone AI risk communication from a creator who has already a track record.
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Jasper Jackson is managing editor at Transformer, overseeing day-to-day operations and editing work from staff and freelance contributors. He was previously tech editor at the Bureau of Investigative Journalism, digital editor at the New Statesman and assistant media editor at The Guardian.
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Lucid Computing builds hardware-rooted AI verification infrastructure that cryptographically proves where AI chips are located and what they are processing, enabling enforceable compute governance and regulatory compliance.
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Aleksandar (Alex) Makelov is a researcher at OpenAI working on mechanistic interpretability of large language models. He earned his PhD in Computer Science from MIT, where he was advised by Prof. Aleksander Madry, and prior to that completed Part III of the Mathematical Tripos at Cambridge University and a BA in mathematics and computer science from Harvard College. His research spans mechanistic interpretability, sparse autoencoders, adversarial robustness, and data poisoning, with papers published at ICLR 2024, ICLR 2025, and ICML 2024. He is known for work on interpretability illusions in subspace activation patching and for developing principled evaluation frameworks for sparse autoencoders. He is a SERI MATS alumnus who worked with Neel Nanda on interpretability research, subsequently joined Guide Labs, and then joined OpenAI where he co-authored work on persona features and emergent misalignment.
MIT is a private research university in Cambridge, Massachusetts, widely recognized as a global leader in science, engineering, and technology research, including AI safety and alignment.
Joe Wheeler is a Partnerships Associate for Global Catastrophic Risks at Coefficient Giving. He previously started Dropbox's Social Impact team and worked with leadership to launch the Dropbox Foundation, later leading partnerships for the UN Development Programme and WhatsApp's civic engagement program in North America. He holds an MPA in Social Impact from the London School of Economics and a BA in Politics from Whitman College.
Luise Woehlke is an AI policy researcher and programs associate at the Institute for AI Policy and Strategy (IAPS), where she works on the IAPS AI Policy Fellowship and expanding the organization's programs portfolio. She holds a Bachelor's degree in Computer Science from the University of Edinburgh. Prior to IAPS, she worked in recruitment and operations at the Centre for the Governance of AI (GovAI). Her research has focused on US AI securitization, the US regulatory process for frontier AI, and the potential for government control over AGI development. As a 2024 Pivotal Research Fellow, she co-authored a study on how involved the US government may become in developing AGI, examining historical base rates. She also received a Long-Term Future Fund grant to conduct a supervised research project on US regulatory decision-making and frontier AI, working with John Halstead, PhD.
Arati Prabhakar is an engineer and public official who served as Director of the White House Office of Science and Technology Policy and President Biden’s chief science advisor from 2022 to 2025, and earlier led the National Institute of Standards and Technology.
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Jakob Graabak is the Interim Director of the Effective Institutions Project’s Peace and Security Program, where he is building a new program focused on great-power diplomacy and emerging-technology escalation risks. He previously led the technology foresight program at the Brussels-based Centre for Future Generations, co-founded the Norwegian Center for Long-Term Policy, worked as a project lead at SecureBio, and was a fellow at the McKinsey Global Institute.
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6-months stipend for transitioning to independent research on AI Safety
Jacob Lagerros is the founder of Ulyssean, a company building integrated hardware and software systems to secure the infrastructure that trains and runs frontier AI models, with backing from leaders at Anthropic, DeepMind, Meta, and CrowdStrike. Originally from Stockholm, Sweden, he studied at the University of Oxford and partially completed an MSc in Economics and Finance at LSE before dropping out to work full-time on AI safety-related projects. He co-founded Lightcone Infrastructure, the parent organization of LessWrong, where he worked on the Campus team alongside Oliver Habryka and others. Earlier in his career, he co-directed EAGxOxford 2016, served as secretary of the Oxford Prioritisation Project, and received a Long-Term Future Fund grant in 2019 to build forecasting infrastructure giving x-risk researchers superforecasting ability with minimal overhead, collaborating with Metaculus and Ozzie Gooen on that project. He has since pivoted toward AI hardware security, co-leading the UK Secure Cluster, advising government bodies including the National Security Council on AI export controls, and presenting at the Paris AI Security Forum 2025. He is also a mentor at Pivotal Research in the area of AI hardware security.
Alex Infanger is an independent AI safety researcher based in the San Francisco Bay Area. He completed his PhD in 2022 at Stanford University's Institute for Computational and Mathematical Engineering (ICME), where he studied theory and algorithms for Markov chains. He transitioned into AI safety and alignment research, receiving Long-Term Future Fund grants for upskilling in deep learning and working on automated red-teaming and interpretability. He was a MATS (Machine Learning Alignment Theory and Surveys) Fellow, and his research has spanned machine unlearning robustness, sparse autoencoders and superposition, and reward misspecification. Notable works include "Distillation Robustifies Unlearning" (NeurIPS 2025 spotlight), "Misalignment from Treating Means as Ends" (arXiv 2025), and "Eliciting Language Model Behaviors using Reverse Language Models" (NeurIPS SoLaR Workshop 2023 spotlight). He also facilitated AGI safety fundamentals reading groups with the MIT AI Alignment Team in Fall 2022.
A shared platform to discover, evaluate, and fund high-impact AI safety work.
Co-founder of EquiStamp, a third-party evaluator that provides objective evaluations of frontier language-model systems and has served as a key contractor to METR on projects such as RE-Bench.
Managing Director at the Center on Long-Term Risk, where he leads work on reducing s-risks from powerful AI systems. Previously a researcher at CLR focusing on s-risk macrostrategy, he also led the community-building team and studied mathematics at the University of Cambridge and the University of Warwick.
Alexander Lintz (also known as Alex Lintz) is an AI governance researcher and entrepreneur based in Washington, DC. He is a co-founder and AI governance advisor at the Institute for AI Policy and Strategy (IAPS) and has helped launch several organizations in the AI safety and governance space, including The AI Governance Archive (TAIGA), the AI Safety Communications Centre (AISCC), and the Long-term AI Strategy Retreat (LAISR). In 2022, he co-organized LAISR in Washington, DC, a longtermist AI strategy retreat for approximately 35 researchers and practitioners, alongside Ashwin Acharya of Rethink Priorities. He has served as an affiliate and contractor for Rethink Priorities' AI Governance & Strategy team and has contributed feedback to foundational AI governance research including work by Allan Dafoe. He received grants from the Long-Term Future Fund for independent distillation and coordination work in the AI governance and strategy space, and earlier for organizing a career-focused workshop for European effective altruists interested in AI governance careers, which he ran with collaborators from EA Zürich. He is active on the EA Forum (handle: LintzA) where his posts on AI governance and democratic politics have received substantial engagement.
Alex Chao, founder of Fide AI. Alex leads benchmark design, evaluation methodology, research writing, and public release. Additional expert reviewers and research contributors will be recruited for scenario generation, rubric validation, and adjudication. His experience spans building AI systems, algorithms, models, and evaluations across places like Uber ATG (self-driving cars), Microsoft, and Bytedance.
