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4-month stipend for 3 people to create demonstrations of provably undetectable backdoors
Hugo Larochelle is Scientific Director of Mila – Quebec Artificial Intelligence Institute, an adjunct professor at Université de Montréal, and a leading deep‑learning researcher. Previously, he led Google’s AI research lab in Montréal, and his work has helped shape modern deep‑learning systems used in industry and academia.
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6-month stipend for Sparse Autoencoder Mech Interp projects
Part-time research scientist with Truthful AI; holds a PhD in Automatic Control and Robotics and works as an assistant professor at the Faculty of Mechatronics, Warsaw University of Technology; collaborates on AI safety projects related to out-of-context reasoning in large language models.
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Swadeep Singh is General Manager – Data Science at IndiaAI, where he leads the data science function within the Government of India’s national AI mission.
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Co-founder of Impact Ops and experienced operations professional; previously served as Head of Staff Support at Effective Ventures, Operations Specialist at the Centre for Effective Altruism, and Operations Manager at Brainlabs, and holds a first-class MA (Oxon) in Psychology and Philosophy from the University of Oxford.
Co‑founder and technology advisor at the Collective Intelligence Project, formerly a research engineer at DeepMind working on multi‑agent reinforcement learning and language models, and a researcher in technology governance with groups such as the Berkman Klein Center.
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Codruta (Coco) Lugoj is an independent AI safety researcher based in London, UK. She holds a master's degree in AI and has a background in machine learning research, with particular expertise in reinforcement learning and probabilistic and variational inference, developed during her time at Radboud University. She received Long-Term Future Fund grants in 2023 and 2024 to build alignment research engineering skills and to continue her work evaluating agent self-improvement capabilities. As part of the Axiom Futures Alignment Research Fellowship, she co-authored "Auto-Enhance: Towards a Meta-Benchmark to Evaluate AI Agents' Ability to Improve Other Agents," presented at NeurIPS 2024, which proposes a meta-benchmark for measuring the ability of LLM agents to modify and improve other agents across tasks including prompt injection resiliency, dangerous knowledge unlearning, and solving real GitHub issues. Her research sits at the intersection of AI safety evaluation and agentic AI capabilities.
A flexible simulation environment for assessing strategic and persuasive capabilities, benchmarking, and agent development, inspired by reality TV competitions.
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Max Lamparth is a Research Fellow at the Hoover Institution's Technology Policy Accelerator at Stanford University, where he is also affiliated with the Stanford Intelligence Systems Laboratory and the Stanford Center for AI Safety. He holds a Ph.D. in Natural Sciences from the Technical University of Munich (2023) and B.Sc. and M.Sc. degrees in Physics from Ruprecht Karl University of Heidelberg. His research focuses on the security and safety of large language models through mechanistic interpretability, reward modeling, and robust evaluation, including developing model-internal interventions for failure modes such as backdoors and reward-proxy shortcuts. He created and teaches CS120: Introduction to AI Safety at Stanford, and his technical work has directly informed AI governance efforts through policy publications in outlets such as Foreign Affairs and the Carnegie Council for Ethics in International Affairs, as well as direct engagement with policymakers on AI legislation. His research has been published at NeurIPS, CoLM, FAccT, and AIES, and has received media coverage from MIT Technology Review, Axios, and New Scientist.
Viktoriya Malyasova is a machine learning engineer focused on AI alignment, based in the San Francisco Bay Area. She holds a Master's degree in Data Science from Skoltech (Skolkovo Institute of Science and Technology) and a Bachelor's degree in Mathematics from HSE (Higher School of Economics) in Russia. She has worked at FAR.AI (Frontier AI Alignment Research), a technical AI safety nonprofit, as well as at DeepSpin in Germany and MainsLab in Russia. She participated in the SERI MATS 2023 winter program as a scholar, where she focused on infrabayesianism — the mathematical framework developed by Vanessa Kosoy for reasoning under logical uncertainty and non-realizability. Prior to the SERI MATS program, she received retrospective funding for up-skilling in infrabayesianism, and she contributed to creating and testing educational exercises on inframeasure theory that were published on the AI Alignment Forum. She maintains a programming and machine learning blog at malyasova.github.io.
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Xin (Eric) Wang is an Assistant Professor of Computer Science at UC Santa Barbara and Director of the UCSB Center for Responsible Machine Learning, with research focusing on multimodal and agentic AI.
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Astrid Sorflaten leads operations at the Forecasting Research Institute, focusing on maximizing impact through efficient operations and project management. She previously led operations at early-stage organizations in both the nonprofit and corporate sectors, including developing systems and infrastructure for a rapidly growing team at the UK nonprofit Good Law Project.
Creator of Aura Protocol
Researcher, focusing on complex, discipline-spanning problems related to food, agriculture, and animals
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Arden Berg is an Investor at Macroscopic Ventures, working on the organization’s investment portfolio with a background in economics and prior work investigating the trajectory of AI.
Forecaster and Developer
Patricio Vercesi is an Argentine individual based in Córdoba, Argentina, with involvement in the AI safety community. He co-authored a research project titled "Public Opinion and Its Importance to AI Policy" submitted to Apart Research as part of the EAGx LatAm Epoch AI Hackathon in July 2023. He is listed as a volunteer with PauseAI, an AI safety advocacy organization. He received a small grant from the Long-Term Future Fund to study machine learning at university and pursue AI safety independently over a 10-month period, reflecting an early-career path into AI safety work.
Conor McGlynn is a doctoral candidate in Public Policy (Science, Technology and Policy Studies) at Harvard Kennedy School and a fellow at the Harvard STS Program. He holds a B.A. in Economics and Philosophy from Trinity College Dublin and an M.Phil. in Philosophy from the University of Cambridge, where he focused on ethics and public policy. Before his PhD, he worked in EU affairs in Brussels as a Robert Schuman Trainee at the European Parliament and subsequently as a government relations consultant specializing in emerging technology and biotech regulation. He was a Schwarzman Scholar at Tsinghua University in Beijing (2019-2020), where he researched the governance of lethal autonomous weapon systems, and a Fulbright Irish Schuman Awardee at the Kissinger Institute on US-China Relations in Washington D.C. (2020-2021), focusing on global governance of emerging technologies. He was an IAPS 2025 AI Policy Fellow with a project on international technology competition, and co-authored the paper "Promising Topics for U.S.-China Dialogues on AI Risks and Governance" presented at the ACM FAccT conference in 2025. He received a grant from the Long-Term Future Fund to upskill for AI governance work before beginning his Science and Technology Policy PhD.
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Joe Collman is a Technical AI Governance Researcher at the Machine Intelligence Research Institute (MIRI), where he joined the Technical Governance Team in late 2024. He holds a Bachelor's degree in Mathematics from the University of Warwick (2000-2004). His research career in AI safety began with a focus on AI Safety via Debate and iterated amplification, including a stint as a Collaborating Researcher at OpenAI in early 2020 working specifically on AI Safety via Debate, and multiple grants from the Long-Term Future Fund supporting independent research on debate algorithms and human alignment in amplification. He has also served as Technical Lead and AI Safety cause area manager at the Stanford Existential Risks Initiative, as a Technical Generalist at the Berkeley Existential Risk Initiative, and as a Teaching Fellow for BlueDot Impact's AI Safety Fundamentals course. At MIRI, he co-authored "Existing Safety Frameworks Imply Unreasonable Confidence" (2025), arguing that current AI lab safety frameworks reflect systematic overconfidence. He is an active contributor to the Alignment Forum and LessWrong under the handle joe-collman.
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Yashvardhan Sharma is an AI safety and policy researcher focused on compute governance, AI hardware, and model safety evaluation. He studied artificial intelligence, machine learning, and economics at Minerva University, where he led Minerva Effective Altruism and AI Safety. He is affiliated with FAR.AI, where he has co-authored research on adversarial AI safety including red-teaming studies of leading frontier models ("Illusory Safety") and jailbreak vulnerability analysis. He also co-authored "Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscape," examining policy implications of shifts from centralized to distributed AI training. He previously served as Office Manager at SERI-MATS and received a stipend from the Long-Term Future Fund to research specialized AI hardware requirements for large AI training runs, mentored by Asher Brass at the Institute for AI Policy and Strategy (IAPS).
Peter McIntyre is a board member of Longview Inc. Ltd, the UK legal entity of Longview Philanthropy.
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A regularly-updated guide on how to donate most effectively to the AI safety field, structured by donation amount and time available.
Senior Advisor at Langsikt, working part-time on biotechnology and security. She is trained as a molecular biologist at the University of Glasgow, Imperial College London and the Institute of Cancer Research, where her PhD was awarded H.M. The King’s Gold Medal in 2015. She has previously been a senior adviser at the Norwegian Biotechnology Advisory Board and serves as a special adviser to the Norwegian Cancer Society.