Database

Retrospective support for small virtual reading group on AI safety topics

Enabling rapid deployment of specialized engineering teams for critical AI safety evaluation projects worldwide

Chief Scientist at the UK AI Security Institute; previously led the Scalable Alignment Team at DeepMind and the Reflection Team at OpenAI, and worked on neural network theorem proving at Google Brain and computational physics and geometry at organisations including Otherlab, D. E. Shaw Research, Pixar and Weta Digital.

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Émélie Brunet is Vice‑President of Talent and Ecosystem at Mila – Quebec Artificial Intelligence Institute, where she oversees talent management, communications, events programming, and the creation of collaborative spaces that connect Mila’s scientific community, industry partners, and the public.

Professor of Data Science and Computer Science at Brown University and Director of the Center for Technological Responsibility, Reimagination, and Redesign (CNTR), whose research focuses on algorithmic fairness and the impact of automated decision-making systems in society; previously the John and Marva Warnock Assistant Professor at the University of Utah and 2021–2022 Assistant Director for Science and Justice in the White House Office of Science and Technology Policy, where he helped co-author the Blueprint for an AI Bill of Rights.

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Alparslan Bayrak is an effective altruism community builder in Turkey, founding EA Bilkent and EA Ankara, mentoring in the Open Student Program, and working to launch effective animal advocacy projects.

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Retrospective funding of salary for up-skilling in infrabayesianism prior to start of SERI MATS program

Avinash A. Independent Researcher | Formal Methods & AI Safety, a mathematical researcher specializing in the structural limits of AI alignment. The architect of the Terminal Boundary Systems (TBS) framework, which applies Category Theory to identify fundamental "safety ceilings" in agentic AI. My core work includes the ASE (Absolute Self-Explanation) Impossibility Theorem, a formal proof using Symmetric Monoidal Closed Categories and Lawvere’s Fixed-Point Theorem to demonstrate why total internal transparency is mathematically unreachable. Currently, focused on the Agda formalization of these results to provide a machine-verifiable "Axiomatic Audit" for frontier AI labs. Research aims to bridge the "missing link" between categorical logic and robust, human-centric AI autonomy.

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Special Projects Manager at the Berkeley Existential Risk Initiative since February 2025. She also works in web and data at Duke University, previously managed educational programs at the Institute for Defense & Business and the Warrior-Scholar Project, and holds a B.A. in Psychology from the University of North Carolina, where she was a Chancellor’s Fellow.

Research to enable transition to AI Safety

Stanford Artificial Intelligence Professional Program tution

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4 month salary to support an early-career alignment researcher, who is taking a year to pursue research and test fit

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Systems architect for technological sovereignty, designing frontier R&D programs at the intersection of materials science, synthetic biology, and AI to help states and institutions turn high-uncertainty science into sovereign capabilities.

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Head of Events at the Safe AI Forum (SAIF). Previously served as Events Producer for The Alan Turing Institute and has held positions with the Australian High Commission in London, the Edinburgh International Culture Summit, Georgetown University, and the British Film Institute, specializing in complex multi‑partner events that tackle global challenges.

6-month support for self study and development in ML and AI Safety. Goals include producing an academic paper while working on the "Inducing Human-Like Biases in Moral Reasoning LMs" project run by AI Safety Camp.

Identifying operational bottlenecks and cruxes between alignment proposals and executable governance.

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6-month salary to upskill for AI safety

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Translating an AI safety report (1k+ downloads) for peer-reviewed publication to formalize "Emergent Depopulation" as a novel systemic risk.

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Ex-climate tech entrepreneur building a media company to address the Metacrisis

work title: Seductive Machines and Human Agency

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Florian Dietz is an artificial intelligence researcher and data scientist pursuing a PhD in AI at Saarland University's Spoken Language Systems group. Before starting his doctorate, he worked as a consultant and freelance data scientist and built a startup based on an AI system designed to automate software and data science tasks.

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Drew Spartz is Head of the Incubation Program at Nonlinear. He previously founded Superlinear, an AI safety bounty platform, the Nonlinear Network funding platform, and a digital media company, and has also helped manage a family office. The team bio notes that he is an avid reader and traveler who has visited more than 50 countries.

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6-month salary to work on the research I started during SERI MATS, solving alignment problems in model based RL

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Patrick Stadler works on shaping a safe and flourishing future at the Swiss think tank Pour Demain. He co-founded and chairs the board of the GiveWell-recommended nonprofit New Incentives, which he helped scale to over 100,000 users for its vaccination program in Nigeria. Previously, he served as a political advisor for Switzerland’s economic development agency and worked on strategic communications for peacebuilding and mediation at the United Nations.

AI and neurotech advisor to Lionheart Ventures and Chief Scientific Officer at the Flow Research Collective, where he applies deep learning and distributed machine learning to understanding and training optimal human performance.

Nova DasSarma is the financial director and co‑founder of Hofvarpnir Studios and a systems leader at Anthropic, where she works on large-scale training and infrastructure. Her background includes systems administration at the NIH, engineering roles at several Y Combinator startups, and a BS in Information Systems from the University of Maryland, Baltimore County.

6-month salary for self-study to be more effective at AI alignment research