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Eli Sugarman is Director of Special Projects at the William and Flora Hewlett Foundation, where he focuses on catalytic opportunities at the intersection of security and emerging technologies, and serves on the Board of Directors of the Institute for Security and Technology as well as boards of organizations such as ROOST and Girl Security.
4 weeks expenses for FAR Labs Residency for research group focusing on goal-directedness in transformer models
Educator turned Director of Waitlist Zero advocating for the passage of the End Kidney Deaths Act & the prevention of kidney failure
6-month salary for two people to find formalisms for modularity in neural networks
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Programme and Research Director at the School of International Futures, with over twelve years’ experience delivering strategic foresight and research projects for governments, non‑profits and academic institutions.
Stipend to produce a guide about AI safety researchers and their recent work, targeted to interested laypeople
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Strategic advisor at the AI Objectives Institute and Program Co-Lead for the AI Supply Chain Observatory, where she applies interdisciplinary expertise in ecology, science communication, and AI ethics to address disruptions in life-sustaining supply chains. She is also known as the co-founder of MICRO, a distributed network of small science museums.
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Leap Labs builds AI-powered interpretability tools to accelerate scientific discovery by finding patterns in complex datasets that humans and standard methods miss.
Chair of the Long-Term Future Fund and a Program Associate at Open Philanthropy, with prior experience as a researcher at AI Impacts and as a trader and software engineer at a crypto hedge fund; she has been a research fellow at the Centre for the Governance of AI at the Future of Humanity Institute and holds a BA in Computer Science and Engineering from MIT.
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Jerremy Holland is Director of AI Research at Apple, where he leads the AI Research group working on artificial intelligence and machine learning for areas such as autonomous systems, natural interaction, and health and wellness, and he serves as chair of the board of directors at Partnership on AI. He has an extensive track record in AI and machine learning research and holds multiple patents in the field.
Alfie Lamerton is a UK-based AI safety researcher and founder of Formation Research, an organization focused on quantifying and minimizing lock-in risk — the risk that harmful or oppressive features of the world become permanently stabilized, particularly through AI-enabled authoritarianism and power concentration. He is also a part-time research assistant at King's College London working on clinical machine learning benchmarking, and holds an MSc from King's College London. He participated in the MARS (Mentorship in Alignment Research Students) London programme, through which he conducted a literature review on in-context learning hypotheses and their implications for automated AI alignment research, supported by a Long-Term Future Fund grant. His research interests span lock-in risks, recommender system alignment, AI-enabled totalitarianism, and governance-informed technical interventions. He writes about these topics on his Substack and has published related work on LessWrong.
Patrick Mellor previously taught philosophy at San Francisco State University, has conducted research on episodic memory and temporal perception, biogeography and vertebrate phylogeny, and herring communication, and holds a BSc in Biological Sciences and an MA in Philosophy from San Francisco State University.
Director of Sage, the nonprofit behind AI Digest, Fatebook, and Quantified Intuitions, with a background in computer science, philosophy, and HCI research and previous work at Clearer Thinking.
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Educational scholarship in AI safety
Executive Director of Effective Thesis, leading its work to empower students to focus their theses and careers on the world’s most pressing problems by providing programs, resources, and initiatives such as the Effective Thesis Pledge and Effective Thesis Fellowship that help them use academic research as a pathway to real-world impact.
SangZi Wang is an independent researcher focused on LLM behavioral reliability, interaction dynamics, and runtime observability. With a background in reconstructive and plastic surgery, his work bridges long-term human-AI interaction observation with practical auditing methodologies for large language models. His current research explores how conversational environments, protocol structures, and long-context interactions influence model behavior over time. Core topics include: - behavioral drift in extended dialogue, - protocol-induced response distortion, - execution confidence vs epistemic confidence (EC–EpC gap), - cross-model behavioral comparison, - runtime observability and interaction ecology. Rather than focusing on AGI speculation, his work emphasizes measurable behavioral phenomena emerging in real-world interaction settings. He has released multiple public Zenodo preprints and datasets, maintains structured GitHub repositories, and develops open behavioral audit frameworks designed for reproducible evaluation across different LLM systems. His long-term goal is to build lightweight, modular infrastructures for AI behavioral auditing, interaction reliability analysis, and runtime governance that remain accessible to independent researchers outside large institutional labs.
6-month salary to conduct AI alignment research circuits in decision transformers
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Researcher at the Existential Risk Observatory with a background in mathematics, physics, and software development, providing technical expertise on AI evaluations and connecting technical and policy perspectives.
Mila is the Quebec Artificial Intelligence Institute, the world's largest academic research center for deep learning, founded by Turing Award winner Yoshua Bengio. It brings together over 1,400 researchers and professors to advance AI for the benefit of all, with responsible and safe AI as a core strategic priority.
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Project Lead of Effective Altruism Funds, with previous experience in global priorities research as a research assistant at the Global Priorities Institute (GPI), in effective altruism community building as a contractor to CEA’s community health team, and in global health policy.
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Accelerating AI Safety Research, ronak@coordinal.org
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Shaowei Lin is a mathematician and machine learning researcher whose work spans singular learning theory, spiking neural networks and program synthesis. He serves as Chief Scientist at the Beneficial AI Foundation and helps lead BAIF’s AI‑assisted formal verification and vericoding research, including contributions to projects such as Signal Shot and the vericoding benchmark.
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Joey Savoie is a leading figure in the effective altruism movement who co-founded and leads Ambitious Impact (formerly Charity Entrepreneurship), incubating new high-impact nonprofits in areas such as global health, animal welfare, and philanthropy-focused interventions.
David Scott Krueger is an AI safety researcher and Assistant Professor in Machine Learning at the University of Montreal and Core Academic Member at Mila, the Quebec Artificial Intelligence Institute, where he holds a CIFAR AI Chair and the IVADO Professorship in Responsible AI. From 2021 to 2024 he was an Assistant Professor at the University of Cambridge, where he founded and led the Krueger AI Safety Lab (KASL), an AI safety research group based in Cambridge's Computational and Biological Learning Lab. He completed his PhD training under Yoshua Bengio, Roland Memisevic, and Aaron Courville at Mila/Université de Montréal (2013–2021) and interned at Google DeepMind's AI Safety team in 2018. His research spans deep learning, AI alignment, and AI safety, with notable contributions to understanding goal misgeneralization, algorithmic manipulation, reward hacking, robustness, and learning from human preferences. In 2023 he served as a research director on the founding team of the UK AI Security Institute and initiated the CAIS Statement on AI Risk. In 2025 he founded Evitable, a nonprofit aimed at informing the public about societal-scale AI risks.
focused on open/decentralized agi, alignment and scientific progress
Events organizer at the Existential Risk Observatory with a degree in geography and prior experience in foresight and operations consulting, supporting the organization’s events.
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SERI MATS 3-month extension to study knowledge removal in Language Models
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Tyrance Billingsley II is the founder and executive director of Black Tech Street, a national initiative based in Tulsa that aims to rebuild Black Wall Street through technology and STEM by cultivating an equitable tech ecosystem for Black entrepreneurs and talent.
Create a toolkit that enables researchers to bootstrap from zero to competence in ambiguous fields, beginning with a review of individual books
Support to maintain a copy of the alignment research dataset etc in the Arctic World Archive for 5 years
Shashwat Goel is a first-year ELLIS PhD student at the ELLIS Institute and Max Planck Institute for Intelligent Systems in Tübingen, Germany, co-advised by Jonas Geiping and Douwe Kiela. He completed a dual degree (B.Tech + M.S.) in Computer Science and Engineering from IIIT Hyderabad (2019–2024) under Prof. Ponnurangam Kumaraguru. His research focuses on evaluation and benchmarking of language models, machine unlearning, and building training environments to improve LLM decision-making. He was a SERI MATS scholar, during which he contributed to the WMDP Benchmark (Weapons of Mass Destruction Proxy), a dataset measuring hazardous knowledge in LLMs and evaluating unlearning methods, published at ICML 2024 and featured in TIME Magazine. He also contributed to the Representation Engineering (RepE) paper on AI transparency, and co-authored work on corrective machine unlearning and evaluating whether unlearning methods truly remove information from model weights. His work on fairness in sequential decision-making won an Outstanding Paper Award at AAAI 2024.
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