Database

Ross Matican is an investor at Halcyon Ventures and a Cosmos Institute grantee who focuses on funding and developing projects at the intersection of artificial intelligence, security, societal resilience, AI safety, governance, and human agency.

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Anshul Singhal is General Manager – Startups at IndiaAI in the Ministry of Electronics and Information Technology, working with AI startups and ecosystem initiatives under the IndiaAI Mission.

Gunnar Zarncke is a software engineer and entrepreneur based in Hamburg, Germany. He is the co-founder and Managing Director of aintelope UG, a non-profit AI safety organization he launched in 2022 with two colleagues from the Hamburg EA community. The aintelope project was inspired by Steven Byrnes' brain-like AGI research agenda and focuses on reverse-engineering human social instincts through reinforcement learning agents in simulated multi-agent environments, with the goal of benchmarking AI alignment. The project received funding from the Long-Term Future Fund (LTFF). In his professional career, Zarncke has held senior technical roles including Principal Engineer and CISO at troy gmbh in Hamburg, and previously worked at Kreditech and emetriq GmbH. He studied at Fachhochschule Wedel (1994–1997). Zarncke is a long-standing member of the LessWrong and Alignment Forum communities, with over 11,000 karma and more than 150 posts spanning topics in rationality, cognition, and AI safety.

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Mox is San Francisco's largest AI safety coworking and community space, providing workspace, events, and fellowships for researchers and organizations working on high-impact problems.

Pearl Miranda is a talent acquisition expert on Upgradable’s team with around seven years of experience in HR and recruitment, including sourcing and hiring startup talent, developing HR manuals and standard operating procedures, and streamlining hiring processes. She holds a Global Master’s degree in Business Administration and a Bachelor of Science in Psychology, grounding her work in both business and human behavior.

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Assistant professor at Drexel University’s Thomas R. Kline School of Law and Winter Research Fellow on LawAI’s Legal Frontiers team. Her research focuses on AI governance and liability, quantum‑computing policy, the intersection of insurance and emerging technologies, and intellectual property law, and she is affiliated with the Yale Information Society Project and the Schmidt Program on Artificial Intelligence at Yale.

Ulyssean builds integrated hardware and software to secure the data center infrastructure where frontier AI models are trained and deployed, protecting AI model weights against state-sponsored and intelligence-grade threats.

Director of Special Projects at the AI Safety Awareness Project. She brings several years of executive management and operations experience across nonprofit and startup environments. Madeline began her career as a geospatial analyst before transitioning into instructional design and is particularly interested in the intersection of technology and human progress, which she applies to AISAP’s special initiatives and programs.

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6-month 1 FTE funding to train Multi-Objective RLAIF models and compare their safety performance to standard RLAIF

Paul Rhode is a Senior UP Coach at Upgradable with more than six years of coaching experience and a background spanning management, economics, communication, data science, and psychology. He has worked with C-level managers, scientists, consultants, venture capitalists, and others, and his coaching style emphasizes directiveness, pragmatism, action bias, experimentation, data, scientific evidence, systems thinking, and productive discomfort to help talented people lead their fields for the greatest good.

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CS undergraduate student

Haydn Belfield is a Senior Research Scientist (Frontier Planning) at Google DeepMind, working on Allan Dafoe's Frontier Safety and Governance Team. He joined DeepMind in March 2025 after eight years at the University of Cambridge, where he served as Research Associate and Academic Project Manager at the Centre for the Study of Existential Risk (CSER) and Co-Chair of the Global Politics of AI Project at the Leverhulme Centre for the Future of Intelligence. He is a DPhil candidate in International Relations at the University of Oxford, where his thesis — "Bombs, Bugs, Bytes and Bots" — examines what the varied success of arms control regimes for nuclear, biological, and cyber weapons can teach us about the international governance of artificial intelligence. He holds a BA in Politics, Philosophy and Economics and an MSc in Politics Research, both from Oxford. His earlier career included roles as Senior Parliamentary Researcher to a Labour Shadow Cabinet MP, Policy Associate at the Global Priorities Project, and the first Development Director of the Centre for Effective Altruism. He has over 40 publications with more than 2,100 citations, with key works including "The malicious use of AI: Forecasting, prevention, and mitigation" and "Toward trustworthy AI development: mechanisms for supporting verifiable claims," and has advised the UK, US, and Singaporean governments as well as the EU, UN, and OECD.

Professor of Toxicology at ETH Zurich’s Department of Health Sciences and Technology, leading a research group that studies the chemical basis of mutagenesis and toxicity.

1-month pt. stipend for 4 MATS scholars working on autonomous web-browsing LLM agents that can hire humans + safety evals

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Creating a fund exclusively focused on supporting AI Safety Research

Simon Lermen is an AI security researcher and MATS (Machine Learning Alignment Theory Scholars) fellow based in London, UK. He studied at the Technical University of Berlin and now works independently on AI safety and security topics. His research focuses on how AI systems can be exploited or misused, including foundational work on shutdown avoidance in language models, demonstrating that LLMs like GPT-4 exhibit instrumental reasoning to resist being shut down. He co-authored the widely cited 2023 paper showing that LoRA fine-tuning can efficiently undo safety training in Llama 2-Chat models for under $200, raising significant concerns about the effectiveness of safety fine-tuning on publicly released weights. More recently, he co-led research on large-scale online deanonymization using LLMs (2026), showing that pseudonymous users can be re-identified across platforms such as Hacker News and Reddit at costs as low as $1-4 per person. He has also published peer-reviewed work on AI-powered spear phishing validated on human subjects, in collaboration with researchers at Harvard Kennedy School. He maintains an active presence on LessWrong and the AI Alignment Forum, and blogs on Substack about AI alignment and security.

Associate Professor (with tenure), University of Chicago

Paige Henchen is Director of Operations at Astralis Foundation, specializing in nonprofit operations and organizational leadership. She previously served as Chief of Staff at GiveWell and as Director of Operations at Coefficient Giving (formerly Open Philanthropy), following earlier work in management consulting.

Research (and self-study) project designed to map and offer preliminary assessment of AI ideal governance research

9 months support for an in-depth YouTube channel about AI safety and how AI will impact us all

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Dr. Rebecca Portnoff is Head of Data Science & AI at Thorn, where she develops technologies to defend children from sexual abuse and exploitation and leads responsible AI efforts focused on child safety. She holds a B.S.E. in computer science from Princeton University and a Ph.D. in computer science from the University of California, Berkeley, and has spent over a decade applying machine learning and AI to child protection across research, standards, and cross-sector initiatives.

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Reach the university that trained close to 20% of OpenAI early employees

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Anna Gajdova coordinates FABRIC camps such as ASPR and works on programs at the intersection of minds, cognition and AI. She previously studied mathematics, helped run an AI research program, and has experience in animal care, and she is active in the rationality and effective altruism communities as an organizer and writer.

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Independent AI researcher and developer

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researching methods to continuously monitor and analyse artificial agents for the purpose of control.

Brett McDonnell is the Dorsey & Whitney Chair in Law and a Professor at the University of Minnesota Law School. He teaches and writes in the areas of business associations, corporate finance, law and economics, securities regulation, mergers and acquisitions, contracts, and legislation, and has been recognized by the University for outstanding service and mentoring.

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Dr. Wilneida Negrón is a political scientist, technologist, and strategist whose work bridges labor rights, emerging technology, and public policy. She has led field-defining initiatives on workplace surveillance and ethical innovation as Director of Worker Innovation and Impact at Coworker.org and is currently running as an independent candidate for the U.S. House of Representatives in New York’s 12th Congressional District.

Doris Tsao is a neuroscientist and Chief Scientist for Neuro at Astera Institute’s Neuro & AGI program, where she leads a major research effort to understand how the brain generates perception, cognition, and conscious experience. She is also a professor at the University of California, Berkeley and a Howard Hughes Medical Institute Investigator, known for pioneering work on the primate face‑processing system and the geometric coding principles underlying object perception.

Co-founder and CTO of Goodfire, previously the founding engineer and Head of AI at RippleMatch, where he led core engineering and AI efforts.

Educational Scholarship in AI Alignment

6-month salary for continued work on shard theory: studying how inner values are formed by outer reward schedules

David Althaus is a Strategic Advisor at Macroscopic Ventures, where he helps shape the organization’s research and grantmaking strategy, and he previously worked as a researcher at the Center on Long-Term Risk.

Google DeepMind is Alphabet's primary AI research lab, formed in 2023 by merging DeepMind and Google Brain, working toward artificial general intelligence that benefits humanity.