Database

Buddhist chaplain, meditation teacher, social entrepreneur, and co-founder of the Buddhism & AI Initiative; he holds a Master of Divinity in Buddhism from Columbia University’s Union Theological Seminary and previously worked as a founder, CMO, startup operator, and strategy and innovation consultant at Deloitte.

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Aidan Ewart is an AI safety researcher and mathematics undergraduate at the University of Bristol (2022-2026), based in the UK. He has participated in the MATS program as a Research Scholar, working primarily on adversarial robustness and latent adversarial training (LAT). He interned at Haize Labs (July-October 2024) in New York, where he built automated red-teaming infrastructure and contributed to red-teaming of OpenAI's o1 models and contract work with Anthropic. His published research includes co-authoring 'Sparse Autoencoders Find Highly Interpretable Features in Language Models' (ICLR 2024), 'Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs' (NeurIPS 2024), and 'AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors' (2026). He has received funding from the Long-Term Future Fund for independent research on LM interpretability and for a MATS 5.0 extension focused on improving methods in latent adversarial training.

No summary available yet.

Darryl Wright is an AI safety researcher and advisor who received a Long-Term Future Fund grant to conduct independent AI safety research, focusing on two projects: penalizing neural networks for learning polysemantic neurons, and crowdsourcing alignment research from volunteers. He holds a Master's in Physics and a PhD in Astrophysics from Queen's University Belfast, where his doctoral research applied machine learning to transient survey classification using data from the Pan-STARRS1 survey. He subsequently held research positions at the University of Minnesota's Minnesota Institute for Astrophysics, the University of Oxford, and Mayo Clinic Rochester, where he worked on machine learning applications in healthcare. He also contributed to the Zooniverse citizen science platform, investigating how AI and citizen scientists can cooperate on data-intensive research problems. He has served as a mentor for the Supervised Program for Alignment Research (SPAR) and is currently an AI policy and law advisor at Successif.

Develop proposals for off-switch designs for AI, including policy games, that have been rigorously evaluated for their effectiveness, technical feasibility and political viability

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CEO and Founder of the Odyssean Institute

A micro-project to turn an early AI governance prototype into risk notes, oversight checklist, review templates and public learning.

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Sijia Liu is a Red Cedar Distinguished Associate Professor in the Department of Computer Science and Engineering at Michigan State University and an affiliated professor at IBM Research and the MIT‑IBM Watson AI Lab. He received his Ph.D. in Electrical and Computer Engineering from Syracuse University, then worked as a postdoctoral research fellow at the University of Michigan and as a research staff member at the MIT‑IBM Watson AI Lab. His research focuses on scalable and trustworthy AI, including scalable optimization for deep models, machine unlearning for vision and language models, AI robustness and data‑model efficiency, and his work has been recognized with honors such as an NSF CAREER Award, the INNS Aharon Katzir Young Investigator Award, MSU’s Withrow Rising Scholar Award and best paper accolades at venues including UAI and ICASSP.

Alex Lintz is an independent researcher specialising in AI governance, affiliated with the Institute for AI Policy and Strategy and co-founder of the AI Safety Communications Centre. He previously worked at the Centre for the Governance of AI, has led workshops on AI safety, and holds a master’s degree in economics from the University of Zurich.

@Bayesian on manifold markets

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Austin Carson is the founder and CEO of SeedAI, a Washington, D.C.–based nonprofit focused on AI policy, governance, and national AI readiness. He previously established and led NVIDIA’s Washington, D.C. government affairs operation and spent several years as a congressional technology staffer, including roles with the House Homeland Security Committee and the Congressional Cybersecurity and High Tech Caucuses.

No summary available yet.

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Formalizing perceptual complexity with application to safe intelligence amplification

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Gunnar Schaefer is a strategic advisor involved with multiple healthcare and technology companies, including AE Studio, MedLever, Gradient Health, Trenser Technology Solutions, Polygon Health, Stratagen Bio, and Nakamir, where he applies extensive experience in technology-driven innovation and digital transformation.

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Funding 2 years of technical AI safety research to understand and mitigate risk from large foundation models

David Bloomin is a founder and chief architect-type leader at Softmax. He previously spent about two decades building large-scale infrastructure at Google, Facebook, and Asana, co-founded the Plurality Institute, and led research on multi-agent AI frameworks and governance methods.

Akash Kundu is a final‑year computer science undergraduate and Cooperative AI Research Fellow whose work in technical AI safety focuses on evaluating and stress‑testing large language models. His projects have uncovered behavioural failures such as dark patterns, sycophancy, harmful reasoning and multilingual vulnerabilities, and he has co‑authored work presented at venues including ICLR, AAAI and NeurIPS in collaboration with groups like Apart Research, FAR AI and Humane Intelligence.

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Help me to organize US moratorium-promoting activities to expand the Overton window and increase public pressure in favor of a moratorium on frontier AI.

Making God is now raising for post-production so we can deliver a festival-ready documentary fit for Netflix acquisition.

Elizabeth Van Nostrand is an independent freelance researcher and founder of North Sea Analytics, a consultancy offering research and analysis on complex, novel problems. She studied computer science and computational biology at Cornell University and previously worked as a software engineer at companies including Adobe, Google, and Wave before transitioning to full-time freelance research in 2017. She writes at her blog Aceso Under Glass (acesounderglass.com) and is an active contributor to LessWrong (username: elizabeth, formerly pktechgirl), where she has accumulated over 22,000 karma across 178 posts. Her research work has focused on epistemic methodology, including the Epistemic Spot Checks and Knowledge Bootstrapping projects aimed at developing tools for researchers to evaluate sources and learn new fields from scratch without deferring to credentialed authorities. She has received grants from the Long-Term Future Fund for this knowledge bootstrapping work and for general research support via Lightcone Infrastructure, and her essays have been included in the LessWrong community anthology The Engines of Cognition.

former AGI alignment at MIRI, now human intelligence enhancement

Dr. Tamara Kneese is a Senior Research Scientist at Partnership on AI, where she leads qualitative research on the social and environmental impacts of AI and digital technologies. She previously directed Data & Society’s Climate, Technology, and Justice program and its Algorithmic Impact Methods Lab, and her work examines how data infrastructures and automation affect labor, communities, and the environment.

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Senior Researcher at CARMA and U.S. Public Policy Lead within the Public Security Policy program, bringing incident‑response and emerging‑technology policy expertise from prior U.S. government roles.

Co-founder of VaHive Systems Lab and co-architect of MAGUS — a runtime governance architecture addressing structural alignment drift in deployed AI agents. AI governance and architecture specialist working at the intersection of formal system design and real-world deployment safety.

Upskilling in contemporary AI techniques, deep RL, and AI safety, before pursuing a ML PhD

Alignment Researcher • Software & Data Engineer • BlueDot and 80,000 Hours alumnus

Generalist at Hive, Orgnizer at Effective Animal Advocacy Austria, Board Member at EA Austria

Founding Director of the UK’s AI Security Institute and Interim Director General for Artificial Intelligence at the Department for Science, Innovation and Technology.

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Co-director of Geodesic Research who transitioned from a biomedical sciences background into technical AI safety, helping to formalise and grow Geodesic into a better-funded alignment research organisation.

Michael Karasik is an AI researcher affiliated with mentaleap.ai, working on machine learning and AI research projects in collaboration with MentaLeap.

No summary available yet.

Jonathan Salter is a Fellow at CeSIA, contributing to the organisation’s work on AI safety and governance as part of its expert network.

No summary available yet.

Tim Winders is vice president of Information Services and chief information officer at RAND, responsible for the organization’s technology strategy and operations in support of its mission to improve policy and decisionmaking through research and analysis. He has more than 30 years of experience in higher education and nonprofit IT leadership and, prior to joining RAND, spent a decade at Purdue University and Purdue University Northwest, where he helped unify IT organizations across campuses, supported advanced research computing, and led major digital transformation initiatives. Winders holds a Ph.D. in technology, leadership, and innovation from Purdue University.

Director of CLTC’s AI Security Initiative and Co-Director of the UC Berkeley AI Policy Hub, focusing on the governance, policy, and politics of artificial intelligence, including comparative analysis of national AI strategies and mechanisms for evaluation and accountability in organizational AI development and deployment; she has published widely on AI and emerging technologies and serves on bodies such as the OECD Expert Group on AI Risk & Accountability and the IEEE Working Group on organizational AI governance.