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Chu Chen is an AI safety researcher who has been involved with the ML Alignment & Theory Scholars (MATS) program. In Q4 2022, they received a Long-Term Future Fund grant of $96,000 covering one year of salary to support upskilling in technical AI alignment research, indicating a career transition into the field. Their LinkedIn profile lists MATS as an affiliation, suggesting participation in the MATS scholar program as part of this transition.
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Out of This Box: The Last Musical (Written by Humans)
A leading Canadian research university founded in 1957, home to AI safety-relevant research programs including technical AI safety grants from Coefficient Giving and CIFAR's Canadian AI Safety Institute program.
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ControlAI is a nonprofit advocacy organization working to keep humanity in control of advanced AI by pushing governments to prohibit the development of artificial superintelligence.
AI Safety Hungary is a Budapest-based nonprofit that runs educational programs and career support to help Hungarian students and professionals enter the AI safety field.
Daniel Schwarcz is the Fredrikson & Byron Professor of Law and a Distinguished University Teaching Professor at the University of Minnesota Law School. His scholarship focuses on insurance law, financial regulation, consumer protection, and the growing role of artificial intelligence in legal practice and legal education, and he has led multiple empirical studies on how generative AI affects legal work and legal training.
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Founder and CEO of Heron AI Security Initiative, a non-profit based in Tel Aviv that bridges the gap between frontier AI models and the cybersecurity they need by connecting cybersecurity experts to high-leverage AI security work.
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The ARIA Lab (Aligned, Robust, and Interactive Autonomy Lab) at the University of Utah, led by Professor Daniel S. Brown, conducts research on human-AI alignment, reward learning, and AI safety. The lab develops algorithms and theory to enable AI systems to safely learn from and interact with humans.
Personal blog of Victoria Krakovna, Senior Research Scientist at Google DeepMind and co-founder of the Future of Life Institute, covering AI alignment research and related topics.
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Matthew Kenney is an AI researcher and the founder of Algorithmic Research Group, where he leads work on benchmarks, environments, and multi-agent systems aimed at understanding recursive self-improvement in AI. Before starting ARG he worked in machine learning roles in academia at Duke University and in industry at Apple and Alethea, focusing on applied machine learning and AI research.
Co-founder of the Buddhism & AI Initiative, previously COO of AI safety company Conjecture; he has been studying Buddhism since 2016 and has spent over four years living in monasteries between London, Canada, and India.
Stop AI is a grassroots activist organization that uses non-violent civil disobedience and public advocacy to demand a permanent, enforceable global ban on the further development of frontier AI technology.
CFG is an independent think-and-do tank based in Brussels that helps policymakers anticipate and govern powerful emerging technologies including advanced AI, biotechnology, climate interventions, and neurotechnology.
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AI Safety Camp 2026 project: Bidirectional Failure modes between security and safety
Inda Harahap serves as Outreach & Communications Lead for the AI Whistleblower Initiative (AIWI) within Whistleblower-Netzwerk e.V.
Dan Valentine is a Member of Technical Staff at Anthropic, where he works on AI safety and alignment research with a focus on scalable oversight. He previously worked as a full-stack software engineer in Toronto, Canada, before transitioning into technical alignment research with support from the Long-Term Future Fund. He participated in MATS Summer 2023 (cohort 4.0) under the mentorship of Ethan Perez. During and after MATS, he contributed to research on debate as a scalable oversight method, co-authoring "Debating with More Persuasive LLMs Leads to More Truthful Answers" (ICML 2024 Best Paper/Oral), which demonstrated that LLM debate helps both non-expert models and humans answer difficult questions more accurately. He is also a co-author on "Failures to Find Transferable Image Jailbreaks Between Vision-Language Models" (ICLR 2025), and contributed to earlier work on mesa-optimization using toy models (AISC8, 2023). Prior to focusing on AI safety, he studied at Dublin City University (2009-2013) and was involved in organizing the Toronto AI Safety community.
PhD student in the Algorithmic Alignment Group at MIT advised by Dylan Hadfield-Menell, studying AI agent alignment to human preferences in open-ended settings, human–AI teaming, and decision making across NLP, vision, and robotics.
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Zershaaneh Qureshi is a podcast host and researcher associated with 80,000 Hours, where she co‑hosts episodes of The 80,000 Hours Podcast and authors problem profiles and articles on AI risk, including work on risks from power‑seeking AI systems and AI‑enhanced societal decision making. She holds a master’s degree in mathematics and philosophy from the University of Oxford, and previously worked as a researcher providing market intelligence to the global water industry before shifting her focus to AI safety and strategy.
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Research manager at ACS helping to set up and run ACS Research, with a Master’s degree in theoretical physics from Charles University and previous experience as executive director of an NGO running international physics competitions.
12-month salary to continue developing research agenda on new ways to make LLMs directly useful for alignment research without advancing capabilities
Secretary of the Existential Risk Observatory with a degree in Classics, working as an editor at a publishing house and a literary magazine, and active as a translator and occasional writer.
Robert Kirk is a Research Scientist at the UK AI Security Institute (AISI), where he is the acting lead of the alignment red-teaming sub-team, focusing on stress-testing model alignment to detect and understand model propensities relevant to loss-of-control risks. He completed his PhD at UCL's DARK Lab in January 2025, supervised by Tim Rocktäschel and Edward Grefenstette, with his dissertation on generalisation in LLM fine-tuning and reinforcement learning agents. Prior to his PhD he received an integrated Master's in Mathematics and Computer Science from Somerville College, Oxford, and worked as a software and infrastructure engineer at Smarkets. His research centers on generalisation in reinforcement learning, out-of-distribution robustness, AI safety and alignment, and evaluating the effects of RLHF on language model behaviour and diversity. He received a Long-Term Future Fund grant to perform human evaluations for evaluating different machine learning methods for aligning language models, and his paper "Understanding the Effects of RLHF on LLM Generalisation and Diversity" (2023) is widely cited in the alignment research community. He also contributes to the Alignment Newsletter covering interpretability and reinforcement learning, and serves as a mentor in the MATS program for the UKAISI red-teaming stream.
James is the Director of Community and Partnerships at Giving What We Can, where he helps support and grow the organisation’s network of givers. An experienced aid worker, he has led international development and humanitarian teams and from 2019 to 2024 lived and worked across Somalia, Kenya and Rwanda. He holds a bachelor’s degree in Philosophy, Politics and Economics from the University of Oxford.
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Funding to support PhD in AI Safety at Imperial College London, technical research and community building
INESIA is France's national institute for AI evaluation and security, a government coordination structure that federates ANSSI, Inria, LNE, and PEReN to evaluate AI systems, analyze systemic risks, and support AI regulation.
