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Charlie Petty is a life sciences and technology investor based in New York City who co-founded Adjuvant Capital, an investment firm focused on global public health, previously worked for the Global Health Investment Fund and Artemis Capital Partners (and its predecessor Axia Partners), and serves on the boards of multiple biotech and global health companies and nonprofits.
Jannik Brinkmann is a PhD student in Computer Science at the University of Mannheim, Germany, advised by Christian Bartelt and Paul Swoboda. He holds an M.Sc. in Data Science (with distinction) and a B.Sc. in Computer Science, both from the University of Mannheim. His research focuses on mechanistic interpretability of neural networks, including sparse autoencoders, causal mediation analysis, and the internal mechanisms underlying multi-step reasoning and cross-lingual representations in large language models. He has worked as a visiting researcher in the interpretable neural networks group at Northeastern University under David Bau, and in the ML2 group at NYU under He He. He received a Long-Term Future Fund grant to support part-time interpretability research in collaboration with David Bau and Logan Riggs, resulting in work on improving sparse autoencoder training methods and measuring progress in dictionary learning for language model interpretability.
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Founder @ On AIR with Aashka | Certified AI Governance Professional | Bug Bounty Hunter @ Anthropic | HBR Advisor | Interviewed by Finnish Media, NPR, France24
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Director at Apart Research
Member of technical staff at Anthropic focused on AI safety and reinforcement learning infrastructure, previously led AI safety programs at BlueDot Impact, and currently serves as an advisor to Formation Research.
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Coordinal Research builds automation tools to accelerate AI safety and alignment research. The organization develops AI-powered scaffolds and workflows that help researchers conduct alignment experiments faster and at greater scale.
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AI safety research
Dawn Song is a Professor of Computer Science at UC Berkeley and co-director of the Berkeley Center for Responsible, Decentralized Intelligence (RDI). Her research focuses on AI safety and security, agentic AI, deep learning, security and privacy, and decentralization technology, and she has received major honors including a MacArthur Fellowship, Guggenheim Fellowship, NSF CAREER Award, Sloan Research Fellowship, and ACM SIGSAC Outstanding Innovation Award.
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TruthfulAI is a non-profit AI safety research organization based in Berkeley that studies situational awareness, deception, and hidden reasoning in large language models.
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6-month stipend for a small group of collaborators to continue research on the Agent Structure Problem
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Luca De Leo is a Co-founding Director of BAISH (Buenos Aires AI Safety Hub) and an AI safety community builder based in Buenos Aires, Argentina. He studied Computer Science at the University of Buenos Aires (UBA), leaving the master's program to focus full-time on AI safety work after receiving grants from ACX+ and the Long-Term Future Fund to develop relevant research skills. He worked in operations at Nonlinear and facilitated AGI Safety Fundamentals courses, growing the AI Safety community at UBA to over 130 active members. He has achieved multiple competitive placements in Apart Research sprints and participated in AI safety hackathons organized at EAGx LatAm. His current work includes co-directing BAISH, serving as a facilitator for BlueDot Impact's AGI Strategy course, and part-time operations for the AI Species YouTube channel.
A 3-month fellowship in Cape Town, connecting a global cohort of talent to top mentors at MIT, Oxford, CMU, and Google DeepMind
Revealing Latent Knowledge Through Personality-Shift Tokens
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Sienka Dounia is a technical AI safety researcher originally from Chad, currently based in London after relocating to work on Eliciting Latent Knowledge (ELK) research with Jake Mendel at Apollo Research. She is a 2023 fellow of the ILINA Program (Initiative for Longtermism in Africa) and a 2024 fellow of the AI Futures Fellowship in Mexico, where she worked on developmental interpretability and singular learning theory. She is an AI Safety Content Associate and Knowledge & Systems Lead at Successif, a platform supporting professionals transitioning into AI risk reduction roles. She is also a researcher at the African Hub on AI Safety, Peace and Security at the University of Cape Town, and a co-author of the 2025 paper "Assessing the Case for Africa-Centric AI Safety Evaluations," which develops a risk taxonomy for frontier AI deployments in African contexts. Her research interests include model evaluation, model interpretability, AI deception, and the technical governance of advanced AI systems.
Geodesic Research is a technical AI safety organization based in Cambridge, UK, focused on implementing and measuring pre- and post-training methods to improve model safety and alignment.
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Policy researcher at the Existential Risk Observatory with a background in regulatory policy in government and a tertiary qualification in economics, preparing submissions and policy proposals on AI existential risk.
Program Director for Talk to the City at the AI Objectives Institute, focused on building technology for knowledge curation and large-scale qualitative data. Before joining AOI she managed a DARPA research portfolio on how machines can help humans understand complex geopolitical systems and holds a PhD in computational modeling from the University of Florida and a B.S. in Symbolic Systems from Stanford.
Co-founder and founding advisor of Sage who led software development for the early Quantified Intuitions calibration and pastcasting tools and serves as a director of Sage Future Inc on corporate filings.
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6-month stipend to work on an ML safety project, with the aim of joining a ML safety team full-time after
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Senior Campaigner at the Existential Risk Observatory, founder of Conjointly and the Campaign for AI Safety, with a background in marketing and management consulting and a focus on AI safety advocacy.
A research organization focused on reducing risks of astronomical suffering (s-risks) from advanced AI, with emphasis on conflict prevention and cooperation between transformative AI systems.
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Andy Graham is a Chartered Mechanical Engineer and Fellow of the Institution of Mechanical Engineers who co-founded Amodo Design, a Sheffield-based multi-disciplinary engineering consultancy, after earning a first-class Mechanical Engineering degree from the University of Sheffield.
Kathleen Fisher is Chief Executive Officer of the Advanced Research and Invention Agency (ARIA). She previously led DARPA’s Information Innovation Office, overseeing more than 50 programmes, and founded a centre at RAND applying AI and formal methods to cybersecurity. She holds a PhD in computer science from Stanford and is a Fellow of AAAS and ACM.
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Marcus Williams is an AI safety researcher currently working on deception and scheming monitoring at OpenAI. He completed his Master's degree in engineering physics and machine learning at Lund University in 2023. After graduating, he worked at AI Safety Hub Oxford on a theoretical reinforcement learning project, co-authoring "On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning," which was accepted at ICLR 2024. He received a Long-Term Future Fund grant for a six-month independent project on Multi-Objective Reinforcement Learning from AI Feedback (MORLAIF), which produced an arXiv paper demonstrating that decomposing preference modeling into multiple principles outperforms standard RLAIF baselines. In the MATS Summer 2024 cohort under mentor Micah Carroll, he researched annotator vulnerabilities and LLM influence on human preferences, resulting in the paper "Targeted Manipulation and Deception Emerge in LLMs Trained on User Feedback" (accepted at NeurIPS workshops). He is also a co-author on "Stress Testing Deliberative Alignment for Anti-Scheming Training" alongside researchers from OpenAI and Apollo Research.
Researcher at Anthropic whose prior roles include researcher at Google and PhD student at the Technical University of Munich; his expertise spans AI safety and alignment as well as graph neural networks and machine learning on molecules.
Vael Gates is a researcher and field-builder focused on improving the safety of AI systems to reduce potential large-scale risks from advanced AI. They completed a PhD in Computational Cognitive Science at UC Berkeley in Tom Griffiths's lab, working on computational models of social cognition, and subsequently held a postdoctoral fellowship at Stanford University jointly with HAI (Human-Centered AI Institute) and CISAC (Center for International Security and Cooperation). During their Stanford postdoc, they conducted structured interviews with nearly 100 AI researchers about their perceptions of risks from current and future AI systems, publishing results as the "Risks from Advanced AI" (2022) and "Risks from Highly-Capable AI" (2023) series on the EA Forum and LessWrong. They previously founded Arkose, an AI safety field-building nonprofit providing informational resources and support calls to machine learning researchers and engineers interested in entering the field (closed June 2025). They subsequently served as Head of Content at FAR.AI, leading content programming for the FAR.Futures division including global conferences, workshops, and community engagement. As of early 2026, Vael is the Founder and Executive Director of Humans in Control, a bipartisan grassroots organization focused on protecting communities from risks of unchecked AI.
Executive Director of Saving Humanity from Homo Sapiens and a mathematics graduate whose work and interests shifted from academia toward existential risk and philanthropy.
