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Nikiforos Pittaras is a Greek machine learning researcher and engineer currently working as an ML Research Engineer at the Digital Safety Research Institute (UL Research Institutes), where he focuses on safety evaluations of large language models. He holds a PhD in machine learning from the Informatics and Telecommunications department of the University of Athens, an MSc in Signal and Information Processing from the University of Athens, and a BSc in Computer Science from the University of Ioannina. His doctoral thesis was titled "Beyond Deep Learning: Enriching Data Representations for Machine Learning Tasks." His AI safety work includes a cooperative reinforcement learning project on detecting and penalizing betrayal patterns in self-interested agents, undertaken at AI Safety Camp 2022 and supported by the EA Long-Term Future Fund. He also served as a Teaching Assistant on Machine Learning, Deep Learning, AI Safety, and Alignment at the Center for AI Safety's ML Safety Scholars program. His broader research background spans NLP (argument mining, event detection, summarization), computer vision, audio, and multimodal data tasks.
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The National Academies of Sciences, Engineering, and Medicine is the United States' preeminent independent scientific advisory body, providing expert consensus reports to inform government policy on science, engineering, and medicine, including AI safety and governance.
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David “davidad” Dalrymple is a Programme Director and technical advisor at the UK’s Advanced Research and Invention Agency (ARIA), where he launched and helps lead the £59m Safeguarded AI programme on mathematically guaranteed safe AI. He previously worked on technical AI safety at Oxford’s Future of Humanity Institute, co‑invented the cryptocurrency Filecoin, and has a long‑standing research background spanning computer science, neuroscience, and formal methods.
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Co-Director of the AI Safety Initiative at Georgia Tech and computer science undergraduate minoring in Law, Science & Technology, with research interests in interpretability and technically informed AI policy that protects individuals without hindering innovation.
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Executive Director of the AI Safety Awareness Project. Previously spent five years at Bridgewater Associates’ Systemized Intelligence Lab and four years as a founding engineer at Vowel.com (acquired by Zapier). He has completed stints at the Recurse Center studying formal verification, modern AI, and AI safety, and holds an A.B. in Mathematics with a secondary concentration in Comparative Religion from Harvard University. He frequently speaks on criminal AI, law enforcement, and AI safety for public-sector and crisis-management audiences.
Venture Partner at deep-tech fund Lunar Ventures and futurist researcher focused on data, cryptography, privacy, and frontier computing, publishing long-form theses via his State of the Future Substack.
Karl Berzins is the co‑founder and President of FAR.AI. He previously served as Head of Strategy at Advanced Navigation, an Australian robotics and navigation technology company, spent three years at Swire, and was Chief of Staff at a Berlin‑based software automation company. He holds a Bachelor of Engineering and a Bachelor of Commerce from UNSW in Australia.
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Marc-Everin Carauleanu is an AI safety researcher and Chief Scientist at AE Studio, based in Oxford, United Kingdom. He holds a BSc in Artificial Intelligence from Oxford Brookes University. He has previously been a Summer Research Fellow at the Stanford Existential Risk Initiative (SERI) in 2021, a Student Researcher at the Center for AI Safety (CAIS) in 2022, and received an LTFF grant in 2021 to write a paper on cognitive and evolutionary insights for AI alignment. His primary research agenda focuses on operationalizing "self-other overlap" — a concept from the cognitive neuroscience of empathy — as a mechanism to reduce deceptive behavior in AI systems. He co-authored the paper "Towards Safe and Honest AI Agents with Neural Self-Other Overlap" (arXiv:2412.16325), which was presented at the NeurIPS 2024 Safe Generative AI Workshop and demonstrated significant reductions in deceptive responses across multiple large language models.
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Alex Altair (also known as Alex Powell Altair) is an independent AI alignment researcher based in Berkeley, California, specializing in agent foundations. He leads Dovetail Research, a group whose mission is to help humanity safely navigate the creation of powerful AI systems through foundational mathematics research. He was previously a MIRI fellow, a MATS scholar, and an AI Safety Camp research lead, and is a two-time college dropout who attended Worcester Polytechnic Institute and the University of Maine. His research focuses on the agent structure problem, optimization frameworks, Solomonoff induction, and abstract entropy as they relate to understanding the nature of agency and its implications for AI alignment. He has been conducting independent AI alignment research in agent foundations since early 2022 and has received funding from the Long-Term Future Fund (LTFF) for this work. He is an active contributor to LessWrong and the AI Alignment Forum, where he has published over 70 posts.
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John Steidley is Chief of Staff at Palisade Research, supporting the organization’s work on AI safety. He has a background as a programmer and is described as being strong at chess.
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Basil Halperin is an assistant professor of economics at the University of Virginia whose research focuses on monetary economics, macroeconomic growth, and the economics of artificial intelligence. He received his PhD in economics from MIT in 2024 and previously worked as a data scientist at Uber and as a quantitative researcher at AQR Capital Management.
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Curriculum Developer & Instructor at the Center for Applied Rationality. Preston holds a PhD in philosophy from Rutgers University and has taught courses on rationality while working as a philosophy professor at Nanyang Technological University in Singapore, with research focusing on rational decision making, the value of life, and the ethics of emerging technologies.
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Biotech entrepreneur and longevity advocate, co-founder and CEO of YouthBio Therapeutics developing partial reprogramming gene therapies for age-related diseases after more than a decade in drug discovery and development.
Sophia Besch is a senior fellow in the Europe Program at the Carnegie Endowment for International Peace and an adjunct lecturer at Johns Hopkins SAIS, specializing in European defense policy, EU security and defense cooperation, and transatlantic security.
George Mason University is a large public research university in Fairfax, Virginia, notable in the AI safety and governance space for housing the Mercatus Center and for faculty research on AI scenarios and policy.
Chris Patrick is a science writer who received a $5,000 stipend from the Long-Term Future Fund (LTFF) in June 2022 to produce a guide about AI safety researchers and their recent work, targeted to interested laypeople. Working in collaboration with EA Forum user Justis (who provided editing and subject-matter support), Patrick aimed to bridge the gap between introductory AI safety explainers and highly technical blog posts by interviewing researchers and producing accessible writeups. The project resulted in at least one published piece, "AI Safety Concepts Writeup: WebGPT," posted on the EA Forum and LessWrong in August 2023, which covered Jacob Hilton's work on WebGPT at OpenAI. The grant notes described Patrick as the primary recipient with high-level science writing talent.
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Dr. Philip Fox is European AI Policy Lead at the KIRA Center in Berlin, where he works on AI governance and co-authored the International AI Safety Report. He holds a PhD in philosophy from Humboldt University Berlin and studied philosophy and economics in Bayreuth, Oxford and Berlin.
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AI researcher and entrepreneur who co-founded personalized AI startup Workshop Labs and served as its CTO, helping build a proprietary training stack for trillion-parameter models that was acquired by Thinking Machines Lab in April 2026.
MentaLeap is an Israel-based AI safety research group focused on mechanistic interpretability, applying neuroscience and cybersecurity expertise to reverse-engineer neural networks and reduce risks from advanced AI systems.
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Ross Nordby is technical staff at Anthropic working on AI safety. Before joining Anthropic, he was an independent AI alignment researcher funded by the Long-Term Future Fund, during which he worked on corrigibility frameworks, interpretability, and reinforcement learning environments. His background is in real-time graphics and physics simulation for video games; he created bepuphysics2, a widely-used open-source C# 3D physics engine, and runs Bepu Entertainment LLC. His published alignment work includes the paper "Soft Prompts for Evaluation: Measuring Conditional Distance of Capabilities" (arXiv, May 2025), exploring optimized input embeddings as a metric for latent capability discovery and automated red-teaming of language models, as well as LessWrong posts on using predictors in corrigible systems and AGI timelines. He received an honorable mention in the AI Alignment Awards Research Contest in the corrigibility category. He is based in Chicago, Illinois, and posts on LessWrong under the handle "porby".
Hannah Nobles is a cyber and AI policy specialist at OpenPolicy, where she designs and hosts policy-focused briefings and events connecting technology companies, security practitioners and policymakers. Her work includes organizing executive briefings and receptions around major security conferences such as Black Hat, helping stakeholders understand the governance, regulatory and business implications of emerging AI and cybersecurity trends.
AI safety practitioner and technical leader based in Dubai, serving as West & Central Asia Lead for Strategic Futures & Global Affairs at AI Safety Asia and co-founder of AI Safety UAE, with prior developer relations roles at IBM, Lightning AI, and SurrealDB and work on reducing medical AI hallucinations.
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