Mehmet Sencan is the CEO of Earendil, with work spanning medical devices, biosensors, nanofabrication and optics.

Iván Godoy is an AI safety researcher who received a grant to dedicate six months full-time to upskilling and AI alignment research, with a tentative focus on agent foundations. A LessWrong account under the handle "ivan-godoy" was created in September 2025, suggesting recent entry into the AI safety community. The small grant amount ($6,000 for six months of salary support) indicates Godoy is likely based in Latin America where living costs are lower. Beyond these details, limited public information is available about Godoy's background, prior roles, or research output at this time.

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Nick Hay is an AI alignment researcher and co-founder of Encultured AI, an alignment-focused startup developing platforms for AI safety experiments. He holds a PhD from UC Berkeley (2015), where he studied metalevel control under Professor Stuart Russell, applying reinforcement learning and Bayesian analysis to how agents can learn to control their own computations. Before co-founding Encultured AI, he spent five years at Vicarious AI working on AGI approaches grounded in robotics and served as a technical researcher at the Machine Intelligence Research Institute (2017-2021). In 2021 he received a $150,000 grant from the Long-Term Future Fund to design and implement simulations of human cultural acquisition as both an analog of and testbed for AI alignment, working as a visiting scholar at CHAI advised by Andrew Critch and Stuart Russell. His research interests span reinforcement learning, value alignment, and using cultural acquisition dynamics as a lens for understanding how AI systems can learn human-compatible behavior. He first engaged with AI safety upon reading Eliezer Yudkowsky's Creating Friendly AI in 2001, interning at MIRI in 2006 and attending the Singularity Summit in 2007.

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Research Director at the Collective Intelligence Project and a neuroscientist focused on emerging technologies and the science of collectivity, following a 15‑year academic career and leadership roles at Irrational Labs and the Social Science Observatory.

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Lennart Justen (known as Lenni) is a doctoral researcher at MIT's Media Lab and the Broad Institute, co-advised by Kevin Esvelt and Pardis Sabeti. He holds a BS in Physics and Political Science from the University of Wisconsin-Madison (2022) and completed his SM thesis at MIT titled "Advancing Biosecurity in the Age of AI: Integrating Novel Detection, Suppression, and Evaluation Approaches." His research focuses on biosecurity and pandemic preparedness, spanning pathogen-agnostic biosurveillance, airborne transmission suppression, and AI capability evaluation in biology, including work on the WMDP (Weapons of Mass Destruction Proxy) benchmark and the Virology Capabilities Test. He has previously held research positions at SecureBio, the Office of the Director of National Intelligence, and the U.S. State Department, and served as a 2024-25 Fellow at the Council on Strategic Risks. As of October 2025, he also serves as Research Manager for the ERA AIxBio Research Fellowship. He received early-career funding from the Long-Term Future Fund to increase his impact as a biosecurity researcher.

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Emre Yavuz is Director of Programs at the Cambridge Boston Alignment Initiative, where he leads CBAI’s research fellowship portfolio. He also serves as a research volunteer with MIT’s AI Risk Initiative, applying insights from political science and macroeconomics to frontier AI governance and risk.

Lynette Bye is a productivity coach and AI journalist based in London, UK. She holds a BA in Psychology from Harvard University and previously researched self-control with over 3,000 participants under Angela Duckworth at the University of Pennsylvania. She has been coaching effective altruists since 2017, accumulating over 2,000 coaching sessions, with clients reporting an average of 25 additional productive hours per month. Her coaching clients include staff at organizations such as Open Philanthropy, the Future of Humanity Institute, and the Centre for Effective Altruism. In 2024, she was selected as one of eight Tarbell Fellows from a pool of over 500 candidates, a fellowship supporting early-career AI journalists, and began contributing analysis pieces on AI policy and alignment to the Transformer newsletter. She is also a board member of the Mental Health Navigator and an active community organizer in the London EA community.

Michael E. Leiter is chair of the RAND Corporation’s Board of Trustees and a partner at Skadden, Arps, Slate, Meagher & Flom LLP, where he leads the firm’s national security-focused practice. He previously served as director of the United States National Counterterrorism Center (NCTC) and has held senior roles across government and the private sector dealing with national security, intelligence, and cybersecurity matters.

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Keith Wynroe is an independent mechanistic interpretability researcher focused on attention layers in transformer models. He graduated from Trinity College, Cambridge with double first class honours and previously worked as a Research Analyst at the Forethought Foundation for Global Priorities Research, William MacAskill's global priorities research organization. He participated in the SERI MATS (ML Alignment & Theory Scholars) program, working in Lee Sharkey's stream during the Winter 2023-24 cohort, and received LTFF grants to continue independent research afterward. His research outputs include "An OV-Coherent Toy Model of Attention Head Superposition" (co-authored with Lauren Greenspan, 2023) and "Decomposing the QK Circuit with Bilinear Sparse Dictionary Learning" (co-authored with Lee Sharkey, 2024), which applies bilinear sparse dictionary learning methods to understand how query and key features interact in attention circuits.

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Nicky Pochinkov is an independent AI safety researcher and ML engineer based in Ireland, currently affiliated with Coefficient Giving. He studied theoretical physics at Trinity College Dublin and represented Ireland in both the International Mathematical Olympiad (2018) and the International Chemistry Olympiad. His research focuses on mechanistic interpretability of large language models, including machine unlearning via selective pruning, neuron modularity and specialization in transformers, and decoding residual stream activations to understand planning in LLMs. He is co-author of the paper "Dissecting Language Models: Machine Unlearning via Selective Pruning" (with Nandi Schoots, arXiv 2024). He was a scholar in the SERI MATS program working with Evan Hubinger, has served as a teaching assistant and compute infrastructure lead for the ARENA alignment research training program (versions 5.0 and 6.0), and has served as a guest lecturer for AI Safety Tokyo. He has received multiple grants from the Long-Term Future Fund totaling approximately $200,000 for independent AI safety research.

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Nikola Moore is a linguistics researcher and recent graduate (Class of 2025) from the University of Pennsylvania, where she also completed graduate study with research interests spanning sycophancy, calibration gaps, computational pragmatics, anthropomorphism, and theoretical linguistics. Originally from central Europe and fluent in seven languages (including two programming languages), she has focused her academic work on the intersection of linguistics and large language models. At Penn, she spearheaded "The New Mind" workshop series on the safety and social impact of AI and LLMs, funded by a Draw Down the Lightning grant from the Penn Linguistics Society, attracting around 100 participants and featuring speakers from OpenAI and the AI Governance and Safety Institute. She also led the AI4Good Research Incubator and presented theoretical linguistics research at the FASL 33 conference. In 2024, she received a $5,000 grant from the Long-Term Future Fund to run a 9-month programme helping language and cognition scientists repurpose their existing skills for longtermist research.

K. Eric Drexler is an American engineer and researcher best known for pioneering molecular nanotechnology and authoring works such as Engines of Creation and Nanosystems. More recently, he has focused on advanced AI risk and governance, developing the Comprehensive AI Services (CAIS) framework and writing the AI Prospects Substack series on options in a hypercapable world, while advising organizations such as the Centre for the Governance of AI and the Center for AI Risk Management & Alignment.

Gidi Kadosh is a social entrepreneur and CEO of VIVID who focuses on scaling effective personal-growth and mental-health tools. He founded the Effective Altruism Israel nonprofit and, within about two years, led it from a small volunteer group to an established organization with around eight employees, thousands of community members, and large projects such as academic courses at Tel Aviv University and the Maximum Impact program.

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Heiner Benking is an internationally known independent journalist, science writer, and curator with a background in geosciences and geophysics. A Senior International Expert in Structured Democratic Dialogue at the Future Worlds Center, he has supported dialogue design and futures-oriented projects on global change, environmental issues, governance, and youth engagement since the 1970s.

Richard Hames is a Research Associate at the Odyssean Institute, as well as a political theorist and journalist. He is co-author of the books “Post-Internet Far Right” and “The Rise of Ecofascism: Climate Change and the Far Right”, an editor of the volume “Crude Futures”, and a host and series producer of the Novara FM show, and is currently working on a book project on collapse with Beau-Caprice Vetch.

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Associate Professor of Electrical Engineering and Computer Science at MIT who runs the Algorithmic Alignment Group at CSAIL, developing methods to align AI systems’ behavior with human goals and societal values across multi-agent systems, human–AI teams, and societal oversight of machine learning.

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Jason Matheny is president and chief executive officer of the RAND Corporation, a nonprofit, nonpartisan research organization that helps improve policy and decisionmaking through research and analysis. Prior to becoming RAND’s president and CEO in July 2022, he led White House policy on technology and national security at the National Security Council and the Office of Science and Technology Policy, and previously served as founding director of Georgetown University’s Center for Security and Emerging Technology and as director of the Intelligence Advanced Research Projects Activity (IARPA). He has received multiple awards for his work on emerging technologies and national security, including the National Intelligence Superior Service Medal and the Presidential Early Career Award for Scientists and Engineers.

Senior Advisor at Langsikt, where he works on artificial intelligence and emerging technologies. He holds a master’s and a PhD in sociology from the University of Cambridge and has recently worked as a researcher at SNF at the Norwegian School of Economics, focusing on how media and technology function in society, with particular interest in political economy, regulation, strategy and innovation.

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Vasil Georgiev is an independent AI safety researcher based in London, UK, focused on AI control and mechanistic interpretability. He participated in the MATS (ML Alignment Theory Scholars) program's Winter 2025 cohort and subsequently received funding to continue his AI control research as a MATS extension. He is a co-author of "Ctrl-Z: Controlling AI Agents via Resampling" (arXiv 2504.10374, 2025), which presents the first control evaluation in an agent environment using BashBench, a dataset of 257 system administration tasks designed to test whether safety protocols can prevent adversarial AI agents from executing malicious code. He is also a co-author of "Evidence of Learned Look-Ahead in a Chess-Playing Neural Network" (NeurIPS 2024), where he ran exploratory experiments and first identified a key attention head mechanism in Leela Chess Zero. Prior to his AI safety work, he had a software and game development career at Sports Interactive, King, Bloomberg LP, Meta, and ElevenLabs. He holds a Bachelor's degree in Software Engineering from Sofia University "St. Kliment Ohridski" (2010-2015).

Mohammad Aflah Khan is a research software engineer at the Max Planck Institute for Software Systems (MPI-SWS) and an open-source contributor at EleutherAI. His work focuses on natural language processing, deep learning, and large language models for social good, including contributions to projects such as Pythia, Multilingual Natural Instructions, and benchmarks for advanced reasoning and hate-speech detection.([blog.eleuther.ai](https://blog.eleuther.ai/contributor-spotlight-1/))

Pseudonymous YouTuber and AI research scientist with a PhD in computer security from an Ivy League institution, creating weekly videos about the philosophy of artificial intelligence, future technology, and how technological advancements affect society, with an emphasis on accessibility and adapting to a chronic health condition.

Guillaume Corlouer is an independent AI safety researcher based in Brighton, England. He holds a PhD from the University of Sussex (Sackler Center for Consciousness Science), where he studied information flow in ECoG time series during visual perception under the supervision of Lionel Barnett and Anil Seth, with prior training in mathematics at the University of Paris-Sud. His AI safety work centers on mechanistic interpretability, applying information-theoretic and complex-systems methods to discover latent variables from neural network activations. He was a fellow in the 2023 PIBBSS program, investigating stochastic gradient descent on singular models in the context of Singular Learning Theory, and subsequently a PIBBSS research affiliate, during which he co-authored an information-theoretic study of lying in LLMs presented at the ICML 2024 Workshop on LLMs and Cognition. He also participated in AI Safety Camp 8 (2023), where his team produced the paper "Linearly Structured World Representations in Maze-Solving Transformers," demonstrating that transformers trained on maze-solving learn linear representations of maze structure.

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Data scientist with a BSc in Cognitive Science, an MSc in Computer Science, and a PhD in player modeling in video games, with past research at the MIT Media Lab and the European Space Agency; currently a Member of Technical Staff at AI Digest working on the AI Village and related projects.

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