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Tahir Mahmood Saleh is passionate about building a better, more inclusive world. With hands-on experience in project management, governance, climate action, and youth empowerment, he has led and supported impactful initiatives that uplift communities and drive change. Through his work with organizations like Bridge Nigeria Initiative, DOTAKEACTION, OCCEN, and now with Center for Renewable Energy and Action on Climate Change CREACC-NG, Tahir champions citizen engagement, economic empowerment, and sustainable development, always bringing energy, empathy, and a vision for a brighter future.

Goodfire is an AI interpretability research lab that builds tools to understand and design the internal mechanisms of neural networks. Their flagship product, Ember, gives engineers direct, programmable access to AI model internals.

Jonathan Ng is a Singapore-based AI safety researcher and engineer currently working as a Project Officer at the Singapore AI Safety Institute (AISI). He completed the SERI MATS 3.1 program (Spring 2023), where he worked with the Cadenza Labs team on extending the 'Discovering Latent Knowledge' paper by contributing to the EleutherAI/elk library, running large-scale hyperparameter sweeps, and conducting original experiments in LLM probing. He holds a BComp in Computer and Information Systems Security from the National University of Singapore (2017-2021). His research includes co-authoring the MACHIAVELLI benchmark (ICML 2023), which measures trade-offs between rewards and ethical behavior in AI agents, and the Catastrophic Cyber Capabilities Benchmark (3CB, AAAI 2025 Workshop). He is also a co-author of CCS-Lib, a Python package for eliciting latent knowledge from LLMs published in the Journal of Open Source Software. Beyond research, Jonathan has been a key organizer of AI safety capacity-building in Singapore, founding the Research Engineering Camp for Alignment Practitioners (RECAP), directing AI Safety Fellowships at NUS and NTU, and serving as an instructor at the ML4Good Singapore bootcamp. He received funding from the Long-Term Future Fund for his early ML alignment skill development and his SERI MATS project.

Research Manager at MATS, London

Nicole Ruiz is a non-resident fellow at the Foundation for American Innovation and director of The Third Oikos, a publication exploring how technology reshapes family life and the household. She is also a visiting fellow at the Institute for Family Studies and previously invested in frontier technology startups at seed stage as a venture capitalist at Compound.

Subhojeet Pramanik is a researcher at Softmax with an MSc from Alberta’s RLAI lab whose work focuses on reinforcement learning and representation learning. He introduced the Recurrent Linear Transformer (AGaLiTe, TMLR 2024), previously worked at IBM Research, and is the author of OmniNet, a unified architecture for multi-modal multi-task learning.

Ondrej Bajgar is a DPhil student in Bayesian machine learning at the University of Oxford, supervised by Michael A. Osborne, Alessandro Abate, and Konstantinos Gatsis. He studied mathematics at the University of Warwick and subsequently spent three years as a Research Scientist at IBM Watson, working on machine learning for text understanding and dialogue systems. He then joined the Future of Humanity Institute at Oxford as a Senior Research Scholar, where he worked on AI safety for approximately two years before beginning his doctorate. His current research focuses on active inverse reinforcement learning, developing methods to align AI decision-making with human preferences by strategically selecting informative demonstrations. He has also published work on negative human rights as a principled framework for long-term AI safety and regulation, co-authored with Jan Hořeňovský in the Journal of Artificial Intelligence Research. He received LTFF funding to support his AI safety PhD at Oxford.

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Technical AI risk analyst at ORCG and systems engineer from Universidad de los Andes, co‑founder of AI Safety Colombia, focusing on advanced AI safety and mechanistic interpretability.

A major Washington, DC-based think tank founded in 1910 that produces independent policy research on international security, democracy, and governance, with a growing program on AI safety and technology governance.

Looking for Fund for my PhD at Oxford - Interested in AI Alignment, Safety and Governance.

Senior Marketer at Probably Good with a master’s degree in Communication Science and ongoing master’s studies in Philosophy; serves as a Marketing Advisor for Effectief Geven and has previously worked for Amnesty International, the United Nations, and advised think tanks, government bodies, and tech companies on communication strategy and impact.

Successif helps mid-career and senior professionals transition into high-impact careers in AI safety and governance through free personalized advising, workshops, and job market research.

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Softmax is an AI alignment research startup developing the science of organic alignment through multi-agent reinforcement learning. Founded by Emmett Shear, Adam Goldstein, and David Bloomin, the company studies how agents learn to cooperate, share goals, and form collectively intelligent systems.

Niko McCarty is a molecular bioengineer, writer, and Fellow at Astera Institute whose work focuses on biophysics, metascience, and visual tools for explaining complex ideas. He previously worked as a data journalist, founded and serves as founding editor of the biotechnology magazine Asimov Press, and is writing a book on cell biology titled “Biology is a Burrito & Other Essays.”

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Glauber De Bona is a Brazilian computer scientist and assistant professor in the Department of Computer Engineering and Digital Systems (PCS) at the Escola Politécnica, University of São Paulo (USP). He holds a Bachelor's in Computer Engineering from the Aeronautics Institute of Technology (ITA, 2006), a Master's in Computer Science from USP (2011), and a PhD in Computer Science from USP (2016), with his doctoral dissertation focused on measuring inconsistency in probabilistic knowledge bases. He conducted postdoctoral research at University College London (2017) and USP (2018). His academic research spans probabilistic logic, inconsistency measurement and localization in knowledge bases, epistemic argumentation, and formal epistemology, with publications in venues such as AAAI and the Journal of Artificial Intelligence Research. He has described his broader research interest as mitigating existential risks posed by AI, and has been active on the Alignment Forum under the handle glauberdebona, where he has posted work on computational complexity arguments about the alignment problem. He received a 6-month stipend from the Long-Term Future Fund to transition to independent research on AI safety.

Amritanshu Prasad is an AI safety researcher and policy writer based in the United Kingdom, focused on AI evaluations, AI governance, and the intersection of nuclear risk with emerging AI. He received an upskilling grant to study the AGI Safety Fundamentals Alignment Curriculum, and has since built a career in technical AI safety work, including a research engineering role at Equistamp where he helped UK AISI develop ControlArena, an infrastructure project for evaluating protocols for controlling unaligned frontier LLMs. He has contracted with METR for baselining and model interaction tasks, and facilitated courses on AI governance and transformative AI through BlueDot Impact. He is a member of the working group on international AI governance at the Alva Myrdal Centre for Nuclear Disarmament at Uppsala University, co-authoring work on the influence of nuclear governance frameworks on AI governance. He also completed a research fellowship at Pivotal Research and is founding Suav Tech, a for-profit AI safety evaluations organization. He writes the Substack newsletter The Next Frontier, covering AI evals, AI policy, and nuclear risk.

Veterinary Student building AI evaluation frameworks in food systems and animal health across Africa

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Assistant Professor of Computer Science at the University of Virginia who leads the Responsible AI for Science and Engineering (RAISE) group, focusing on foundational challenges in artificial intelligence, privacy, safety and the intersection between machine learning and optimization.

Singapore's national AI safety institute, operated by the Digital Trust Centre at NTU in partnership with IMDA, focusing on AI evaluation, testing, and governance to address gaps in global AI safety science.

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Andrei Alexandru is an AI safety researcher and machine learning engineer currently working at iGent AI on Maestro, an autonomous agentic coding agent. He holds an MPhil in Machine Learning from the University of Cambridge, where his dissertation examined the inductive biases of shallow neural networks, funded by a Long-Term Future Fund grant. He previously worked on the dangerous capability evaluations team at OpenAI and at Atla, where he was first author on the Atla Selene Mini paper introducing a state-of-the-art small language model-as-a-judge. Earlier in his career he participated in the SERI MATS program under Evan Hubinger's mentorship and the ML for Alignment Bootcamp at Redwood Research. His research interests include mechanistic interpretability, AI evaluations, and understanding deceptive alignment, and he maintains the blog inwaves.io where he writes about AI safety topics.

Curriculum Developer & Instructor at the Center for Applied Rationality. Jack studied psychology and gender and has previously worked in roles including event planning, data research, and legal assistance, and is especially interested in gaming, structured analysis, and deep conversations about culture and identity.

Peter Barnett is a researcher at the Machine Intelligence Research Institute (MIRI), where he works on the Technical Governance Team focusing on international coordination and governance strategies to prevent catastrophic outcomes from advanced AI. He holds a Master's degree in Physics from the University of Otago in New Zealand, where he conducted research in quantum optics and quantum fluids. He transitioned into AI safety work through the first cohort of the MATS (ML Alignment Theory Scholars) program and subsequently worked at the Center for Human-Compatible AI on reward learning before joining MIRI in December 2022, initially on technical alignment and later shifting to technical governance. His governance research includes verification mechanisms for international AI agreements, distributed training oversight, and AI capability red-lines. He has authored a book on AI x-risk aimed at policymakers and the general public, and is active on LessWrong and the Alignment Forum under the handle peterbarnett.

Nicholas Kees Dupuis is an AI alignment researcher and entrepreneur who co-founded Mosaic Labs, a nonprofit R&D organization developing AI-facilitated group deliberation tools, where he serves as CEO alongside co-founder and CTO Sofia Vanhanen. He holds a Master's degree in Artificial Intelligence from the University of Groningen (2022), where his thesis focused on theory of mind for multi-agent coordination. He conducted research at EleutherAI under Kyle McDonell and Laria Reynolds, studying how finetuning methods can cause alignment failures analogous to those in reinforcement learning, and has published academic work on computational social choice including the paper "Condorcet Markets" (2023). He is best known in the AI safety community for his influential "Cyborgism" essay on the Alignment Forum (February 2023), which proposed a strategy of using human-in-the-loop systems to safely accelerate alignment research by empowering human agency rather than outsourcing it; he subsequently led the Cyborgism track at AI Safety Camp 2023. He received a $120,000 one-year grant from the Long-Term Future Fund to continue developing his research agenda on making LLMs directly useful for alignment research without advancing capabilities. His personal website is lovedoesnotscale.com and he maintains a Substack under the same name.

A major public research university in Ann Arbor, Michigan, hosting faculty conducting AI safety and alignment research funded by organizations including Open Philanthropy.

Co-founder and co-director of Geodesic Research, leading technical AI safety work within the Meridian Cambridge community.

Connor Dunlop is a researcher and strategist working at the intersection of AI governance, compute security, and geopolitics, with experience spanning frontier AI policy research, hardware‑enabled verification, foresight, and institutional design.

Journalism executive and philanthropy leader who serves as chair of the Hudson Institute Board of Trustees and previously ran business operations at Commentary magazine; she also sits on the board of the Flourishing Future Foundation, which supports research on controlling advanced AI to ensure a safe and flourishing future.

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Building high signal AI community infrastructure in Los Angeles focused on talent, collaboration, and ecosystem development.

Nick Corvino is a Tarbell AI Journalism Fellow and writer for ChinaTalk. He holds an M.A. from the Yenching Academy of Peking University, where he studied Chinese philosophy and religion, and a B.A. in philosophy and international relations from Northwestern University.

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James Lester leads the Oxford AI Safety Initiative and has written about AI safety topics on the Effective Altruism Forum.

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Geoffrey Miller is an evolutionary psychologist and associate professor of psychology at the University of New Mexico. He is known for his research on sexual selection and human nature and for books such as The Mating Mind and Spent, and in recent years he has become an active public commentator on AI risk and other existential threats.

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