Database

S. Yash Kalash is a CIGI senior fellow and expert in strategy, public policy, digital technology and financial services, with experience advising governments and private‑sector clients on emerging technologies such as fintech, digital assets and AI across India, MENA and the Asia‑Pacific region.

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Toronto-based AI safety organizer, educator, and nonprofit founder; co-founder and advisor to AIGS Canada and founder leading the Trajectory Labs AI safety office and community.

Chelsea Liang is a biosecurity policy researcher and Australian public servant, currently working as a Senior Policy Officer at the Australian Government Department of Health and Aged Care. She holds a degree in Bioinformatics Engineering from the University of New South Wales (UNSW), which she leverages to bridge technical and policy dimensions of biosecurity. She was previously affiliated with Good Ancestors Policy, an Australian EA-aligned charity focused on catastrophic and existential risk, where she received an Open Philanthropy grant (AUD 46,140, January 2023) to support biosecurity policy work in Australia. She co-authored the peer-reviewed paper "Managing the Transition to Widespread Metagenomic Monitoring: Policy Considerations for Future Biosurveillance" (Health Security, 2023), which addresses regulatory and policy challenges for adopting metagenomic sequencing in biosurveillance systems. She also received a Long-Term Future Fund grant to produce a policy paper on managing the transition to universal genomic surveillance. She was an active participant in the EA UNSW community.

Michael is the creator of Lethal Intelligence (lethalintelligence.ai), an "AI Risk Awareness Force" producing animated explainer videos and other multimedia content to raise general-public awareness of the existential dangers posed by upcoming autonomous and general AI systems and to make AI existential risk a "dinner-time conversation."

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Independent researcher whose work focuses on sparse autoencoders, mechanistic interpretability, and functional analysis; previously a researcher at Boston Fusion, a PhD student in mathematics at the University of Nebraska–Lincoln, and an undergraduate at Hamilton College.

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Harriet Farlow is the CEO and founder of Mileva Security Labs, an AI security company, and a PhD candidate in AI security at UNSW Canberra. With nearly a decade of experience at the intersection of AI and cyber security, she has worked as a senior consultant at Deloitte Australia, a data scientist at the University of Sydney, and later in the Australian Government on data science and national security, while also communicating about AI security through the AI Security Podcast and her HarrietHacks channel.

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Research Fellow at the Safe AI Forum (SAIF) and Policy Fellow at Yale’s Digital Ethics Center, where she researches transatlantic AI governance approaches. She is also a PhD candidate in Law, Science, and Technology at the University of Bologna and KU Leuven, focusing on the ethical impacts of XR technologies from a fundamental rights perspective.

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Chris Painter is President at METR, where he leads engagement with governments and AI labs on frontier AI safety, helps shape industry frontier safety policies, and works to scale METR’s third‑party AI risk assessments. Previously he was a Technology and National Security Fellow at the U.S. Department of Defense’s Joint Artificial Intelligence Center and worked on machine‑learning applications in medicine and biotechnology.

Bill Morris is a Director of The AI Safety Foundation and the former CEO of Accenture Canada, with more than three decades of leadership experience in professional services. He is known for championing inclusive leadership and sustainable business transformation in Canada’s corporate sector.

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Emil Wasteson Wallén is the Executive Director of Effective Altruism Sweden. With a background as an impact‑focused entrepreneur, including co‑founding the plant‑based seafood startup Hooked Foods, he now uses his experience to help others pursue high‑impact careers and projects within the EA Sweden community.

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Joshua Landes works on helping AI go well at BlueDot Impact, where he focuses on AI safety education and community building, drawing on prior experience in philosophy, political campaigns, and AI governance and regularly organizing AI safety events and meetups.

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Founder of Holtman Systems Research; systems architect and independent AI safety researcher with a PhD in Software Design from Eindhoven University of Technology for computer science research conducted at CERN, and with 20 years of industrial R&D experience and 10 years of experience in standards creation.

Angel investor and conservationist based in the Netherlands, CEO and founder of Symbiotic Projects, investing in natural capital via nature-based solutions that restore degraded land, conserve ecosystems and support biodiversity.

Lev Heller is the Operations Manager at the Effective Institutions Project, responsible for improving and maintaining organizational systems, managing compliance, and providing operational support to strategic initiatives. His background spans operational quality management at CAF America, strategy work for healthtech startups in emerging markets, biomedical research at the NIH, and field-based emergency medicine across multiple continents.

Scott Aaronson is the Schlumberger Centennial Chair of Computer Science at The University of Texas at Austin and director of its Quantum Information Center. He is a theoretical computer scientist whose research focuses on quantum computing and computational complexity theory, and from 2022 to 2024 he was on leave at OpenAI working on the theoretical foundations of AI safety. With support from Open Philanthropy, he is now building a research group at UT Austin on theoretical computer science for AI alignment.

Robert Kralisch is an independent conceptual and theoretical AI alignment researcher with a background in cognitive science. He became interested in AI safety in 2014 after reading Nick Bostrom's Superintelligence and later pursued both computer science and cognitive science before leaving formal academia to focus on independent alignment research. He completed the AI Safety Fundamentals course in 2021 and has since received funding from the Long-Term Future Fund for independent research. His work centers on three main areas: conceptual clarity around notions of agency, intelligence, and embodiment; the development of more inherently interpretable cognitive architectures (including his Prop-room and Stage Cognitive Architecture); and Simulator theory as an alternative framework for understanding large language models. He also serves as a research coordinator and organizer for AI Safety Camp, where he evaluates and supports conceptually sound alignment research projects.

Gabriel Recchia is a cognitive scientist and director of Modulo Research, where he works on the evaluation and alignment of large language models and the design of scalable oversight protocols. At Modulo he has led work releasing datasets of expert-annotated valid and invalid long-form solutions for use in scalable oversight experiments and related studies on how humans and models evaluate complex answers. Previously, he led user-testing research and evaluation for patient-friendly genetic reports and the Predict: Breast Cancer prognostic tool at the University of Cambridge’s Winton Centre for Risk and Evidence Communication, and has co-authored widely cited research on risk perception and communication.

David Reber is a PhD student in Computer Science at the University of Chicago, advised by Victor Veitch and Ari Holtzman. His research centers on precise causal inference over large language models, with a focus on post-hoc internal interpretability and validating human-understandable concepts within these systems. He is motivated by AI safety applications such as monitoring long-term planning and detecting deception, and is also interested in fairness and adversarial robustness. Earlier in his PhD he worked on empirical and theoretical extensions of Cohen and Hutter's pessimistic conservative reinforcement learning agent under the guidance of Michael Cohen. He received multiple grants from the Long-Term Future Fund, beginning in 2021, supporting his early RL safety research and his transition into the AI safety field. He is an active contributor to the AI Alignment Forum and LessWrong under the handle derber, and has published at venues including ICML.

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Roman Soletskyi is a Ukrainian researcher based in Paris, France, currently working as a researcher at Mistral AI. He completed an MS in Physics at Ecole Normale Superieure – PSL (2022–2024) after undergraduate studies in physics at Moscow Institute of Physics and Technology (2020–2022), and won a gold medal at the International Physics Olympiad in 2017. His research spans AI safety and formal verification, machine learning theory, and applied deep learning. Notable work includes "Training Safe Neural Networks with Global SDP Bounds" (2024, co-authored with David Dalrymple of ARIA), which develops methods for training neural networks with formal safety guarantees using semidefinite programming, with applications to safe reinforcement learning policies; this work was supported by the Long-Term Future Fund and the Machine Learning Alignment Theory Scholars program. At Mistral AI he has contributed to projects including the Pixtral 12B multimodal model and research on variational inference theory.

Alexander Mann is a grantee of the Long-Term Future Fund who received funding to develop a megaproject proposal focused on building a longtermist industrial conglomerate aligned via a reputation-based economy. Limited public information is available about this individual beyond their grant receipt.

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Muslim theologian and scholar of Islamic law who has served as Imam of the Islamic Center of Virginia for many years, previously Imam of the Colorado Muslim Society in Denver, after spending 12 years studying in Saudi Arabia at Umm Al‑Qura University in Mecca and the Graduate Institute for the Preparation of Imams in Mecca.

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Cody Rushing is a Member of Technical Staff at Redwood Research, where he works on AI control, model organisms, scheming and deception, and AI security. He completed his Bachelor's in Computer Science from UT Austin in Fall 2024 and attended the MATS Summer 2024 program under mentor Buck Shlegeris, later receiving a stipend extension to continue his AI Control research. He now also serves as a MATS mentor for the Redwood Research stream. His prior research includes mechanistic interpretability work under Neel Nanda and value alignment research with Brad Knox. He is a co-author of several papers including "Ctrl-Z: Controlling AI Agents via Resampling," "Factor(T,U): Factored Cognition Strengthens Monitoring of Untrusted AI," and "Basic Legibility Protocols Improve Trusted Monitoring." He is based in the San Francisco Bay Area.

Kiryl Shantyka is Executive Manager at Effective Altruism Sweden and works on operations and community support, including speaking on operations as a high‑impact career for the effective altruism movement.

Co-Director of the AI Safety Initiative at Georgia Tech, overseeing the group’s funding and strategy and conducting technical AI safety research on representation engineering, applied interpretability, and agentic misalignment.

Robbie McCorkell is the CTO at Leap Laboratories (Leap Labs), as indicated on his GitHub profile, and works on the company’s machine learning and interpretability tooling.

Garrison Lovely is a Brooklyn-based freelance journalist covering the intersection of money, power and artificial intelligence. He publishes Obsolete, an independent Substack newsletter on the economics and geopolitics of the AI industry, and is the author of the forthcoming book Obsolete: The AI Industry’s Trillion Dollar Race to Replace You—and How to Stop It (Nation Books/OR Books, 2026). His reporting on AI and corporate power has appeared in outlets including The New York Times, Nature, Bloomberg, The Verge, TIME, The Guardian US, SF Standard, The Nation, The American Prospect, Jacobin, BBC Future, Vox and Le Monde Diplomatique, and has been referenced by publications such as The New Yorker, The New York Times, The Atlantic and ProPublica. Lovely previously served as a Reporter in Residence at the Omidyar Network and earlier worked at GiveDirectly and as a product manager at Enigma Technologies.

Director and research lead at Truthful AI, an AI safety research non-profit based in Berkeley; affiliate of CHAI at UC Berkeley; previously based at the University of Oxford’s Future of Humanity Institute; holds a PhD from MIT and serves on the board of Ought.

Susie Alegre is an international human rights lawyer and CIGI senior fellow whose work focuses on technology, human rights and the emerging right to freedom of thought in the digital age; she is the author of "Freedom to Think" and "Human Rights, Robot Wrongs: Being Human in the Age of AI."

Monica Valcourt is a Bay Area engineer currently working on an FPGA hardware project. She previously founded and ran a small MEV trading firm, has hobby interests in GPUs, semiconductor manufacturing, and other low-level systems, and has completed internships at Uber ATG and Amazon. She graduated from MIT in 2022 with a degree in Computer Science.

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