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Clear filtersMaite Abadia-Manthei is Director of Operations at the Cambridge Boston Alignment Initiative, overseeing operations for CBAI’s fellowships, CAMBRIA bootcamps, and fiscally sponsored student groups at Harvard and MIT, and co-authoring CBAI hiring posts for research and operations roles.
Showing 2751-2800 of 3284 results
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Clear filters to view everything →Organizing for a moratorium on frontier AI
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Jonas Hallgren is a researcher and community builder based in Uppsala, Sweden, focused on AI safety and multi-agent coordination. He co-founded AI Safety Sweden in September 2022 and previously served as Lead Organizer of Effektiv Altruism Uppsala. He is Co-Director of Equilibria Network, where he builds simulation infrastructure to test coordination mechanisms at the intersection of game theory, active inference, computational social science, and democratic mechanism design. He has received Long-Term Future Fund grants for establishing AI safety groups at Swedish universities and for creating a distillation course to help new AI safety theory researchers engage with technical literature. He has also served as a full-time mentor for the AFFINE Superintelligence Alignment Seminar and as an AI Researcher at Digital Democracy World.
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Danielle MacLean works in communications and marketing at High Impact Professionals and runs Marketing Growth Lab. She brings roughly two decades of experience in global marketing, communications, and strategy to supporting effective altruism organisations.
Benjamin (Ben) Todd is the president and co‑founder of 80,000 Hours and the author of the 80,000 Hours career guide. He led the organisation as CEO through its first decade, growing it from a student society at Oxford into a Y Combinator–backed nonprofit with dozens of staff, millions of annual readers, and coverage in outlets such as the Financial Times, The Economist, The Guardian, and the BBC. He also helped to kick‑start the effective altruism community in Oxford in 2011.
Damien Scott is a technologist and founder serving as a Resident at Astera Institute, where he leads the 1cFE initiative to investigate whether fusion energy can achieve sub‑cent per kilowatt‑hour costs and to publish open models, data, and AI benchmarks for fusion R&D. He previously founded Marain, an electric and autonomous‑vehicle simulation and optimization company acquired by General Motors, worked on engineering projects at Williams Formula 1, and holds a BSc in physics from the University of Sydney and MS and MBA degrees from Stanford University.
Technology executive and philanthropist who currently works at Good Forever, previously led technical operations at Recursion Pharmaceuticals, and earlier served as CIO and CMO of BuildASign.com, with computer science degrees from the University of Texas at Austin (BS) and the University of Colorado Boulder (MS).
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Model behavior & welfare, safety, digital minds | Ex Rovio/SEGA, Varjo
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Jacques Thibodeau is a French Canadian AI alignment researcher and physicist working to reduce risks from superintelligent AGI. He is the founder of a stealth AI safety organization focused on building infrastructure to progressively automate technical AI safety research, helping researchers rapidly iterate on experiments through a centralized alignment research ecosystem. He created the Alignment Research Literature Dataset, which has been used by OpenAI, Anthropic, and StampyAI, and has conducted research on model editing techniques and mechanistic interpretability. He participated in SERI MATS in Berkeley (July 2022) and has been an AI Safety Camp participant, including on a project to build datasets and tools for alignment research. He collaborates with Quintin Pope on the Supervising AIs Improving AIs agenda, which focuses on making automated AI science safe and controllable. Prior to his AI safety work, he had a background in physics and government roles in social innovation, strategic foresight, and regulation.
Program and operations manager at Catalyze Impact who co-runs the organization’s AI safety incubation program, handling recruitment, selection, program design, logistics, and participant support while building operational infrastructure for AI safety initiatives.
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Claire Short is a researcher and field-builder working at the intersection of AI safety and diversity in research. She is the founder of Athena, a mentorship program for women and gender-minority researchers in technical AI alignment, which provides a hybrid retreat-and-mentorship experience to help underrepresented researchers build skills and networks in the field. She currently serves as Research Manager at MATS (ML Alignment & Theory Scholars) in Berkeley, CA. Claire holds a Master's degree in Cognitive Science from Columbia University and has a background in neuroscience, including behavioral studies of impulsive decision-making in animal models and EEG research on meditation states. Her previous affiliations include AI Safety Camp (as a research lead), MATS fellowship (as a scholar in cohorts 3.0 and 7.0), Foresight Institute (as a Neurotech Fellow), the Atlas Fellowship, Epistea, and the Stanford Existential Risks Initiative. She has received funding from the Long-Term Future Fund to run the Athena program.
Lester L. Arnold, Sr. is vice president and chief human resources officer at RAND, where he leads the organization’s human resources strategy and functions. He joined RAND from George Mason University, where he served as chief human resources officer and vice president for Human Resources and Payroll, and previously held senior HR roles at Winston-Salem State University and in the private sector at organizations including FOCUS Brands, ARAMARK Healthcare, Lowe’s, and Wells Fargo. Arnold holds an M.B.A. with a concentration in human resources from the University of Hartford and a B.S. in accounting from Norfolk State University, along with professional HR certifications.
Ben Weinstein-Raun is a Senior Researcher at Palisade Research and a researcher and software engineer focused on AI and related fields. In addition to his work at Palisade, he serves as acting director of AI Impacts and has previously worked as technical staff at SecureDNA, Redwood Research, the Machine Intelligence Research Institute, and Cruise Automation.
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Research Scientist at Zeroth Research specialising in safe AI, stochastic control, decision-making, reinforcement learning, and formal verification, including work on neural supermartingale certificates for safety guarantees.
Philosopher of technology specializing in existential phenomenology and its applications to AI, holding a PhD in philosophy from Northwestern University and serving as Philosopher in Residence at Topos Institute and a visiting scholar in philosophy at UC Berkeley.
Operations Associate at Kairos who handles operations for SPAR and Pathfinder and is leading the transition for Kairos’s takeover of the Global Challenges Project, after more than three years on the groups team at the Centre for Effective Altruism and work in grants administration at Effective Ventures.
Dr. Dewey Murdick served as Executive Director of Georgetown’s Center for Security and Emerging Technology (CSET) from 2021 to 2025, where he provided policymakers and industry leaders with data-driven analysis on the security implications of emerging technologies. Prior to that role he was CSET’s Director of Data Science and Research, founding the center’s data analytics capabilities. Before joining CSET, he was Director of Science Analytics at the Chan Zuckerberg Initiative, Deputy Chief Scientist at the U.S. Department of Homeland Security, and a program manager at the Intelligence Advanced Research Projects Activity (IARPA). He holds a Ph.D. in Engineering Physics from the University of Virginia and a B.S. in Physics from Andrews University.
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James Herbert is a co-director of Effective Altruism Netherlands, based in Amsterdam. He previously worked as a consultant on urban socio-economic development projects and programmes funded by the EU, after studying liberal arts in the UK and philosophy in the Netherlands. Originally from northeast England, he now focuses on building the Dutch EA community and helping people use their careers, time and money to have more impact.
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Founder and Executive Director at AI Safety South Africa
backend eng with an interest in latent space exploration
Engineer at Atlas Computing based in Cambridge, United States, helping AI and formal verification communities support each other and with a physics background from Harvard University.
Andrew Zeng is an AI policy researcher and undergraduate student at Stanford University (class of 2026), where he serves as co-president of Stanford AI Alignment (SAIA). His research focuses on international coordination and governing high-risk AI systems, with particular interest in the state of AI safety in China and its implications for global existential risk. He received a 3-month stipend from the Long-Term Future Fund to support research on AI safety in China. Zeng also co-authors the AI Safety Newsletter published by the Center for AI Safety (CAIS), where he has written on topics including AI policy implications of the Trump administration and compute scaling. He has also served as a spotlight editor for The Stanford Daily.
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Sumeet Ramesh Motwani is a Machine Learning PhD student at the University of Oxford, advised by Philip Torr and Christian Schroeder de Witt, with funding from Eric Schmidt and CAIF. He completed his undergraduate degree in computer science at UC Berkeley, where he was a member of Berkeley AI Research (BAIR) advised by Dan Hendrycks. His research focuses on RL post-training, multi-agent systems, and AI security, with particular interests in meta-RL, open-endedness, and long-horizon LLM agent capabilities. He is known for his work on "Secret Collusion Among Generative AI Agents" (NeurIPS 2024), which established the subfield of secret collusion in multi-agent AI systems, and for "STARC: A General Framework For Quantifying Differences Between Reward Functions" (ICLR 2024), published while he was an undergraduate. He has also contributed to research on autonomous web-browsing agents (Agent Q, REAL benchmark) and multi-agent LLM training (MALT, COLM 2025). He participated in the MATS (ML Alignment Theory Scholars) program and is affiliated with the Future of Life Institute as a community researcher. He has held research positions at Microsoft Research (AI Frontiers lab) and Google X.
Fulton Wang is a co-founder of Guide Labs and holds a PhD in computer science from the Massachusetts Institute of Technology (MIT).
Marketing, product, and community leader with around 14 years’ experience across tech startups, media corporations, social platforms, and agencies; former Head of Marketing & Growth at Spark Wave; co-founded and helped lead AI Safety Australia & New Zealand; and currently leads the Technical Alignment Research Accelerator (TARA) while serving on advisory boards for organisations such as Giving What We Can and Results Australia.
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Nicolas Rodriguez is an AI governance specialist, LinkedIn Learning instructor with over 300,000 students, and consultant who founded RiesgosIA.org and GobernarIA.com to build practical AI safety and governance infrastructure, educational resources, and tools for Spanish-speaking organizations.
Director of Partnerships at the AI Safety Awareness Project. Originally from Caracas, Venezuela, he has lived in Chicago for roughly 25 years (with brief periods in Canada, Colorado, and Scotland) and spent about seven years working in sales roles at five startups, helping to navigate and secure funding rounds. In 2024 he pivoted into AI safety and now leads AISAP’s partnership framework while personally delivering AI safety workshops, webinars, and train-the-trainer programs for libraries and community organizations across the United States.
AI safety researcher and principal researcher at Cavendish Labs, with previous undergraduate study at Brown University.
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Jonas Hallgren is a co-director at Equilibria Network who directs the organization’s research architecture and operational systems, drawing on several years of AI safety research with a special focus on multi-agent coordination using active inference frameworks.
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