Jiayi Guo
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Clear filters to view everything →Linda Linsefors is a physicist turned independent AI safety researcher and organizer based in London. After a PhD in loop quantum cosmology, she shifted focus to AI alignment, co-initiated the first AI Safety Camp, and has since worked on theory-focused alignment research (including work on superposition and Newcomblike environments) and on organizing and advising AI safety programs.
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Head of Societal Resilience at the UK AI Security Institute and former Associate Director at the Ada Lovelace Institute, with around a decade of experience working at the intersection of technology, law and society.
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Software engineer on the MIT AI Risk Initiative at MIT FutureTech with a background in AI research, embedded software, and systems engineering, and a Bachelor of Science in Engineering from Harvey Mudd College.
A nonprofit research institute that develops methods to align AI systems, markets, and democratic institutions with what people genuinely value, using an approach they call full-stack alignment.
Research Associate in the Department of Computer Science at the University of Oxford’s OXCAV group with a PhD in Computer Science from the University of Buenos Aires, where he specialized in formal methods for distributed systems; his current work focuses on connecting formal verification and AI safety.
Jérémy Andréoletti is an AI Security Researcher at the General-Purpose AI Policy Lab, where he builds models to forecast AI capabilities and emerging risks, and he recently completed a PhD in computational evolutionary biology at École Normale Supérieure in Paris.
https://docs.google.com/document/d/11iw4nd43VUOUSReWL3GrVmEn9tqeVD6N/edit?usp=drivesdk&ouid=108060521704048492060&rtpof=true&sd=true
Operations Manager at Probably Good who specializes in building systems that drive impact; previously supported youth health and education initiatives in Botswana and led operations for an international professional training organization based in Mexico City.
PhD student in the ML4STS Lab working on benchmarking fair coding assistants to assess LLM performance across dimensions such as bias mitigation and code quality.
Investing to give. A little programming background and a little more crypto.
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Blake Pierson is a serial entrepreneur and nonprofit leader who helped co‑found and scale the apartment‑rental startup Lovely and later worked in senior roles at companies such as Opendoor before focusing full‑time on philanthropic and nonprofit work with organizations including the Future of Life Institute, Ergo Impact, Rainbow Gardens, and Fathom.
Ex particle physicist & AI safety guy. Community lead for integral altruism
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Eli Sugarman is Director of Special Projects at the William and Flora Hewlett Foundation, where he focuses on catalytic opportunities at the intersection of security and emerging technologies, and serves on the Board of Directors of the Institute for Security and Technology as well as boards of organizations such as ROOST and Girl Security.
Educator turned Director of Waitlist Zero advocating for the passage of the End Kidney Deaths Act & the prevention of kidney failure
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Programme and Research Director at the School of International Futures, with over twelve years’ experience delivering strategic foresight and research projects for governments, non‑profits and academic institutions.
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Strategic advisor at the AI Objectives Institute and Program Co-Lead for the AI Supply Chain Observatory, where she applies interdisciplinary expertise in ecology, science communication, and AI ethics to address disruptions in life-sustaining supply chains. She is also known as the co-founder of MICRO, a distributed network of small science museums.
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Leap Labs builds AI-powered interpretability tools to accelerate scientific discovery by finding patterns in complex datasets that humans and standard methods miss.
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Jerremy Holland is Director of AI Research at Apple, where he leads the AI Research group working on artificial intelligence and machine learning for areas such as autonomous systems, natural interaction, and health and wellness, and he serves as chair of the board of directors at Partnership on AI. He has an extensive track record in AI and machine learning research and holds multiple patents in the field.
Alfie Lamerton is a UK-based AI safety researcher and founder of Formation Research, an organization focused on quantifying and minimizing lock-in risk — the risk that harmful or oppressive features of the world become permanently stabilized, particularly through AI-enabled authoritarianism and power concentration. He is also a part-time research assistant at King's College London working on clinical machine learning benchmarking, and holds an MSc from King's College London. He participated in the MARS (Mentorship in Alignment Research Students) London programme, through which he conducted a literature review on in-context learning hypotheses and their implications for automated AI alignment research, supported by a Long-Term Future Fund grant. His research interests span lock-in risks, recommender system alignment, AI-enabled totalitarianism, and governance-informed technical interventions. He writes about these topics on his Substack and has published related work on LessWrong.
Patrick Mellor previously taught philosophy at San Francisco State University, has conducted research on episodic memory and temporal perception, biogeography and vertebrate phylogeny, and herring communication, and holds a BSc in Biological Sciences and an MA in Philosophy from San Francisco State University.
Director of Sage, the nonprofit behind AI Digest, Fatebook, and Quantified Intuitions, with a background in computer science, philosophy, and HCI research and previous work at Clearer Thinking.
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Executive Director of Effective Thesis, leading its work to empower students to focus their theses and careers on the world’s most pressing problems by providing programs, resources, and initiatives such as the Effective Thesis Pledge and Effective Thesis Fellowship that help them use academic research as a pathway to real-world impact.
SangZi Wang is an independent researcher focused on LLM behavioral reliability, interaction dynamics, and runtime observability. With a background in reconstructive and plastic surgery, his work bridges long-term human-AI interaction observation with practical auditing methodologies for large language models. His current research explores how conversational environments, protocol structures, and long-context interactions influence model behavior over time. Core topics include: - behavioral drift in extended dialogue, - protocol-induced response distortion, - execution confidence vs epistemic confidence (EC–EpC gap), - cross-model behavioral comparison, - runtime observability and interaction ecology. Rather than focusing on AGI speculation, his work emphasizes measurable behavioral phenomena emerging in real-world interaction settings. He has released multiple public Zenodo preprints and datasets, maintains structured GitHub repositories, and develops open behavioral audit frameworks designed for reproducible evaluation across different LLM systems. His long-term goal is to build lightweight, modular infrastructures for AI behavioral auditing, interaction reliability analysis, and runtime governance that remain accessible to independent researchers outside large institutional labs.
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Researcher at the Existential Risk Observatory with a background in mathematics, physics, and software development, providing technical expertise on AI evaluations and connecting technical and policy perspectives.
Mila is the Quebec Artificial Intelligence Institute, the world's largest academic research center for deep learning, founded by Turing Award winner Yoshua Bengio. It brings together over 1,400 researchers and professors to advance AI for the benefit of all, with responsible and safe AI as a core strategic priority.
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Accelerating AI Safety Research, ronak@coordinal.org
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