Database

Find the best settings for SAE training we can, then scale across models

Final-year PhD student in Computer Science (EECS) at MIT in the Algorithmic Alignment Group advised by Dylan Hadfield-Menell, working on technical AI safeguards and governance, including red-teaming, robustness, interpretability, and audits of large models.

No summary available yet.

No summary available yet.

Noemi Dreksler is a Senior Research Fellow at the Centre for the Governance of AI (GovAI), based in Oxford, UK. She holds a DPhil in Experimental Psychology from the University of Oxford (2015-2020), an MSc in Industrial/Organisational and Business Psychology from University College London (Distinction), and a BA in Psychology and Philosophy from Oxford (First-Class Honours). At GovAI, she leads the survey research program, which has produced influential studies on AI researchers' views on AI progress and governance, economists' perspectives on AI and economic growth, public attitudes toward AI, local US policymakers' views on AI regulation, and frontier AI companies' safety frameworks. Her recent work includes a survey of AI researchers on beliefs about AI subjective experience and a large-scale study of over 13,000 people across multiple countries on AI risk management practices. She received a two-year grant to run public and expert surveys on AI governance and forecasting, directly supporting GovAI's core mission of developing evidence-based AI policy.

I help people use AI tools, like Claude Code, to automate knowledge work.

No summary available yet.

Oliver Zhang is the Managing Director and Co-Founder of the Center for AI Safety (CAIS), a nonprofit organization based in San Francisco focused on technical AI safety research, policy advocacy, and growing the AI safety field. He co-founded CAIS in 2022 alongside Dan Hendrycks. Prior to CAIS, Zhang co-founded the ML Alignment Theory Scholars (MATS) program through the Stanford Existential Risks Initiative (SERI), which provided mentorship, funding, and community support to emerging alignment researchers under the guidance of Evan Hubinger. He was also involved in launching the ML Safety Scholars Program and organized a $20K AI Safety Arguments Competition. Zhang is active on the AI Alignment Forum and LessWrong under the handle 'ozhang', where he has written about alignment theory programs and AI safety community building.

Economic and Social Impacts of AI

4 month salary to set up AI safety groups at 2 groups covering 3 universities in Sweden with eventual retreat

Research Scholar at ILINA focusing on the role of law and policy in strengthening model evaluations, a Researcher at the University of Cape Town African Hub on AI Safety, Peace and Security, and a Research Fellow at the Centre for AI Risk Management and Alignment (CARMA) working on whistleblower protections for AI safety professionals; he is also a Fall Research Fellow at the Vista Institute for AI Policy and holds a top‑ranked first‑class undergraduate law degree from Strathmore University.

No summary available yet.

Partner at Wuersch & Gering LLP in New York, specializing in cross-border corporate, securities, and commercial matters for U.S. and international clients.

Head of Finance and Services and member of the management team at the ETH Zurich Foundation, with prior roles in ETH Zurich’s finance and accounting functions.

No summary available yet.

No summary available yet.

No summary available yet.

Abigail Hing Wen is a New York Times and national bestselling author, film producer, and speaker best known for the Loveboat series of young adult novels, including Loveboat, Taipei, which was adapted into the film Love in Taipei. She holds a BA from Harvard University, a JD from Columbia Law School, and an MFA from Vermont College of Fine Arts, and has worked across law, finance, technology, and entertainment alongside her writing career.

No summary available yet.

Rob Knake is a senior adjunct policy advisor at the Institute for Security and Technology and a principal at the cybersecurity consultancy Orkestrel; he previously served as the first Deputy National Cyber Director in the White House’s Office of the National Cyber Director and is recognized as a leading authority on U.S. cybersecurity strategy and governance.

Member of the AI Safety Awareness Project team. He graduated from the University of Minnesota Twin Cities with a Bachelor of Science in Mathematics and Computer Science and served as a research fellow at the university’s Robotics and Artificial Intelligence Lab, focusing on deep learning applications in computer vision.

Israeli-American entrepreneur and investor who co-founded Safe Superintelligence Inc., previously co-founded the search engine Cue (acquired by Apple), led artificial intelligence efforts at Apple, served as a partner at Y Combinator, and is known for early-stage investments in companies such as Uber, Instacart, Figma, GitHub, Airtable, Rippling, CoreWeave, Character.ai and Perplexity AI.

Vegan

Andrey Tumas is an independent researcher who received funding from the Long-Term Future Fund for conceptual and theoretical research towards perfect world-model interpretability. Beyond this grant, no public profile, academic publications, or social media presence related to AI safety or alignment research could be located.

Felix Binder is a cognitive scientist and AI safety researcher currently working as a research scientist at Meta AI, where he focuses on AI Safety and Alignment for future superintelligent models. He completed his PhD in Cognitive Science at UC San Diego, with visiting scholar work at Stanford University, advised by Judith Fan, David Kirsh, and Marcelo Mattar. His research broadly falls under high-level interpretability and evaluations: designing experiments to elicit behaviors that reveal the inner workings of frontier models. Key areas of investigation include steganography in large language models — whether models hide information in their outputs such that a human observer cannot detect it — and introspection in LLMs, examining whether models can acquire genuine knowledge about their own internal states. His PhD work investigated agent-environment interactions during planning, exploring how environmental structure supports efficient problem-solving. He received a compute grant to study how steganography in LLMs might arise as a result of benign optimization pressure.

Stipend to upskill under and collaborate with Sahil K and Topos for 4-6 months, seeking to obtain teleological DAGs as the dual of causal DAGs

No summary available yet.

Stephanie Hill is Head of People at Coefficient Giving. She previously served as Vice President of People at GiveDirectly, where she helped scale the organization from roughly 275 to 975 staff across 11 countries and led its transition to a remote-first culture spanning 22 countries, and earlier held senior roles at the NYC Department of Education. She holds a BA in English from Wake Forest University and a Master of Science for Teachers from Pace University.

No summary available yet.

No summary available yet.

No summary available yet.

No summary available yet.

Jian Xin is the Director of Effective Altruism Cambridge, running programmes that connect Cambridge students with high-impact careers in policy, research, and other global priorities.

No summary available yet.

Undergraduate at George Washington University in Washington, DC, studying mathematics and political science. He has become heavily involved in AI policy, raising awareness of AI developments through multiple student organizations and projects such as the Politicians on AI Safety initiative. Liam now helps the AI Safety Awareness Project by designing and running AI policy workshops and has appeared in public discussions and podcasts about AI risk and governance.

No summary available yet.

Head of AI Risk Assessment at the UK Department for Science, Innovation and Technology, leading government efforts to identify and assess potential harms from AI after more than a decade in technology leadership roles at organisations including the UK Home Office, BBC and SEGA.

No summary available yet.

Hunar Batra is a DPhil (PhD) student in Computer Science at the University of Oxford (2023-2026), affiliated with Wolfson College and supervised by Ronald Clark. Her research focuses on multimodal learning, interpretability, and AI alignment. She has co-authored published work on bias mitigation in chain-of-thought reasoning (Bias-Augmented Consistency Training, with researchers from Anthropic and NYU) and on continual learning (EVCL, presented at the ICML 2024 Workshop on Structured Probabilistic Inference). She serves as a consultant at Anthropic and as a visiting researcher at the NYU Center for Data Science, and has previously worked at the UK AI Security Institute and METR. She received the Google Women in Computer Science Generation Scholarship in 2022 while completing her MSc at Oxford. Her PhD is supported in part by a Long-Term Future Fund grant covering tuition and living expenses to accelerate alignment research using expert iteration and Human-AI collaboration tools.

Dewi Erwan is the co-founder and CEO of BlueDot Impact, building the bridge between talented people and high-impact careers in AI safety and biosecurity. He previously served as Executive Director of Effective Altruism Cambridge and Biosecurity Advisor to the Cambridge Existential Risk Initiative, and studied engineering and later international relations and risk at Durham University. Originally from Wales, he is based in London.

AI safety

No summary available yet.

Ryan Hammer / NoBanks Nearby is a 40-year-old solo founder in California. He worked as a professional cinematographer since 2008 for Fortune 500 clients before teaching himself to code in July 2024 by collaborating with AI agents. In 22 months of self-taught coding he has shipped 24 production AI applications including three SaaS products (REDLINE, DATAROOM, COVENANT), an Ethereum L2 (ACiD), a 22-chain DEX (TRAIDE), an AI personal coach in eight languages (MAITE), an AI agent org for solo-founder back office (NoEnterprise, 5 C-level Hermes-based agents in daily production use), and a defensive-primitives toolkit for local-LLM operators (WorkstationLLM: memory guard, request queue, watchdog). Everything runs on a single $2,300 Mac Mini M4 Pro with zero cloud AI bills. His AI-safety focus is sovereign AI: defensive primitives that let individual operators run local-LLM stacks on consumer hardware without depending on hyperscaler safety infrastructure. Late-diagnosed Asperger's and Bipolar II, which he mentions because the founder narrative the funder will hear from him does not look like the standard EA / AI-safety researcher narrative.

One year part time spent on AI safety upskilling and concrete research projects

Chief simulacrum officer, chronicler of hipster museums, and Potemkin geek

No summary available yet.

No summary available yet.

No summary available yet.