Loading results...
Showing 3651-3700 of 4522 results
Abhijit Narayan S received a grant from the Long-Term Future Fund in June 2023 to support a 4-month self-study stipend focused on upskilling in technical AI alignment, with the intention of applying learnings to reinforcement learning models. The grant of $1,000 was aimed at enabling participation in ML safety courses as part of an early-stage entry into the AI safety field.
GAP is an Australian charity, working to improve the long-term future, that requires funding for salary and operational expenses.
1 year salary to research new alignment strategy to analyze and enhance Collective Human Intelligence in 7 pilot studies
No summary available yet.
PhD student in AI safety with David Krueger at the University of Cambridge and Program Associate at the AI Risk Mitigation Fund; his research focuses on AI safety topics such as alignment failures, forecasting AI capabilities, and scalable oversight.
No summary available yet.
No summary available yet.
No summary available yet.
A 501(c)(3) nonprofit that accelerates neglected approaches to AI alignment by providing researchers with engineering teams, compute resources, and operational infrastructure.
No summary available yet.
Professor of Computer Science at the University of Virginia and Co‑Director of AI Research in the Office of the Provost; formerly Division Director for Information & Intelligent Systems at the U.S. National Science Foundation, founding director of the Goergen Institute for Data Science at the University of Rochester, and recipient of the 2018 ACM‑AAAI Allen Newell Award and 2020 AAAI Distinguished Service and Engelmore Lecture awards.
No summary available yet.
Animal protection and longtermism researcher with training in physical sciences, particularly geophysics
Supporting Vanessa with her AI alignment research
IAIGA is a Geneva-based non-profit initiative working to establish a supranational AI governance body and legally-binding global treaty to ensure AI safety and equitable distribution of AI-derived benefits.
Danielle Ensign (also known online as Phylliida) is an AI safety researcher and software developer based in the United States. She received a bachelor's degree from the University of Utah (2012–2017), where she published early research on algorithmic fairness, including the influential paper "Runaway Feedback Loops in Predictive Policing" (FAT/ML 2017). She later participated in the OpenAI Scholars program (2021), studying how text generation models affect opinion ecosystems. As a MATS fellow (2024), mentored by Adrià Garriga-Alonso, she conducted circuit-based mechanistic interpretability research on the Mamba state-space model architecture, producing the paper "Investigating the Indirect Object Identification circuit in Mamba" (arXiv:2407.14008) and creating MambaLens, a widely-used TransformerLens port for Mamba. She subsequently became an Anthropic Fellow (2025), working with mentor Kyle Fish on studying LLM conversation termination behavior, resulting in the paper "The LLM Has Left The Chat: Evidence of Bail Preferences in Large Language Models" (arXiv:2509.04781).
Manya Saini is a business and finance journalist at Reuters, covering U.S. banks, fintechs, private venture funding, IPOs, private equity, crypto, and related capital markets.
No summary available yet.
4-month salary to continue work on AI Control as a MATS extension
No summary available yet.
David Rolnick is an assistant professor in McGill University’s School of Computer Science, a core academic member of Mila, and a Canada CIFAR AI Chair. His research focuses on applying machine learning to address climate change, and he is co‑founder and chair of Climate Change AI as well as scientific co‑director of Sustainability in the Digital Age.
No summary available yet.
11 months stipend for 1.5 FTEs and funding for other costs for an AI Safety field-building organization TUTKE in Finland
No summary available yet.
General Support of Elizabeth Van Nostrand c/o Lightcone
No summary available yet.
Surge AI is a data labeling and AI training data company that provides high-quality human annotation, RLHF datasets, and adversarial red-teaming services to frontier AI labs including Anthropic, OpenAI, Google, Microsoft, and Meta.
Hunter Jay runs the Sydney AI Safety Space (SASS), a volunteer‑run, donation‑supported coworking space providing free office space for people working on AI safety.
Buddhist chaplain, meditation teacher, social entrepreneur, and co-founder of the Buddhism & AI Initiative; he holds a Master of Divinity in Buddhism from Columbia University’s Union Theological Seminary and previously worked as a founder, CMO, startup operator, and strategy and innovation consultant at Deloitte.
No summary available yet.
Aidan Ewart is an AI safety researcher and mathematics undergraduate at the University of Bristol (2022-2026), based in the UK. He has participated in the MATS program as a Research Scholar, working primarily on adversarial robustness and latent adversarial training (LAT). He interned at Haize Labs (July-October 2024) in New York, where he built automated red-teaming infrastructure and contributed to red-teaming of OpenAI's o1 models and contract work with Anthropic. His published research includes co-authoring 'Sparse Autoencoders Find Highly Interpretable Features in Language Models' (ICLR 2024), 'Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs' (NeurIPS 2024), and 'AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors' (2026). He has received funding from the Long-Term Future Fund for independent research on LM interpretability and for a MATS 5.0 extension focused on improving methods in latent adversarial training.
No summary available yet.
Darryl Wright is an AI safety researcher and advisor who received a Long-Term Future Fund grant to conduct independent AI safety research, focusing on two projects: penalizing neural networks for learning polysemantic neurons, and crowdsourcing alignment research from volunteers. He holds a Master's in Physics and a PhD in Astrophysics from Queen's University Belfast, where his doctoral research applied machine learning to transient survey classification using data from the Pan-STARRS1 survey. He subsequently held research positions at the University of Minnesota's Minnesota Institute for Astrophysics, the University of Oxford, and Mayo Clinic Rochester, where he worked on machine learning applications in healthcare. He also contributed to the Zooniverse citizen science platform, investigating how AI and citizen scientists can cooperate on data-intensive research problems. He has served as a mentor for the Supervised Program for Alignment Research (SPAR) and is currently an AI policy and law advisor at Successif.
Develop proposals for off-switch designs for AI, including policy games, that have been rigorously evaluated for their effectiveness, technical feasibility and political viability
No summary available yet.
CEO and Founder of the Odyssean Institute
A micro-project to turn an early AI governance prototype into risk notes, oversight checklist, review templates and public learning.
No summary available yet.
No summary available yet.
Sijia Liu is a Red Cedar Distinguished Associate Professor in the Department of Computer Science and Engineering at Michigan State University and an affiliated professor at IBM Research and the MIT‑IBM Watson AI Lab. He received his Ph.D. in Electrical and Computer Engineering from Syracuse University, then worked as a postdoctoral research fellow at the University of Michigan and as a research staff member at the MIT‑IBM Watson AI Lab. His research focuses on scalable and trustworthy AI, including scalable optimization for deep models, machine unlearning for vision and language models, AI robustness and data‑model efficiency, and his work has been recognized with honors such as an NSF CAREER Award, the INNS Aharon Katzir Young Investigator Award, MSU’s Withrow Rising Scholar Award and best paper accolades at venues including UAI and ICASSP.
Siliconversations is a YouTube channel that creates animated videos explaining AI safety risks and existential risk from advanced AI to general audiences. It is run by a former quantum scientist who became a full-time content creator.
Alex Lintz is an independent researcher specialising in AI governance, affiliated with the Institute for AI Policy and Strategy and co-founder of the AI Safety Communications Centre. He previously worked at the Centre for the Governance of AI, has led workshops on AI safety, and holds a master’s degree in economics from the University of Zurich.
No summary available yet.
A solo-researcher company founded by Koen Holtman that conducts AI safety research and participates in the creation of European AI safety standards in support of the EU AI Act.
No summary available yet.
No summary available yet.
Austin Carson is the founder and CEO of SeedAI, a Washington, D.C.–based nonprofit focused on AI policy, governance, and national AI readiness. He previously established and led NVIDIA’s Washington, D.C. government affairs operation and spent several years as a congressional technology staffer, including roles with the House Homeland Security Committee and the Congressional Cybersecurity and High Tech Caucuses.
No summary available yet.
A major public research university in Madison, Wisconsin, home to AI safety relevant research including interpretability work in the Statistics department and student-led AI safety initiatives.
