BB
Brad Brooks-Rubin
TeamIndividual
Individual
No summary available yet.
Endorsed by-
Database
Loading results...
Loading results...
Showing 3601-3650 of 3954 results
Clear filtersNo summary available yet.
Showing 3601-3650 of 3954 results
Active filters: Type: Individual, Project
Clear filters to view everything →Shlomo Zilberstein is a Professor in the Manning College of Information and Computer Sciences at UMass Amherst whose research in artificial intelligence focuses on the computational foundations of automated reasoning and action under uncertainty and limited computational resources, using probabilistic reasoning and decision-theoretic principles to develop planning algorithms and meta-level control techniques for autonomous agents, often in multi-agent settings.
No summary available yet.
No summary available yet.
No summary available yet.
No summary available yet.
No summary available yet.
Sanmi Koyejo is an Assistant Professor of Computer Science at Stanford University, where he leads the Stanford Trustworthy AI Research (STAIR) lab, and a co-founder of Virtue AI developing enterprise solutions for AI safety and security.
Patrick is a Finance Associate at Giving What We Can. He previously worked as a Finance Associate at Impact Ops and as a Finance Analyst at the University of Buckingham, and he holds a first‑class degree in Philosophy from Durham University, where he wrote his dissertation on moral uncertainty.
No summary available yet.
No summary available yet.
Exec Assistant @ EA UK
No summary available yet.
Request for retroactive funding
No summary available yet.
Daniel O'Connell is the CTO and co-founder of Equistamp, a Public Benefit Corporation that provides research operations for AI safety organizations. Equistamp grew out of Rob Miles' AI safety Discord community and was established in late 2023. O'Connell, a UK citizen, has contributed to AI safety evaluation infrastructure for organizations including METR, the UK AI Security Institute, and Redwood Research. He co-authored the HCAST (Human-Calibrated Autonomy Software Tasks) benchmark paper, which provides a set of 189 machine learning engineering, cybersecurity, software engineering, and general reasoning tasks for evaluating AI autonomy. His work focuses on evaluation implementation, task quality assurance, and baselining for frontier AI models.
Independent researcher working on foundational models of large language model behaviour and alignment. My work focuses on mechanistic explanations of hallucination, coherence, and failure modes using systems theory, information theory, and learning dynamics. I am currently developing a boundary-mediated framework for understanding inference and learning in LLMs, with an emphasis on testable predictions and alignment-relevant design patterns.
No summary available yet.
Founder @ Nisit Sam Yan | Empowering Youth Through Publishing | Trying to be a Good Ancestor
No summary available yet.
No summary available yet.
4-month stipend to study AI Alignment,apply for ML Safety Courses and implemen it on RL models
No summary available yet.
Research into the nature of optimization, knowledge, and agency, with relevance to AI alignment
AI safety researcher who runs AI Lab Watch, where he collects safety recommendations for frontier AI companies, tracks what they are doing, evaluates them on safety, maintains related information collections, and blogs about how companies can prevent extreme risks such as AI takeover and human extinction.
No summary available yet.
No summary available yet.
No summary available yet.
No summary available yet.
Co-founder and President of Safe Superintelligence Inc., also serving as Co-founder and Principal Scientist, and previously a member of technical staff at OpenAI.
No summary available yet.
Member of Technical Staff at AI Digest, working on the organization’s interactive AI explainers and demos including projects like the AI Village.
Financial support for career exploration and related project in AI alignment upon completion of Masters in Computer Science
No summary available yet.
Richard Higgins is a researcher at Softmax with a PhD from the University of Michigan whose work spans compositional image editing with latent diffusion (ICCV 2025), hand–object segmentation in video (CVPR 2023, NeurIPS 2021), and solar magnetic field estimation; he has previously been a visiting academic at NYU Courant and a computer vision research intern at Meta.
A constraint-first approach to ensuring non-authoritative, fail-closed behavior in large language models under ambiguity and real-world pressure
No summary available yet.
Senior researcher whose work at ACS focuses on understanding the civilisational ramifications of powerful AI systems and developing better accounts of how agency works in AI systems, alongside a research affiliation with the University of Toronto computer science department and contributions to the 2026 International AI Safety Report.
Help Keep AI Safety ANZ Alive
No summary available yet.
No summary available yet.
Curriculum Developer & Instructor at the Center for Applied Rationality. Davis has been involved with CFAR since early 2014 in operations, finance, curriculum development, and teaching, and also has experience as a competitive tabletop gamer, commentator, and writer, with a bachelor’s degree in psychology from Carleton College.
A fast, comprehensive directory of the people and orgs in AI safety: search, filter, and match.
Arkose is a field-building nonprofit that supports mid-career ML professionals to enter the field of AI safety.
Thomas Kwa is a researcher on the technical staff at METR (Model Evaluation & Threat Research), where he focuses on measuring AI capabilities and autonomous task completion. He holds a Computer Science degree from Caltech and previously worked at MIRI and conducted interpretability research through the MATS/SERI MATS program with Adrià Garriga-Alonso and Jason Gross. He is the lead author of the influential METR paper introducing the '50% time horizon' metric—the length of tasks AI models can complete autonomously with 50% probability—which found this metric has been doubling roughly every seven months. He also co-authored 'Catastrophic Goodhart,' a 2024 paper demonstrating that KL divergence regularization in RLHF fails to prevent reward hacking under heavy-tailed reward misspecification, presented at ICML and NeurIPS 2024. Thomas is an active contributor to LessWrong and the AI Alignment Forum, where he publishes research on interpretability, Goodhart's Law, and AI safety methodology.
No summary available yet.
Matt Clifford CBE is cofounder and Chair of Entrepreneurs First, a global talent investor, and serves as Chair of ARIA, the UK’s Advanced Research and Invention Agency. He also plays a leading role in UK AI policy, including work on the AI Safety Summit and the UK AI Safety Institute.
Clark Wisenbaker is Operations Manager at Macroscopic Ventures, managing the organization’s operational systems after previously holding various leadership roles at other nonprofits and for-profit startups and working as a practicing attorney.
No summary available yet.
