Adin has been a researcher focused on pathogen transmission suppression (PPE, engineering controls, bioshelters) and agricultural biosecurity at Coefficient Giving for over three years, and has recently transitioned to a grant making role. He is also a PhD student at Johns Hopkins where he focuses on similar topics, and before this he was a Biotechnology Fellow at the Institute for Progress where he mostly worked on US federal agriculture policy.
Dylan is a safety researcher at OpenAI, where he works on curating better/safer training data and monitoring models for harmful behavior.
Before that he completed a PhD in the Machine Learning Department at CMU.
Hani is a software engineer at OpenAI.
Byron Cohen is a biosecurity advisor at DARPA's Biological Technologies Office, where he advises on biosurveillance, attribution, epidemiological modeling, and AI:bio uplift risk. Previously, he served as Advisor for Interagency R&D Oversight at the White House Office of Pandemic Preparedness and Response Policy (OPPR). An epidemiologist by training, he holds a PhD in population health sciences from Harvard University, and has conducted peer-reviewed epidemiological modeling research on biosafety and global health security.
Aman joined Coefficient Giving in March 2026. Previously, he worked as the Special Projects Lead at Blueprint Biosecurity, a pandemic prevention nonprofit. He has a B.S. in computational neuroscience from the University of Southern California.
Isak is a Member of Technical Staff at OpenAI. Previously a Software Engineer at Google, he worked on applications of computer vision, natural language processing, and LLMs.
Isak earned a Master of Computer Science at Carnegie Mellon University, with published work in natural language processing, style transfer, multilingual grapheme-to-phoneme modeling, and computer vision.
Bijan is a Technical Program Manager at OpenAI. He previously worked as a research engineer at Scale AI, where he coauthored work on LLM jailbreaking and red-teaming workflows.
Christopher is Research Scientist on the Alignment team at OpenAI working on fundamental and applied research. His focuses are privacy-preserving and adversarial machine learning including memorization, privacy, and security harms in language modeling, auditing for risks and mitigating them.
Previously he was a Research Scientist at Google Deepmind and Google Brain on the Privacy and Security Research team. There, he led privacy and security evals for their frontier model efforts.
Dewi, originally from Wales, is the CEO of BlueDot Impact and has a focus on attracting top talent into AI safety, helping them figure out how they can have the most impact, and enabling them to do so as fast as possible.
David is a Scientist in the AI Safety team at Lila Sciences, where he leads the technical design and implementation of dangerous capability evaluations in scientific domains like biology, chemistry, and materials science. His work involves measuring model performance on scientific tasks that could pose safety risks through misuse or unintended failure modes as well as the efficacy of guardrails and other mitigations. A core challenge is designing evaluations that meaningfully capture frontier capabilities; assessing not just what models can do today, but what emerging scientific reasoning abilities might enable in adversarial or failure scenarios.
In his previous role, David developed biosafety evaluations featured in the systems cards of Meta’s Muse Spark and multiple versions of Anthropic’s Claude Sonnet and Opus. Previously, he completed his PhD in Theoretical Physics at Queen Mary University of London.
Joseph works in Detections and Response at OpenAI. His public security work includes using large language models to detect malicious macOS activity.
Maja is interested in building AI for humans and trained by humans. Previously a Senior/Staff Research Engineer at DeepMind, an AI resident at X, and an intern at DeepMind, Google, and Amazon. Her OpenAI work includes scalable oversight and auto-review systems for coding agents.
Jason is a Member of Technical Staff at OpenAI working on alignment and model behavior.
Operating Partner at Halcyon. Cofounded and scaled a software company, Shogun, to Series C: $115M raised, $575M valuation (Y Combinator, Initialized, Accel, Insight) with over 20,000 customers and 200 team members. Investor in over 50 startups and early stage funds.
Sebastian Oehm is the co-founder and CEO of SynX Therapeutics, a biotech start-up developing non-natural peptides as next-generation medicines. He is also an Adjunct Assistant Professor at the J. Craig Venter Institute, and a Research Fellow at RAND Europe. He was one of 38 scientists who first publicly warned of the risks from mirror life. Previously, he completed a PhD and postdoc at the MRC LMB / University of Cambridge, where his research focused on non-natural biology. He worked as a staffer in the German parliament, and earned a BA in Natural Sciences at the University of Cambridge.
James is a Researcher at OpenAI working on model personality, post-training, and personalization.
Gabriel Wu is an AI alignment researcher at OpenAI. Previously, he directed the AI Safety Student Team at Harvard, where he earned a Master's degree in Computer Science and a bachelor's degree in Mathematics.
Dr. Jacob Swett serves as Executive Director and founder of Blueprint Biosecurity, a nonprofit dedicated to achieving breakthroughs in humanity’s ability to suppress pathogens. Drawing from a diverse background spanning scientific research, technology R&D, and political strategy, he is considered a leading voice in the biosecurity community.
Jake founded Blueprint directly after his experience shaping the Apollo Program for Biodefense, a report published in the wake of COVID-19 by the Bipartisan Commission on Biodefense. Anchored by Jake’s guidance, the report laid out an ambitious plan for overhauling America’s layers of defense against pandemics. Blueprint was founded to continue this work in the US and abroad.
Jake received a PhD in nanotechnology from the University of Oxford and bachelor’s degrees in physics and applied mathematics from Missouri State University. Before Blueprint, he cofounded a research nonprofit called altLabs and was a research scientist at Lockheed Martin’s Advanced Technology Center. He has contributed to over 70 articles and patents and authored op-eds for the New York Times and STAT.
Gary leads R&D at Fourth Eon Bio, and is a Contributing Scholar at Johns Hopkins Center for Health Security. His expertise spans biochemistry, molecular biophysics, biosecurity, and sequencing technology. He's spent nearly two decades studying how DNA, RNA, and proteins behave and interact. Gary holds a BS in Physics from San Jose State University and a PhD in Chemistry & Chemical Biology from University of California Merced.
Deger Turan is the CEO of Metaculus. Before Metaculus, Deger Turan served as President of the AI Objectives Institute, developing Talk to the City, a platform that strengthens communication between under-resourced communities and the government officials serving them. Prior to AOI, he founded Cerebra Technologies, which forecasted shifts of public opinion and demand trends for 300 million citizens, used by governments, hedge funds, and international retailers.
The MATS Program is a 10-week research fellowship designed to train and support emerging researchers working on AI alignment, transparency and security. Fellows collaborate with world-class mentors, receive dedicated research management support, and join a vibrant community in Berkeley focused on advancing safe and reliable AI. The program provides the structure, resources, and mentorship needed to produce impactful research and launch long-term careers in AI safety.
MATS mentors are leading researchers from a broad range of AI safety, alignment, governance, field-building and security domains. They include academics, industry researchers, and independent experts who guide scholars through research projects, provide feedback, and help shape each scholar’s growth as a researcher. The mentors represent expertise in areas such as:
Key dates
Application:
The main program will then run from September 28th to December 4th, with the extension phase for accepted fellows beginning in December.
MATS accepts applicants from diverse academic and professional backgrounds - from machine learning, mathematics, and computer science to policy, economics, physics, cognitive science, biology, and public health, as well as founders, operators, and field-builders without traditional research backgrounds. The primary requirements are strong motivation to contribute to AI safety and evidence of technical aptitude, research potential, or relevant operational experience. Prior AI safety experience is helpful but not required.
Applicants submit a general application, applying to various tracks (Empirical, Theory, Strategy & Forecasting, Policy & Governance, Systems Security, Biosecurity, Founding & Field-Building.
In stage 2, applicants apply to streams within those tracks as well as completing track specific evaluations.
After a centralized review period, applicants who are advanced will then undergo additional evaluations depending on the preferences of the streams they've applied to before doing final interviews and receiving offers.
For more information on how to get into MATS, please look at this page.