Jacob Merizian

This stream will focus on AI control and evaluations of dangerous capabilities, propensities, and alignment.

Stream overview

I would be interested in advising work in control and dangerous capability/propensity/alignment evals, as I feel I have the best chance of being a good mentor for these sorts of projects. Currently, I work on propensity evaluations, evaluation awareness, and sandbagging. I would be happy to suggest concrete project ideas and help with brainstorming topic choices, or help guide an existing project.

Mentors

Jacob Merizian
UK AISI
,
Research Scientist, Workstream Lead
London
Misalignment Science
AI Control and Monitoring
Capability and Propensity Evaluations

I work at the UK AI Security Institute. In the past, I’ve done research in high-performance computing, language model pretraining, interpretability, and hardware enabled governance.

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Mentorship style

I prefer a weekly meeting cadence of at least one research meeting per week, where we discuss results from the previous week and potential next steps, and just generally align ourselves on priorities and stay motivated. I'm also a fan of relatively few meetings, and much more support given asynchronously, so I can think carefully about my responses and help throughout the process.

I have a decent amount of experience on the technical side, and so in the past have had good experiences unblocking scholars when they were stuck on technical obstacles right away (e.g. low-level bugs like memory issues, taking a step back and thinking about alternative approaches, etc). For example, I'm a huge fan of impromptu pair programming sessions to debug things together, and I always learn new things from dropping into someone's workflow. I'm also happy to help clarify things conceptually and just brainstorm together. The two biggest bottlenecks in my experience have been 1) getting stuck on technical obstacles and 2) conceptually understanding the problem we're trying to solve.

Fellows we are looking for

I'm open to a wider variety of skillsets, but these would be a big plus:

  • some relevant technical background in running basic finetuning/inference/interp experiments on a multi-gpu cluster
  • some prior level of interest in any of the research categories I've listed
  • ability to work independently once there is a clear enough goal (though I'm happy to be the one supplying the goal if that is the bottleneck)

It depends on the chosen category, but I would probably try to connect scholars together if they are working on similar-enough projects, or help find UK AISI or external collaborators as makes sense. Scholars are of course welcome to find collaborators on their own as well, and I can help facilitate that if need be.

Project selection

I would be happy to suggest concrete project ideas and help with brainstorming topic choices, or help guide an existing project that the scholar is interested in. My preference is that the scholar picks a category that overlaps with an area I actively work on so that I can give effective high-level advice.

Streams

The Winter 2027 cohort offers a wide range of research streams led by experts across AI alignment, interpretability, governance, and safety. Each stream provides its own research agenda, methodology, and mentorship focus.

London
Empirical
Interpretability
London
Interpretability, Red-Teaming, Monitoring
London
Monitoring, Adversarial Robustness, Control, Model Organisms, Red-Teaming, Dangerous Capability Evals, Safeguards
New York City
Policy and Governance
Dangerous Capability Evals, Control, Strategy & Forecasting, Policy & Governance, Scalable Oversight, Agent Foundations
SF Bay Area
Empirical
Theory
Dangerous Capability Evals, Adversarial Robustness, Security, Red-Teaming, Scalable Oversight
London
Control, Scheming & Deception, Dangerous Capability Evals, Monitoring
Washington, D.C.
Policy and Governance
Policy & Governance, Strategy & Forecasting
Oxford
Theory
AI Welfare
SF Bay Area
Control, Model Organisms, Scheming & Deception, Strategy & Forecasting
SF Bay Area
Theory
Interpretability
Tübingen
Dangerous Capability Evals, Agent Foundations, Adversarial Robustness, Monitoring, Scalable Oversight, Scheming & Deception
SF Bay Area
Policy and Governance
Dangerous Capability Evals, Policy & Governance
New York City
Monitoring, Dangerous Capability Evals, Scalable Oversight, Safeguards
SF Bay Area
Policy and Governance
Strategy & Forecasting, Policy & Governance
Montreal
Agent Foundations, Dangerous Capability Evals, Monitoring, Control, Red-Teaming, Scalable Oversight
SF Bay Area
Control, Model Organisms, Red-Teaming, Scheming & Deception