OpenProbe
An open toolkit for probing and visualizing internal activations of large language models.
8k+ stars · used across 30+ research labs
Frontier Systems Lab · San Francisco, CA
AI Research Scientist
Building machines that reason, align, and explain themselves — bridging deep learning theory and systems that actually ship.
01 / About
Adam Tesar is an AI research scientist working at the intersection of large language model reasoning, alignment, and efficient training. His work focuses on making capable models that are also legible — systems whose decisions can be inspected, steered, and trusted.
Before joining Frontier Systems Lab he completed a PhD in machine learning, where he studied emergent reasoning in transformer architectures and methods for scaling supervision without scaling cost. He has published at NeurIPS, ICML, and ICLR, and his open-source tools are used by research groups worldwide.
When he is not training models he writes about interpretability, mentors early-career researchers, and is generally curious about how intelligence — artificial or otherwise — actually works.
02 / Research
Eliciting and measuring multi-step reasoning in large models — chain-of-thought faithfulness, planning, and verification.
Scalable oversight, preference learning, and methods that keep increasingly capable systems pointed at human intent.
Reverse-engineering the internal circuits of neural networks to understand what they compute and why.
Joint representations across text, vision, and audio — and how grounding changes what a model can reason about.
Doing more with less: sparse architectures, distillation, and training recipes that cut compute without cutting capability.
Building benchmarks and evals that measure what we actually care about, and resist being gamed.
03 / Publications
04 / Projects
An open toolkit for probing and visualizing internal activations of large language models.
8k+ stars · used across 30+ research labs
A framework for building tamper-resistant evaluation suites for reasoning models.
Adopted by 3 frontier labs for internal evals
Reference implementations of scalable-oversight methods that run on a single GPU.
Teaching tool in 5 graduate courses
05 / Contact
Open to research collaborations, talks, and advising. The fastest way to reach me is email.
$ adam@adamtesar.com