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Active:University: MIT, HarvardMin h-index: 5Has GitHub
CandidateUniversityFieldPapersCitationsh-indexScore

Dr. Sarah Chen

Assistant Professor

MITAI Safety474,2503897

Marcus Rivera

PhD Candidate

HarvardML Safety128901294

Dr. Yuki Tanaka

Postdoc

NortheasternInterpretability231,3401591

Priya Patel

PhD Candidate

Boston UniversityNLP8420789

Dr. James Okafor

Research Scientist

MITComputer Vision312,1802288

Lin Wei Zhang

PhD Candidate

NortheasternRobotics6310586

Dr. Anna Kowalski

Assistant Professor

TuftsBiotech383,1002885

David Nguyen

Masters Student

HarvardML Systems4180382
Showing 8 of 2,847 enriched profilesSorted by Scout Score · Infinite scroll
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Dr. Sarah Chen

Assistant Professor

MIT CSAIL · Computer Science & AI Lab
Interpretability Lab
97Scout Score

38

h-index

29

i10-index

4,250

Citations

47

Papers

94

Novelty

Bio

Sarah Chen is an Assistant Professor at MIT CSAIL specializing in mechanistic interpretability of large language models. Her work on circuit-level analysis of transformer attention heads has been cited over 4,000 times. She leads the Interpretability Lab, developing open-source tools for neural network analysis. Previously a research scientist at Anthropic, she now focuses on scalable interpretability methods for frontier models.

Affiliations

MIT CSAIL, Center for AI Safety, EleutherAI (advisor)

PhD 2016-2020Advisors: Prof. David Bau, Prof. Jacob Steinhardt
GitHub Activity

34

Repos

2,800

Stars

1,240

Followers

1,847

Contributions

circuit-finderPython980 stars
github.com/sarahchen-mlschen@mit.eduHomepageScholar: abc123XYLinkedIn
AI SafetyMechanistic InterpretabilityInterpretability Lab
Skills & Expertise
Mechanistic InterpretabilityTransformer AnalysisCircuit DiscoveryAttention Head AttributionSparse AutoencodersPyTorchNeural Network ProbingCausal ScrubbingFeature Visualization
Recent Publications

Sparse Feature Circuits in Large Language Models

NeurIPS 2025 · 2025

Automated Circuit Discovery via Causal Scrubbing

ICML 2025 · 2025

Attention Head Taxonomy: A Unified Framework

ICLR 2024 · 2024

Scaling Monosemanticity in Language Models

NeurIPS 2024 · 2024

Toward Comprehensive Mechanistic Interpretability

AAAI 2024 · 2024

Frequent Co-authors
David Bau (MIT)Jacob Steinhardt (UC Berkeley)Neel Nanda (DeepMind)Chris Olah (Anthropic)
Novelty Score94/100

Measures how unique and forward-looking their research is relative to the field.

Scout Score Breakdown
Publication Impact
96
Code Contributions
92
Research Novelty
94
Citation Trajectory
98
Collaboration Network
88

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