Sanmi Koyejo
Associate Professor of Computer Science
Studies trustworthy machine learning, including evaluation, robustness and fairness of AI models.
Sanmi Koyejo's lab at Stanford works on trustworthy & safe ML and interpretability, evaluation & safety of LMs. 102 papers since 2023, 58 at top venues, mostly NeurIPS and ICML. Applications close .
At a glance
- papers, 2023–2026
- 27/ year
- at T1 venues
- 57%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage and DBLP, 2023–2026
- 16 papers2026 · T1 7 · collecting
- 47 papers2025 · T1 29
- 26 papers2024 · T1 12
- 13 papers2023 · T1 10
T1 venuesOtherVenues: NeurIPS, ICML, ICLR, AISTATS, EMNLP
Research focuspaper titles that use each topic's words
- Trustworthy & safe ML8 papers
- Interpretability, evaluation & safety of LMs8 papers
- fairness6 papers
- trustworthy machine1 paper
- studies trustworthy0 papers
Paper list
From the lab homepage and DBLP.
202616 papers
- ICLR (T1)AbdCTBench: Learning Clinical Biomarker Representations from Abdominal Surface Geometry (opens in a new tab)
- —ALMo: Interactive Aim-Limit-Defined, Multi-Objective System for Personalized High-Dose-Rate Brachytherapy Treatment Planning and Visualization for Cervical Cancer
- SaTMLDifferentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings (opens in a new tab)
- JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATIONDiscussion of "The ICML 2023 Ranking Experiment" by Su et al. (opens in a new tab)
- ICLR (T1)Distributional Machine Unlearning via Selective Data Removal (opens in a new tab)
- Nature medicineHolistic evaluation of large language models for medical tasks with MedHELM. (opens in a new tab)
- TAG. Theoretical and applied genetics. Theoretische und angewandte GenetikImproving multi-trait genomic prediction using synthetic traits from hyperspectral data based on co-heritability. (opens in a new tab)
- ICLR (T1)Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models (opens in a new tab)
- Trans. Mach. Learn. Res.Let's Measure Information Step-by-Step: AI-Based Evaluation Beyond Vibes (opens in a new tab)
- ICLR (T1)No, of Course I Can! Deeper Fine-Tuning Attacks That Bypass Token-Level Safety Mechanisms (opens in a new tab)
- ICLR (T1)Pretraining Scaling Laws for Generative Evaluations of Language Models (opens in a new tab)
- EACLSCENEBench: An Audio Understanding Benchmark Grounded in Assistive and Industrial Use Cases (opens in a new tab)
202547 papers
- ENERGY AND AIAdvancing oil and gas emissions assessment through large language model data extraction (opens in a new tab)
- Science (T1)Advancing science- and evidence-based AI policy. (opens in a new tab)
- NeurIPS (T1)Aligning Compound AI Systems via System-level DPO (opens in a new tab)
- Trans. Mach. Learn. Res.Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified? (opens in a new tab)
- NeurIPS (T1)AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration (opens in a new tab)
- NeurIPS (T1)Best-of-N Jailbreaking (opens in a new tab)
- ICML (T1)Certified Unlearning for Neural Networks (opens in a new tab)
- ICML (T1)Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World (opens in a new tab)
- ICLR (T1)Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data (opens in a new tab)
- AISTATS (T1)Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration (opens in a new tab)
- PLOS digital healthEvaluating anti-LGBTQIA+ medical bias in large language models. (opens in a new tab)
- ICLR (T1)Failures to Find Transferable Image Jailbreaks Between Vision-Language Models (opens in a new tab)
202426 papers
- AISTATS (T1)Adaptive Compression in Federated Learning via Side Information (opens in a new tab)
- COMMUNICATIONS OF THE ACMArtificial Intelligence, Social Responsibility, and the Roles of the University (opens in a new tab)
- Nature Communications (T1)Author Correction: Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs. (opens in a new tab)
- AABIBayesian Optimization for Crop Genetics with Scalable Probabilistic Models (opens in a new tab)
- PLOS global public healthBridging gaps in automated acute myocardial infarction detection between high-income and low-income countries. (opens in a new tab)
- AISTATS (T1)Causally Inspired Regularization Enables Domain General Representations (opens in a new tab)
- Findings of NAACLCrossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models (opens in a new tab)
- NeurIPS (T1)Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections (opens in a new tab)
- Trans. Mach. Learn. Res.For Robust Worst-Group Accuracy, Ignore Group Annotations (opens in a new tab)
- ICLR (T1)HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance (opens in a new tab)
- —Impact of biased models in the context of fairness towards patients, and how to avoid or minimise biases in our datasets
- ICML (T1)Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks (opens in a new tab)
202313 papers
- AISTATS (T1)Adapting to Latent Subgroup Shifts via Concepts and Proxies (opens in a new tab)
- NeurIPS (T1)Are Emergent Abilities of Large Language Models a Mirage? (opens in a new tab)
- AISTATS (T1)Cooperative Inverse Decision Theory for Uncertain Preferences (opens in a new tab)
- NeurIPS (T1)DECODINGTRUST: A Comprehensive Assessment of Trustworthiness in GPT Models (opens in a new tab)
- BioengineeringFast Optical Signals for Real-Time Retinotopy and Brain Computer Interface. (opens in a new tab)
- UAI (T1)Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation (opens in a new tab)
- JOURNAL OF MEDICAL IMAGINGLongitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons (opens in a new tab)
- AISTATS (T1)One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning (opens in a new tab)
- Nature Communications (T1)Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs. (opens in a new tab)
- ICML (T1)Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions (opens in a new tab)
- NeurIPS (T1)Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells (opens in a new tab)
- JOURNAL OF MEDICAL IMAGINGToward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to StanfordFall 2027
Stanford Computer Science PhD
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- Single round
- Opens
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- English
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Confirmed on the program page.
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Data
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