Dinkar Juyal

I am an ML Engineer at Meta working on agentic systems. Previously, I was a Staff ML Researcher and Engineer at PathAI, focused on foundation models and computer vision for digital pathology.

My work spans foundation models for pathology (PLUTO), domain generalization (ContriMix, best-performing official submission on the Camelyon17 WILDS leaderboard), interpretability (Additive MIL, sparse-autoencoder analysis of pathology embeddings), and evaluation of AI agents as ML engineers (ML-Dev-Bench). This work has been applied clinically, including AI-based automation of enrollment criteria and endpoint assessment in liver disease trials (Nature Medicine, 2024). See publications for the full list.

I write about ML research on this site and on Substack — mostly notes on agents, foundation models, and evaluation.

Talks & articles

latest posts

Jun 01, 2025 How to think with images
Jan 25, 2025 Evaluation for Agentic AI
Jan 03, 2025 Observations on self-supervised learning for vision

selected publications

  1. PLUTO: Pathology-Universal Transformer
    Dinkar Juyal, Harshith Padigela, Chintan Shah, and 30 more authors
    arXiv preprint arXiv:2405.07905, 2024
    Accepted at ICML 2024 workshops: ML for Life and Material Science, Foundation Models in the Wild, and Accessible and Efficient Foundation Models for Biological Discovery
    arXiv
  2. ContriMix: Scalable Stain Color Augmentation for Domain Generalization without Domain Labels in Digital Pathology
    Tan H. Nguyen, Dinkar Juyal, Jin Li, and 10 more authors
    arXiv preprint arXiv:2306.04527, 2023
    Best-performing official submission on the Camelyon17 track of the Stanford WILDS leaderboard
    arXiv Code Website
  3. ML-Dev-Bench: Comparative Analysis of AI Agents on ML Development Workflows
    Harshith Padigela, Chintan Shah, and Dinkar Juyal
    In ICLR 2025 Workshop on Deep Learning for Code (DL4C), 2025
    arXiv Code
  4. AI-based Automation of Enrollment Criteria and Endpoint Assessment in Clinical Trials in Liver Diseases
    Janani S. Iyer, Dinkar Juyal, Quang Le, and 28 more authors
    Nature Medicine, 2024
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