UT MD Anderson Cancer Center

APEX Lab

We build next-generation AI tools for computational pathology, grounded in rigorous principles of statistical inference, with the overarching goal of deciphering multi-scale oncologic complexity.

We are recruiting. Talented and motivated computational researchers are invited to join the lab as a postdoctoral fellow or graduate student. See Join us for details on how to apply.

Latest news

All news

  1. We present CORAL and also new KRONOS2 model for end-to-end foundation model-centric spatial proteomics analysis.

  2. Really excited to welcome Kunpeng (Eric) Zhang, an incoming Rice CS PhD student, as the second member of our lab!!

  3. Really excited to welcome Huilin Tai, an incoming Rice CS PhD student, as the first member of our lab!!

  4. We present MAMMOTH on how mixture-of-experts can slot into existing multiple instance learning frameworks for universally improving downstream task performance, which will appear in ICLR 2026!

  5. We present SEAL on how pathology foundation models can be further enhanced with the guidance of corresponding spatial transcriptomics.