Jacopo Teneggi

Johns Hopkins University, Baltimore, MD


I am a PhD student in the Computer Science Department at Johns Hopkins University, where I am honored to be advised by Jeremias Sulam and to be affiliated with the Mathematical Institute for Data Science. Prior to joining JHU, I obtained my Bachelor’s degree in Biomedical Engineering at Politecnico di Torino, Italy.

My research focuses on:

  • Formal machine learning explainability,
  • Uncertainty quantification,
  • Weakly supervised learning for medical imaging.

In the past, I have worked with Rhonda Dzakpasu in the Department of Physics at Georgetown University to study spontaneous activity of in vitro, embryonal neural-astrocyte networks.

contact: jtenegg1 at jhu dot edu


Feb, 2024 Excited our paper was featured on the cover of Radiology: Artificial Intelligence!
Nov, 2023 Our paper “Examination-level Supervision for Deep Learning-Based Intracranial Hemorrhage Detection on Head CT” has been accepted for publication in Radiology: Artificial Intelligence.
Nov, 2023 Our paper “SHAP-XRT: The Shapley Value Meets Conditional Independence Testing” has been accepted for publication in TMLR.
Jun, 2023 I am interning at Profluent as a ML Scientist this summer, working on uncertainty quantification for sequence generation under the supervision of Aadyot Bhatnagar.
Apr, 2023 Our paper “How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control” has been accepted for presentation at ICML 2023!
Nov, 2022 Our paper “Weakly Supervised Learning Significantly Reduces the Number of Labels Required for Intracranial Hemorrhage Detection on Head CT” received a Trainee Research Prize at the RSNA 2022 Annual Meeting. Check out the abstract on Microsoft Research’s project InnerEye website!
Jul, 2022 Our paper “Fast Hierarchical Games for Image Explanations” has been accepted for publication in IEEE TPAMI. You can check it out here!
Jun, 2022 It was an inspiring week at Princeton ML Theory Summer School! Thanks to Boris Hanin and ORFE for having us; to Nati Srebro, Sebastien Bubeck, Soledad Villar, and Tengyu Ma for their great lectures. Cannot wait to see what these great researchers will achieve!



    1. 2023
      Rad AI
      Teneggi, J., Yi, P., and Sulam, J.
    2. 2023
      Teneggi, J.*Bharti, B.*Romano, Y., and Sulam, J.
    3. 2023
      Teneggi, J., Tivnan, M., Stayman, W., and Sulam, J.
    4. 2022
      Teneggi, J., Luster, A., and Sulam, J.
    5. 2021
      Front Neurosci
      Athey, T.,  Teneggi, J.Vogelstein, J.Tward, D., Mueller, U., and Miller, M.
    6. 2021
      Phys Rev E
      Teneggi, J., Chen, X., Balu, A., Barrett, C., Grisolia, G., Lucia, U., and Dzakpasu, R.