Jacopo Teneggi
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
news
Sep, 2024 | Excited to share that our work “I Bet You Did Not Mean That: Testing Semantic Importance via Betting” has been accepted for publication in NeurIPS. |
---|---|
May, 2024 | Our latest preprint “I Bet You Did Not Mean That: Testing Semantic Importance via Betting” has been posted on arxiv! |
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! |