cv
General Information
| Full Name | Sanketh Vedula |
| Date of Birth | 1 November 1997 |
| Languages | English, Telugu, Hindi |
Education
-
2025 Ph.D. Computer Science
Technion - Israel Institute of Technology - Advisor - Alex Bronstein
- Research topics - matrix completion, graphs, optimal transport, vector quantile regression, structural biology, single-cell multi-omics
-
2020 M.Sc. (cum laude) Computer Science
Technion - Israel Institute of Technology - Advisors - Alex Bronstein, Michael Zibulevsky
- Research - Learning-based design of ultrasound imaging and MRI systems.
-
2017 B.Eng. (Honors) Computer Science
BITS Pilani, India - Undergraduate thesis - Deep learning for image restoration. Supervisor - Michael Zibulevsky.
- Spent the final year as an exchange student at Technion, Israel.
- Internships - Chennai Mathematical Institute, Tata Research & Development Design Center, Pune.
Experience
-
2024- ML Research Scientist Intern
Pfizer - Host - Djork-Arne Clevert
- ML-based methods for NMR imaging, ML-based prediction of enantiomeric separation.
-
2024- Visiting Researcher
Institute of Technology & Science, Austria. - Hosts - Paul Schanda, Francesco Locatello
- ML-based approaches for NMR imaging of proteins, unsupervised alignment of single-cell modalities.
-
2019-2023 ML Researcher
Sibylla Ltd, UK - First employee. Built quant trading and portfolio management strategies.
Honors and Awards
- Pfizer--Technion Ph.D. Fellowship, 2023-24.
- Excellence scholarship for Ph.D. studies, The Israeli Smart Transportation Research Center (won twice - 2022-23, 2023-24).
- Faculty scholarship for excellence in studies and research, Computer Science Department, Technion. (won thrice - Fall 2019, Spring 2020, Fall 2022).
- Graduated Cum Laude, M.Sc. studies, Technion, 2021.
- VATAT prize for outstanding interdisciplinary research in data science, Machine Learning and Intelligent Systems (MLIS) Center, Technion, 2020.
Research Interests
-
Tools
- generative models, optimal transport, geoemtric deep learning, distribution-free uncertainty estimation, graph signal processing.
-
Applications.
- computational and structural biology, bioinformatics, single-cell multiomics, computational imaging, physics.