Sandesh Kalantre
Lanczos Graduate Student (2018-2020)
Graduate Student, Alumni, Former Lanczos Graduate Fellow, Lanczos Graduate Fellow
Contact Information
- skalantr@umd.edu
- Office:
2231 Atlantic Building
Bio
Sandesh was a doctoral student in physics. He is interested in applying modern computational techniques like classical machine learning to efficiently bootstrap quantum experiments. He also works broadly on topological quantum materials and in particular on Josephson junction experiments. Sandesh held a QuICS Lanczos Graduate Fellowship 2018 to 2020. His advisor was James Williams in JQI.
Recent Publications
Theoretical bounds on data requirements for the ray-based classification
, , SN Comput. Sci., 3, (2022)Ray-based classification framework for high-dimensional data
, , Proceedings of the Machine Learning and the Physical Sciences Workshop at NeurIPS 2020, Vancouver, Canada, (2020)
Related Events
- December 7, 2018 12:00 pmJQI-QuICS-CMTC Seminar
Machine Learning Techniques for State Recognition and Auto-tuning in Quantum Dots
Sandesh Kalantre(JQI/QuICS)
Affiliated Research Centers
JQI