Sandesh Kalantre
Lanczos Graduate Student (2018-2020)
Former Lanczos Graduate Fellow, Alumni, Graduate Student, 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
Codebase release 1.0 for QDFlow
, , SciPost Phys. Codebases, 65-r1.0, (2026)QDFlow: A Python package for physics simulations of quantum dot devices
, , SciPost Phys. Codebases 65, 65, (2026)Theoretical bounds on data requirements for the ray-based classification
, , SN Comput. Sci., 3, (2022)
Related Events
December 7, 2018 12:00 pmJQI-QuICS-CMTC SeminarMachine Learning Techniques for State Recognition and Auto-tuning in Quantum Dots
Sandesh Kalantre(JQI/QuICS)
Affiliated Research Centers
JQI
