Sandesh S. Kalantre

Engineering · Physical Sciences

6h-index253citations18works6.02yr avg
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Research Topics

Advancements in Semiconductor Devices and Circuit Design(6), Quantum and electron transport phenomena(5), Force Microscopy Techniques and Applications(5), Physics of Superconductivity and Magnetism(4), Neural Networks and Applications(3)

Publications18 total

QDFlow: A Python package for physics simulations of quantum dot devices
arXiv (Cornell University)·2025Open Access
Torsional force microscopy of van der Waals moirés and atomic lattices
Proceedings of the National Academy of Sciences·2024· 12 citedOpen Access
Torsional Force Microscopy of Van der Waals Moirés and Atomic Lattices
arXiv (Cornell University)·2023Open Access
Toward Robust Autotuning of Noisy Quantum dot Devices
Physical Review Applied·2022· 4 citedOpen Access
Theoretical Bounds on Data Requirements for the Ray-Based Classification
SN Computer Science·2021· 2 citedOpen Access
Josephson detection of time-reversal symmetry broken superconductivity in SnTe nanowires
npj Quantum Materials·2021· 26 citedOpen Access
Ray-Based Framework for State Identification in Quantum Dot Devices
PRX Quantum·2021· 27 citedOpen Access
Ray-based classification framework for high-dimensional data
arXiv (Cornell University)·2020· 5 citedOpen Access
Supercurrent interference in semiconductor nanowire Josephson junctions
Physical review. B./Physical review. B·2019· 30 citedOpen Access
Josephson Detection of Time Reversal Symmetry Breaking $s\pm is^{\prime}$ Superconductivity in SnTe Nanowires
arXiv (Cornell University)·2019Open Access
Josephson Detection of Time Reversal Symmetry Broken Superconductivity in SnTe Nanowires
arXiv (Cornell University)·2019· 4 citedOpen Access
True machine learning for quantum dot tune-up
Bulletin of the American Physical Society·2019· 1 cited
Quantum-Transport in Semiconductor Nanowire Josephson Junctions
Bulletin of the American Physical Society·2019
Machine learning techniques for state recognition and auto-tuning in quantum dots
npj Quantum Information·2019· 99 citedOpen Access
AC Josephson effect in a capacitively shunted graphene Josephson junction
Bulletin of the American Physical Society·2018
QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments
PLoS ONE·2018· 42 citedOpen Access
Applying Machine Learning to Quantum-Dot Experiments: Generation of Training Datasets and Auto-tuning
Bulletin of the American Physical Society·2018
Applying Machine Learning to Quantum-Dot Experiments: Learning from the Data
Bulletin of the American Physical Society·2018· 1 cited

Frequent Co-authors

Justyna P. Zwolak(10), Jacob M. Taylor(9), Xingyao Wu(5), Thomas McJunkin(4), J. R. Williams(4), Christie J. Trimble(3), Ming Wei(3), Liang Fu(3), Stephen Ragole(2), Praveen Sriram(2), Kaveh Gharavi(2), Jonathan Baugh(2), Bhaskaran Muralidharan(2), M. A. Eriksson(2), P. Liu(2), Hyeuk Jin Han(2), Myung‐Geun Han(2), J. J.(2), Mihir Pendharkar(2), Steven J. Tran(2)