Apurva Mehta

According to our database, Apurva Mehta authored at least 13 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction.

Bowen Zheng, Katayun Kamdin, David Shapiro, Alexander Ditter, Dayne Sasaki, Emma Bernard, Roopali Kukreja, Petrus H. Zwart, Slavomír Nemsák, Apurva Mehta, Nicholas Schwarz, Alexander Hexemer, Tanny Chavez

CoRR, May, 2026

Domain Knowledge Guided Bayesian Optimization For Autonomous Alignment Of Complex Scientific Instruments.

Aashwin Mishra, Matt Seaberg, Ryan Roussel, Daniel Ratner, Apurva Mehta

CoRR, February, 2026

2025

Towards generalizable deep ptychography neural networks.

Albert Vong, Steven Henke, Oliver Hoidn, Hanna Ruth, Junjing Deng, Alexander Hexemer, Apurva Mehta, Arianna Gleason, Levi Hancock, Nicholas Schwarz

CoRR, September, 2025

A Start To End Machine Learning Approach To Maximize Scientific Throughput From The LCLS-II-HE.

Aashwin Mishra, Matt Seaberg, Ryan Roussel, Frédéric Poitevin, Jana Thayer, Daniel Ratner, Auralee Edelen, Apurva Mehta

CoRR, May, 2025

2024

Portable Cross-Facility Workflows for X-ray Ptychography.

Albert Vong, Steven F. Henke, Oliver Hoidn, Hannah Parraga, Tao Zhou, Apurva Mehta, Nicholas Schwarz

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

2023

Physics Constrained Unsupervised Deep Learning for Rapid, High Resolution Scanning Coherent Diffraction Reconstruction.

Oliver Hoidn, Aashwin Ananda Mishra, Apurva Mehta

CoRR, 2023

2022

MLExchange: A web-based platform enabling exchangeable machine learning workflows.

Zhuowen Zhao, Tanny Chavez, Elizabeth Holman, Guanhua Hao, Adam Green, Harinarayan Krishnan, Dylan McReynolds, Ronald Pandolfi, Eric J. Roberts, Petrus H. Zwart, Howard Yanxon, Nicholas Schwarz, Subramanian Sankaranarayanan, Sergei V. Kalinin, Apurva Mehta, Stuart Campbell, Alexander Hexemer

CoRR, 2022

MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies.

Zhuowen Zhao, Tanny Chavez, Elizabeth Holman, Guanhua Hao, Adam Green, Harinarayan Krishnan, Dylan McReynolds, Ronald Pandolfi, Eric J. Roberts, Petrus H. Zwart, Howard Yanxon, Nicholas Schwarz, Subramanian Sankaranarayanan, Sergei V. Kalinin, Apurva Mehta, Stuart Campbell, Alexander Hexemer

Proceedings of the 4th Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing, 2022

2021

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping.

Aaron Gilad Kusne, Austin McDannald, Brian L. DeCost, Corey Oses, Cormac Toher, Stefano Curtarolo, Apurva Mehta, Ichiro Takeuchi

CoRR, 2021

Consistency and Completeness: Rethinking Distributed Stream Processing in Apache Kafka.

Guozhang Wang, Lei Chen, Ayusman Dikshit, Jason Gustafson, Boyang Chen, Matthias J. Sax, John Roesler, Sophie Blee-Goldman, Bruno Cadonna, Apurva Mehta, Varun Madan, Jun Rao

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

Predicting structural class for protein sequences of 40% identity based on features of primary and secondary structure using Random Forest algorithm.

Apurva Mehta, Himanshu S. Mazumdar

Comput. Biol. Chem., 2020

Enabling Scientific Discovery at Next-Generation Light Sources with Advanced AI and HPC.

Nicholas Schwarz, Stuart Campbell, Alexander Hexemer, Apurva Mehta, Jana Thayer

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

2012

Yes you can: offer a comprehensive set of technologies to enhance teaching and learning.

Apurva Mehta

Proceedings of the ACM Proceedings of the SIGUCCS Annual Conference, 2012