Pratiush, Utkarsh https://orcid.org/0009-0003-7249-103X
Houston, Austin
Barakati, Kamyar
Raghavan, Aditya
Bulanadi, Ralph
Yin, Xiangyu
Welborn, Samuel S
Yoon, Dasol
K P, Harikrishnan
Baraissov, Zhaslan
Ma, Desheng
Jakowski, Mikolaj
Barhorst, Shawn-Patrick
Pattison, Alexander J
Manganaris, Panayotis
Madugula, Sita Sirisha
Gayathri Ayyagari, Sai Venkata
Kennedy, Vishal
Wang, Michelle
Pang, Kieran J
Addison-Smith, Ian
Menacho, Willy
Guzman, Horacio V
Kiefer, Alexander
Furth, Nicholas
Kolev, Nikola L
Petrov, Mikhail
Liu, Viktoriia
Ilyev, Sergey
Rairao, Srikar
Rodani, Tommaso
Pinto-Huguet, Ivan
Chen, Xuli
Cruañes, Josep
Torrens, Marta
Pomar, Jovan
Su, Fanzhi
Vedanti, Pawan
Lyu, Zhiheng
Wang, Xingzhi
Yao, Lehan
Taqieddin, Amir
Laskowski, Forrest
Shao, Yu-Tsun
Fein-Ashley, Benjamin
Jiang, Yi
Kumar, Vineet
Mishra, Himanshu
Paul, Yogesh
Bazgir, Adib
Praneeth Madugula, Rama Chandra
Zhang, Yuwen
Omprakash, Pravan
Huang, Jian
Montufar-Morales, Eric
Chawla, Vivek
Sethi, Harshit
Huang, Jie
Kurki, Lauri
Guinan, Grace
Salvador, Addison
Ter-Petrosyan, Arman
Van Winkle, Madeline
Spurgeon, Steven R https://orcid.org/0000-0003-1218-839X
Narasimha, Ganesh
Wu, Zijie
Liu, Richard
Liu, Yongtao https://orcid.org/0000-0003-0152-1783
Slautin, Boris
Lupini, Andrew R https://orcid.org/0000-0002-1874-7925
Vasudevan, Rama https://orcid.org/0000-0003-4692-8579
Duscher, Gerd
Kalinin, Sergei V
Funding for this research was provided by:
Thermo Fisher Scientific
Office of Naval Research
U.S. Department of Energy, Office of Science,Office of Workforce Development for Teachers and Scientists (WDTS), through the Science Undergraduate Laboratory Internship (SULI) Program
National Renewable Energy Laboratory (DE-AC36-08GO28308)
U.S. Department of Energy, Office of Science, Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory
AI Tennessee Initiative at the University of Tennessee Knoxville.
Laboratory Directed Research and Development
U.S. Department of Energy, Office of Science, Artificial Intelligence Initiative (DE-AC05-00OR22725)
Article Title: Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy
Journal Title: Machine Learning: Science and Technology
Article Type: paper
Copyright Information: © 2025 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2025-06-29
Date Accepted: 2025-11-13
Online publication date: 2025-12-02