Advances of the development of a ferroelectric field-effect transistor on Ge(001). - Patrick Ponath; Agham B. Posadas; Yuan Ren; Xiaoyu Wu; Keji Lai; Alex Demkov; Michael Schmidt; Ray Duffy; Paul K. Hurley; Jian Wang; Chadwin D. Young; Rama K. Vasudevan; et al. (ICICDT, 2017)

Optimizing Individualized Treatment Planning for Parkinson's Disease Using Deep Reinforcement Learning. - Jeremy Watts; Anahita Khojandi; Rama K. Vasudevan; Ritesh A. Ramdhani (EMBC, 2020)

Off-the-shelf deep learning is not enough: parsimony, Bayes and causality. - Rama K. Vasudevan; Maxim A. Ziatdinov; Lukas Vlcek; Sergei V. Kalinin (CoRR, 2020)

Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening. - M. P. Oxley; Junqi Yin; N. Borodinov; Suhas Somnath; Maxim A. Ziatdinov; Andrew R. Lupini; Stephen Jesse; Rama K. Vasudevan; Sergei V. Kalinin (Mach. Learn. Sci. Technol., 2020)

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. - Pravallika Devineni; Panchapakesan Ganesh; Nikhil Sivadas; Abhijeet Dhakane; Ketan Maheshwari; Drahomira Herrmannova; Ramakrishnan Kannan; Seung-Hwan Lim; Thomas E. Potok; Jordan B. Chipka; Priyantha Mudalige; Mark Coletti; et al. (SMC, 2021)

Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery. - Suhas Somnath; Rama K. Vasudevan; Stephen Jesse; Sergei V. Kalinin; Nageswara S. V. Rao; Christopher Brumgard; Feiyi Wang; Olga A. Kuchar; Arjun Shankar; Ben Mintz; Elke Arenholz; J. Robert Michael; et al. (SMC, 2021)

Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy. - Sergei V. Kalinin; Maxim A. Ziatdinov; Jacob D. Hinkle; Stephen Jesse; Ayana Ghosh; Kyle P. Kelley; Andrew R. Lupini; Bobby G. Sumpter; Rama K. Vasudevan (CoRR, 2021)

Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy. - Yongtao Liu; Rama K. Vasudevan; Kyle P. Kelley; Dohyung Kim; Yogesh Sharma; Mahshid Ahmadi; Sergei V. Kalinin; Maxim A. Ziatdinov (CoRR, 2021)

Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis. - Nicole Creange; Kyle P. Kelley; C. Smith; D. Sando; Oliver Paull; N. Valanoor; S. Somnath; S. Jesse; Sergei V. Kalinin; Rama K. Vasudevan (Mach. Learn. Sci. Technol., 2021)

Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy *. - Yongtao Liu; Rama K. Vasudevan; Kyle K. Kelley; Dohyung Kim; Yogesh Sharma; Mahshid Ahmadi; Sergei V. Kalinin; Maxim A. Ziatdinov (Mach. Learn. Sci. Technol., 2021)

Improving Medication Regimen Recommendation for Parkinson's Disease Using Sensor Technology. - Jeremy Watts; Anahita Khojandi; Rama K. Vasudevan; Fatta B. Nahab; Ritesh A. Ramdhani (Sensors, 2021)

Improving Deep Reinforcement Learning With Transitional Variational Autoencoders: A Healthcare Application. - Matthew Baucum; Anahita Khojandi; Rama K. Vasudevan (IEEE J. Biomed. Health Informatics, 2021)

Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning. - Maxim A. Ziatdinov; Yongtao Liu; Kyle P. Kelley; Rama K. Vasudevan; Sergei V. Kalinin (CoRR, 2022)

Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach. - Arpan Biswas; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (CoRR, 2022)

Microscopy is All You Need. - Sergei V. Kalinin; Rama K. Vasudevan; Yongtao Liu; Ayana Ghosh; Kevin Roccapriore; Maxim A. Ziatdinov (CoRR, 2022)

Towards automating structural discovery in scanning transmission electron microscopy *. - Nicole Creange; Ondrej Dyck; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (Mach. Learn. Sci. Technol., 2022)

Experimental discovery of structure-property relationships in ferroelectric materials via active learning. - Yongtao Liu; Kyle P. Kelley; Rama K. Vasudevan; Hiroshi Funakubo; Maxim A. Ziatdinov; Sergei V. Kalinin (Nat. Mach. Intell., 2022)

Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model. - Rama K. Vasudevan; Erick Orozco; Sergei V. Kalinin (Mach. Learn. Sci. Technol., 2022)

A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments. - Arpan Biswas; Yongtao Liu; Nicole Creange; Yu-Chen Liu; Stephen Jesse; Jan-Chi Yang; Sergei V. Kalinin; Maxim A. Ziatdinov; Rama K. Vasudevan (CoRR, 2023)

Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy. - Sergei V. Kalinin; Yongtao Liu; Arpan Biswas; Gerd Duscher; Utkarsh Pratiush; Kevin Roccapriore; Maxim A. Ziatdinov; Rama K. Vasudevan (CoRR, 2023)

Opportunities for Retrieval and Tool Augmented Large Language Models in Scientific Facilities. - Michael H. Prince; Henry Chan; Aikaterini Vriza; Tao Zhou; Varuni K. Sastry; Matthew T. Dearing; Ross J. Harder; Rama K. Vasudevan; Mathew J. Cherukara (CoRR, 2023)

Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach *. - Arpan Biswas; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (Mach. Learn. Sci. Technol., 2023)

Autonomous scanning probe microscopy with hypothesis learning: Exploring the physics of domain switching in ferroelectric materials. - Yongtao Liu; Anna N. Morozovska; Eugene A. Eliseev; Kyle P. Kelley; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (Patterns, 2023)

Adaptive sampling for accelerating neutron diffraction-based strain mapping *. - S. V. Venkatakrishnan 001; Chris M. Fancher; Maxim A. Ziatdinov; Rama K. Vasudevan; Kyle Saleeby; James Haley; Dunji Yu; Ke An; Alex Plotkowski (Mach. Learn. Sci. Technol., 2023)

Optimizing Patient-Specific Medication Regimen Policies Using Wearable Sensors in Parkinson's Disease. - Matt Baucum; Anahita Khojandi; Rama K. Vasudevan; Ritesh A. Ramdhani (Manag. Sci., 2023)

Explainability and human intervention in autonomous scanning probe microscopy. - Yongtao Liu; Maxim A. Ziatdinov; Rama K. Vasudevan; Sergei V. Kalinin (Patterns, 2023)

Image Segmentation of Bacterial Biofilms to Study Pathogen-Surface Interactions. - Sita Sirisha Madugula; Blythe Dumerer; Ruben Millan-Solsona; Checa Nualart Marti; Liam Collins; Rama K. Vasudevan; Retterer Scott; Lance Zhang; Spencer Cox; Jennifer Lynn Morrell-Falvey (IEEE Big Data, 2024)

Synergizing Human Expertise and AI Efficiency with Language Model for Microscopy Operation and Automated Experiment Design. - Yongtao Liu; Marti Checa; Rama K. Vasudevan (CoRR, 2024)

Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities. - Arpan Biswas; Sai Mani Prudhvi Valleti; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (CoRR, 2024)

Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning. - Boris N. Slautin; Yongtao Liu; Hiroshi Funakubo; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (CoRR, 2024)

SANE: Strategic Autonomous Non-Smooth Exploration for Multiple Optima Discovery in Multi-modal and Non-differentiable Black-box Functions. - Arpan Biswas; Rama K. Vasudevan; Rohit Pant; Ichiro Takeuchi; Hiroshi Funakubo; Yongtao Liu (CoRR, 2024)

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization. - Arpan Biswas; Mani Valleti; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (J. Comput. Inf. Sci. Eng., 2024)

Bias in Reinforcement Learning: A Review in Healthcare Applications. - Benjamin Smith; Anahita Khojandi; Rama K. Vasudevan (ACM Comput. Surv., 2024)

Deep kernel methods learn better: from cards to process optimization. - Mani Valleti; Rama K. Vasudevan; Maxim A. Ziatdinov; Sergei V. Kalinin (Mach. Learn. Sci. Technol., 2024)

Curiosity Driven Exploration to Optimize Structure-Property Learning in Microscopy. - Aditya Vatsavai; Ganesh Narasimha; Yongtao Liu; Jan-Chi Yang; Hiroshi Funakubo; Maxim A. Ziatdinov; Rama K. Vasudevan (CoRR, 2025)

Mic-hackathon 2024: Hackathon on Machine Learning for Electron and Scanning Probe Microscopy. - Utkarsh Pratiush; Austin Houston; Kamyar Barakati; Aditya Raghavan; Dasol Yoon; Harikrishnan KP; Zhaslan Baraissov; Desheng Ma; Samuel S. Welborn; Mikolaj Jakowski; Shawn-Patrick Barhorst; Alexander J. Pattison; et al. (CoRR, 2025)