Rama K. Vasudevan

According to our database, Rama K. Vasudevan authored at least 32 papers between 2017 and 2024.

Collaborative distances:

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

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., March, 2024

Bias in Reinforcement Learning: A Review in Healthcare Applications.

Benjamin Smith, Anahita Khojandi, Rama K. Vasudevan

ACM Comput. Surv., February, 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

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

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

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

2023

Explainability and human intervention in autonomous scanning probe microscopy.

Yongtao Liu, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin

Patterns, November, 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., October, 2023

Adaptive sampling for accelerating neutron diffraction-based strain mapping ^*.

S. V. Venkatakrishnan, Chris M. Fancher, Maxim A. Ziatdinov, Rama K. Vasudevan, Kyle Saleeby, James Haley, Dunji Yu, Ke An, Alex Plotkowski

Mach. Learn. Sci. Technol., June, 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, March, 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., March, 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

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

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

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., December, 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

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

Microscopy is All You Need.

Sergei V. Kalinin, Rama K. Vasudevan, Yongtao Liu, Ayana Ghosh, Kevin Roccapriore, Maxim A. Ziatdinov

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

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

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

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

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

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 P. Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim A. Ziatdinov

CoRR, 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

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, Sarp Oral

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

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, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

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

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

Optimizing Individualized Treatment Planning for Parkinson's Disease Using Deep Reinforcement Learning.

Jeremy Watts, Anahita Khojandi, Rama K. Vasudevan, Ritesh A. Ramdhani

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

2017

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, M. Baris Okatan, Stephen Jesse, Sergei V. Kalinin

Proceedings of the 2017 IEEE International Conference on IC Design and Technology, 2017