| A non-enzymatic urea sensor based on the nickel sulfide/graphene oxide modified glassy carbon electrode TSSK Naik, S Saravanan, KNS Saravana, U Pratiush, PC Ramamurthy Materials Chemistry and Physics 245, 122798, 2020 | 73 | 2020 |
| Human-in-the-Loop: The Future of Machine Learning in Automated Electron Microscopy SV Kalinin, Y Liu, A Biswas, G Duscher, U Pratiush, K Roccapriore, ... Microscopy Today 32 (1), 35-41, 2024 | 19 | 2024 |
| Egraffbench: Evaluation of equivariant graph neural network force fields for atomistic simulations, 2023 V Bihani, U Pratiush, S Mannan, T Du, Z Chen, S Miret, M Micoulaut, ... URL https://arxiv. org/abs/2310.02428, 0 | 15* | |
| Co-orchestration of multiple instruments to uncover structure–property relationships in combinatorial libraries BN Slautin, U Pratiush, IN Ivanov, Y Liu, R Pant, X Zhang, I Takeuchi, ... Digital Discovery 3 (8), 1602-1611, 2024 | 8* | 2024 |
| Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation Y Liu, U Pratiush, J Bemis, R Proksch, R Emery, PD Rack, YC Liu, ... arXiv preprint arXiv:2405.12300, 2024 | 5 | 2024 |
| Implementing dynamic high-performance computing supported workflows on Scanning Transmission Electron Microscope U Pratiush, A Houston, SV Kalinin, G Duscher arXiv preprint arXiv:2406.11018, 2024 | 3* | 2024 |
| Building Workflows for Interactive Human in the Loop Automated Experiment (hAE) in STEM-EELS U Pratiush, KM Roccapriore, Y Liu, G Duscher, M Ziatdinov, SV Kalinin arXiv preprint arXiv:2404.07381, 2024 | 3 | 2024 |
| Machine Learning-Based Reward-Driven Tuning of Scanning Probe Microscopy: Towards Fully Automated Microscopy Y Liu, R Proksch, J Bemis, U Pratiush, A Dubey, M Ahmadi, R Emery, ... arXiv preprint arXiv:2408.04055, 2024 | 2 | 2024 |
| Multimodal co-orchestration for exploring structure-property relationships in combinatorial libraries via multi-task Bayesian optimization SV Kalinin, BN Slautin, U Pratiush, IN Ivanov, Y Liu, R Pant, X Zhang, ... Microscopy and Microanalysis 30 (Supplement_1), ozae044. 157, 2024 | 2 | 2024 |
| Scientific exploration with expert knowledge (SEEK) in autonomous scanning probe microscopy with active learning U Pratiush, H Funakubo, R Vasudevan, SV Kalinin, Y Liu Digital Discovery, 2025 | 1 | 2025 |
| Unsupervised Reward-Driven Image Segmentation in Automated Scanning Transmission Electron Microscopy Experiments K Barakati, U Pratiush, AC Houston, G Duscher, SV Kalinin arXiv preprint arXiv:2409.12462, 2024 | 1 | 2024 |
| Automating Experiments with Scanning Probe Microscopy R Liu, U Pratiush, J Bemis, R Proksch, SV Kalinin Microscopy and Microanalysis 30 (Supplement_1), ozae044. 1010, 2024 | 1 | 2024 |
| Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization A Raghavan, U Pratiush, M Valleti, RY Liu, R Emery, H Funakubo, Y Liu, ... Journal of Applied Physics 137 (3), 2025 | | 2025 |
| Roadmap on Atomic-scale Semiconductor Devices SR Schofield, AJ Fisher, E Ginossar, JW Lyding, RM Silver, F Fei, ... Nano Futures, 2025 | | 2025 |
| Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Y Zimmermann, A Bazgir, Z Afzal, F Agbere, Q Ai, N Alampara, ... arXiv preprint arXiv:2411.15221, 2024 | | 2024 |
| Constrained DKL to Accelerate Structure-Property Relationship Discovery in Automated Electron and Scanning Probe Microscopy U Pratiush, J Yao, M Checa, Y Liu, SV Kalinin, Y Liu Microscopy and Microanalysis 30 (Supplement_1), ozae044. 1021, 2024 | | 2024 |
| Realizing Smart STEM via Machine Learning on Remote High Performance Computer U Pratiush, KM Roccapriore, Y Liu, SV Kalinin, G Duscher Microscopy and Microanalysis 30 (Supplement_1), ozae044. 164, 2024 | | 2024 |
| Silicon Nanostructures Through Guided Recrystallization G Duscher, A Houston, U Pratiush, MF Chisholm, S Kalinin Microscopy and Microanalysis 30 (Supplement_1), ozae044. 1013, 2024 | | 2024 |
| Discovering mesoscopic descriptions of collective movement with neural stochastic modelling U Pratiush, A Nabeel, V Guttal, P AP arXiv preprint arXiv:2303.09906, 2023 | | 2023 |
| Machine Learning meets Statistical Physics: a Web3 perspective: EC Matteo Manzi, Utkarsh Pratiush https://desci.crunchdao.com/projects/crunchdao/feature-engineering/about, 2023 | | 2023 |
Sergei V. KalininWeston Fulton Chair Professor, UT Knoxville. Chief Scientist, AI/ML for Physical Sciences, PNNLVerificeret mail på utk.edu