| ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data M Haghighatlari, G Vishwakarma, D Altarawy, R Subramanian, BU Kota, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 10 (4), e1458, 2020 | 84 | 2020 |
| Metrics for benchmarking and uncertainty quantification: Quality, applicability, and best practices for machine learning in chemistry G Vishwakarma, A Sonpal, J Hachmann Trends in Chemistry 3 (2), 146-156, 2021 | 80 | 2021 |
| Towards autonomous machine learning in chemistry via evolutionary algorithms G Vishwakarma, M Haghighatlari, J Hachmann | 17 | 2019 |
| A physics-infused deep learning model for the prediction of refractive indices and its use for the large-scale screening of organic compound space M Haghighatlari, G Vishwakarma, MAF Afzal, J Hachmann | 17 | 2019 |
| Machine Learning Model Selection for Predicting Properties of High Refractive Index Polymers G Vishwakarma State University of New York at Buffalo, 2018 | 12 | 2018 |
| Chemlg–a program suite for the generation of compound libraries and the survey of chemical space MAF Afzal, G Vishwakarma, JA Dudwadkar, M Haghighatlari, ... | 7 | 2019 |
| Liquid Organic Hydrogen Carriers: High-throughput Screening of Homogeneous Catalysts G Vishwakarma, J Hachmann | 1 | 2023 |
| Tailor-Made Materials-Inverse Design A Pradhan, G Vishwakarma, J Hachmann 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Design of organic materials with tailored optical properties: Predicting quantum-chemical polarizabilities and derived quantities G Vishwakarma, A Sonpal, A Pradhan, M Haghighatlari, MAF Afzal, ... Quantum Chemistry in the Age of Machine Learning, 653-674, 2023 | | 2023 |
| Data-driven Discovery of Molecular Catalysts for Liquid Organic Hydrogen Carriers G Vishwakarma State University of New York at Buffalo, 2022 | | 2022 |
| Evaluating Homogeneous Catalysts for De-hydrogenation of Liquid Organic Hydrogen Carriers G Vishwakarma APS March Meeting Abstracts 2022, K01. 002, 2022 | | 2022 |
| Acceptorless catalytic dehydrogenation of liquid organic hydrogen carriers: Virtual high-throughput study G Vishwakarma, J Hachmann American Chemical Society SciMeetings 1 (1), 2020 | | 2020 |
| Online Support Vector Regression for Non-Linear Control G Vishwakarma, I Rahman | | |
| OPTIMAL TEMPERATURE HISTORIES FOR BULK POLYMERIZATION OF MMA G Vishwakarma, SS Metkar, RB Mankar, I Rahman | | |
Dr. Johannes HachmannAssociate Professor in the Department of Chemical and Biological Engineering, University at BuffaloVerified email at buffalo.edu