Research Summary
My current research is focused on the development of algorithms for building predictive and causal models from large amounts of heterogeneous, high dimensional, spatial, temporal, multi-scale data and the application of the resulting tools in predicting health risks and health outcomes using combinations of clinical, genomic, behavioral, environmental, and socio-demographic data, modeling complex interactions between food, energy, and water systems, and people.In the News
Research Keywords
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Recent Publications
Class Incremental Learning from First Principles: A Review
Ashtekar, N., Zhu, J. & Honavar, V. G., 2025, In: Transactions on Machine Learning Research. 2025Research output: Contribution to journal › Article › peer-review
C-HDNet: A Fast Hyperdimensional Computing Based Method for Causal Effect Estimation from Networked Observational Data
Dalvi, A., Ashtekar, N. & Honavar, V. G., Dec 2025, In: Social Network Analysis and Mining. 15, 1, 97.Research output: Contribution to journal › Review article › peer-review
A practical guide to machine learning interatomic potentials – Status and future
Jacobs, R., Morgan, D., Attarian, S., Meng, J., Shen, C., Wu, Z., Xie, C. Y., Yang, J. H., Artrith, N., Blaiszik, B., Ceder, G., Choudhary, K., Csanyi, G., Cubuk, E. D., Deng, B., Drautz, R., Fu, X., Godwin, J., Honavar, V. & Isayev, O. & 10 others, , Mar 2025, In: Current Opinion in Solid State and Materials Science. 35, 101214.Research output: Contribution to journal › Review article › peer-review
Beyond training data: how elemental features enhance ML-based formation energy predictions
Mahdavi, H., Honavar, V. & Morgan, D., Oct 8 2025, In: Digital Discovery. 4, 10, p. 2972-2982 11 p.Research output: Contribution to journal › Article › peer-review
Causal Matching using Random Hyperplane Tessellations
Dalvi, A., Ashtekar, N. & Honavar, V., 2024, In: Proceedings of Machine Learning Research. 236, p. 688-702 15 p.Research output: Contribution to journal › Conference article › peer-review
Can machine learning predict late seizures after intracerebral hemorrhages? Evidence from real-world data
Lekoubou, A., Petucci, J., Femi Ajala, T., Katoch, A., Hong, J., Sen, S., Bonilha, L., Chinchilli, V. M. & Honavar, V., Aug 2024, In: Epilepsy and Behavior. 157, 109835.Research output: Contribution to journal › Article › peer-review
Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data
Liang, J., Ren, W., Sahar, H. & Honavar, V., Mar 25 2024, In: Proceedings of the AAAI Conference on Artificial Intelligence. 38, 12, p. 13736-13743 8 p.Research output: Contribution to journal › Conference article › peer-review
Real world study of racial disparities associated with toxicities of sacituzumab govitecan
Priyadarshini, S., Petucci, J., Katoch, A., Honavar, V. & Vasekar, M. K., 2024, In: Journal of Clinical Oncology. 42, 16, 1572.Research output: Contribution to journal › Article › peer-review
TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules
Ren, W., Li, X., Chen, H., Rakesh, V., Wang, Z., Das, M. & Honavar, V., 2024, In: Proceedings of Machine Learning Research. 235, p. 42417-42427 11 p.Research output: Contribution to journal › Conference article › peer-review
Corrigendum to “Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing” [Sleep Health 9 (2023) 596-610, (S2352721823001341), (10.1016/j.sleh.2023.07.001)]
Roberts, D. M., Schade, M. M., Master, L., Honavar, V. G., Nahmod, N. G., Chang, A. M., Gartenberg, D. & Buxton, O. M., 2024, (Accepted/In press) In: Sleep health. 10, 2, p. 255-260 6 p.Research output: Contribution to journal › Comment/debate › peer-review
Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment
Xiao, T., Yuan, Y., Zhu, H., Li, M. & Honavar, V. G., 2024, In: Advances in Neural Information Processing Systems. 37Research output: Contribution to journal › Conference article › peer-review
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs
Xiao, T., Zhu, H., Zhang, Z., Guo, Z., Aggarwal, C. C., Wang, S. & Honavar, V. G., 2024, In: Proceedings of Machine Learning Research. 235, p. 54363-54381 19 p.Research output: Contribution to journal › Conference article › peer-review
Forecasting User Interests Through Topic Tag Predictions in Online Health Communities
Adishesha, A. S., Jakielaszek, L., Azhar, F., Zhang, P., Honavar, V., Ma, F., Belani, C., Mitra, P. & Huang, S. X., Jul 1 2023, In: IEEE Journal of Biomedical and Health Informatics. 27, 7, p. 3645-3656 12 p.Research output: Contribution to journal › Article › peer-review
MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein–Protein Docking Conformations
Jung, Y., Geng, C., Bonvin, A. M. J. J., Xue, L. C. & Honavar, V. G., Jan 2023, In: Biomolecules. 13, 1, 121.Research output: Contribution to journal › Article › peer-review
Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing
Roberts, D. M., Schade, M. M., Master, L., Honavar, V. G., Nahmod, N. G., Chang, A.-M., Gartenberg, D. & Buxton, O. M., Aug 10 2023, (E-pub ahead of print) In: Sleep health.Research output: Contribution to journal › Article › peer-review