Preprints

Sharma, S., Lindsey, K., Kumar, V. Physics-Guided Wildfire Emulation. 2023. *

Ghosh, R., Renganathan, R., Sharma, S., Yang, H., Kumar, V. Entity-Aware Modeling: A Survey. 2023. *

Ghosh, R., Caliley, W., Renganathan, R., Tayal, K., Sharma, S., Jia, X., Kumar, V. Towards Entity-Aware Conditional Variational Inference: An application in Heterogenous Time-Series Prediction. 2023. *

Sharma, S., Sharma, S., Liu, L., Neal, A., Crawford, J., Kiciman, E., Chandra, R. Knowledge-Guided Representation and Causal Structure Learning. 2023. *

Accepted

Sharma, S., Ghosh, R., Renganathan, A., Li, X., Chatterjee, S., Nieber, J., Duffy, C., Kumar, V.  Probabilistic Inverse Modeling: An Application in Hydrology. In 2023 SIAM International Conference on Data Mining (SDM) 2023. *

Sharma, Somya, Marten Thompson, Debra Laefer, Michael Lawler, Kevin McIlhany, Olivier Pauluis, Dallas R. Trinkle, and Snigdhansu Chatterjee. "Machine Learning Methods for Multiscale Physics and Urban Engineering Problems." Entropy 24, no. 8 (2022): 1134.*

Somya Sharma, Swati Sharma, Andy Neal, Sara Malvar, Eduardo Rodrigues, John Crawford, Emre Kiciman, and Ranveer Chandra. "Causal Modeling of Soil Processes for Improved Generalization." In ML for Physical Science Workshop, Neural Information Processing Systems (NeurIPS) 2022.*

Sharma, S., Chatterjee, S. Winsorization for Robust Neural Networks. (2021, December) Entropy special issue on Probabilistic Methods for Deep Learning. Entropy 2021; 23(11):1546.*

Neel Chatterjee, Somya Sharma, Sarah L. Swisher, Snigdhansu Chatterjee. “Approximate Bayesian Computation for Physical Inverse Modeling”, In ML for Physical Science Workshop, Neural Information Processing Systems (NeurIPS) 2021.*

Sharma, S., Chatterjee, S. Corn Yield Prediction in US Midwest Using Artificial Neural Networks. In 2021 PAKDD, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Workshop on Smart & Precise Agriculture (PAKDD) 2021.*

Sharma, S., Ray, D., Chatterjee, S. Climate Change Driven Crop Yield Failures. In 2020 Workshop on Tacking Climate Change with Machine Learning, Neural Information Processing Systems (NeurIPS) 2020.*

Invited Presentations at Professional Meetings, Conferences, etc.

1.     Poster presentation on Uncertainty Quantification in Hydrology in ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach CA. 2023

2.     Student paper presentation on Uncertainty Quantification in Hydrology in the International Indian Statistical Association Conference, Golden. 2023.

3.     Invited presentation on Graph Neural Network for Spatial Statistical Modeling in the International Conference on Econometrics and Statistics. 2023.

4.     Invited presentation on Responsible AI in MIDAS Future Leaders Summit, Ann Arbor. 2023.

5.     Somya Sharma, Swati Sharma, Andy Neal, Sara Malvar, Eduardo Rodrigues, John Crawford, Emre Kiciman, and Ranveer Chandra. "Causal Modeling of Soil Processes for Improved Generalization." Presentation in ML for Physical Science Workshop, Neural Information Processing Systems (NeurIPS) 2022.

6. Invited talk on Interpretable Machine Learning. Minnesota Center for Financial and Actuarial Mathematics, Machine Learning Summer Camp. 2022.

7. Sharma, S., Chatterjee, S. Multi-scale Gaussian Processes for Dynamical Systems. Presentation in NISS Graduate Student Research Conference. 2022.

8.     Neel Chatterjee, Somya Sharma, Sarah L. Swisher, Snigdhansu Chatterjee. “Approximate Bayesian Computation for Physical Inverse Modeling”, In ML for Physical Science Workshop, Neural Information Processing Systems (NeurIPS) 2021.

9. Invited talk on Multi-resolution Gaussian Processes for Modeling Large Scale Physical Processes. GRADS Computer Science Graduate Student Associations. 2022.

10.  Sharma, S., Chatterjee, S. Corn Yield Prediction in US Midwest Using Artificial Neural Networks. Highlighted talk in 2021 PAKDD, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Workshop on Smart & Precise Agriculture (PAKDD) 2021.

11.  Sharma, S., Ray, D., Chatterjee, S. Climate Change Driven Crop Yield Failures. Highlighted talk in 2020 Workshop on Tacking Climate Change with Machine Learning, Neural Information Processing Systems (NeurIPS) 2020.

12.  Invited talk on Computer Vision and AI for Earth. Women in Analytics & Data Science Conference, MinneAnalytics. 2020.

13.  Invited talk on Animated Spatial Maps in R Shiny. R Ladies, Twin Cities. 2019.

14.  Invited talk on Git Version Control. Women in Machine Learning & Data Science, Twin Cities. 2019