Publications

Mathematics of Data Science

  1. Shekhar P., Babu M., and Patra A. Hierarchical regularization networks for sparsification based learning on noisy datasets. Foundations of Data Science. 2023; doi: 10.3934/fods.2023009 Link arXiv Code.

  2. Shekhar P. and Patra A., A Forward Backward Greedy Approach for Sparse Multiscale Learning. Computer Methods in Applied Mechanics and Engineering. 2022; 400: 115420 Link arXiv Code.

  3. Shekhar P. and Patra A., Hierarchical approximations for data reduction and learning at multiple scales. Foundations of Data Science. 2020;2(2):123-154 Link arXiv Code.

AI in Medicine

  1. Vora, N., Shekhar, P., Esmail, M., Patra, A., & Georgakoudi, I. Deep Learning-Enabled, Detection of Rare Circulating Tumor Cell Clusters in Whole Blood Using Label-free, Flow Cytometry. bioRxiv, 2023 August Link..

  2. Vora, N., Shekhar, P., Kwan, J., Esmail, M., Patra, A., and Georgakoudi, I. Meet the clusters: a deep learning approach for label-free detection of circulating tumor cell clusters using flow cytometry. In Multiscale Imaging and Spectroscopy IV (p. PC123630A). SPIE. 2023 March Link.

  3. Vora, N., Shekhar, P., Esmail, M., Patra, A., and Georgakoudi, I. Label-free flow cytometry of rare circulating tumor cell clusters in whole blood. Nature Scientific Reports. 2022 ;12(1): 1-14 Link.

  4. Georgakoudi, I., Vora, N., Shekhar, P., and Patra, A. Label-free flow cytometric detection of circulating tumor cell clusters is enabled in whole blood samples by machine learning-based signal analysis. In Unconventional Optical Imaging III (p. PC121360U). SPIE. 2022 May Link.

  5. Vora, N., Shekhar, P., Esmail, M., Patra, A., and Georgakoudi, I. Detection of Rare Circulating Tumor Cell Clusters in Whole Blood Using Label-free, Flow Cytometry. In Microscopy Histopathology and Analytics (pp. MW3A-3). Optica Publishing Group. 2022 April Link.

AI in Engineering

  1. Babu, M., Franciosa, P., Shekhar, P., and Ceglarek, D. Object Shape Error Modelling and Simulation During Early Design Phase by Morphing Gaussian Random Fields. Computer-Aided Design, 2023; 158, 103481 Link.

  2. Parida, S. S., Bose, S., Butcher, M., Apostolakis, G., and Shekhar, P.. SVD enabled data augmentation for machine learning based surrogate modeling of non-linear structures. Engineering Structures, 2023; 280, 115600 Link.

  3. Dasarla Giri Babu, V., Chao, Y., Lopes, N. C., Ricklick, M., Shekhar, P., and Boetcher, S. Impact of Data Representation on Artificial Neural Network Performance in sCO2 Cooling Applications. In AIAA SCITECH (p. 0390). 2023 January Link.

  4. Chan F.T., Shekhar P. and Tiwari M.K., Dynamic scheduling of oil tankers with splitting of cargo at pickup and delivery locations: a Multi-objective Ant Colony-based approach. International Journal of Production Research. 2014 Dec 17;52(24):7436-53 Link.

AI in Remote Sensing and Environmental Science

  1. Shekhar P., Csathó B., Schenk T., Roberts C. and Patra A., ALPS: A Unified Framework for Modeling Time Series of Land Ice Changes. IEEE Transactions on Geoscience and Remote Sensing. 2020 Oct 16. Link arXiv Code.

  2. Shekhar P., Csatho B., Schenk T. and Patra A., Localized time series modeling of Greenland ice sheet elevation changes. In Proceedings of the 8th International Workshop on Climate Informatics: CI 2018 (No. NCAR/TN-550+PROC). doi:10.5065/D6BZ64XQ.

  3. Shekhar P., Patra A. and Csatho B., Multiscale and Multiresolution methods for Sparse representation of Large datasets. Procedia Computer Science. 2017 Jan 1;108:1652-61Link.

  4. Shekhar P. and Rai R., Anomaly Detection in Complex Spatiotemporal Networks Through Location Aware Geospatial Big Data Sets. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2016 Aug 21 (Vol. 50190). American Society of Mechanical Engineers Link.

  5. Shekhar P., Patra A and Stefanescu ER., Multilevel methods for sparse representation of topographical data. Procedia Computer Science. 2016 Jan 1;80:887-96 Link.