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ORCIDNiharika S. D'Souza
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- affiliation: IBM Research Almaden, San Jose, CA, USA
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Journal Articles
- 2025
[j4]Zhenhan Huang, Kavitha Srinivas, Horst Samulowitz, Niharika S. D'Souza, Charu C. Aggarwal, Pin-Yu Chen, Jianxi Gao:
Language Models Are Good Tabular Learners. Trans. Mach. Learn. Res. 2025 (2025)- 2024
- [j3]Niharika Shimona D'Souza, Hongzhi Wang, Andrea Giovannini
, Antonio Foncubierta-Rodríguez, Kristen L. Beck, Orest B. Boyko, Tanveer F. Syeda-Mahmood:
Fusing modalities by multiplexed graph neural networks for outcome prediction from medical data and beyond. Medical Image Anal. 93: 103064 (2024) - 2021
- [j2]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. NeuroImage 241: 118388 (2021) - 2020
- [j1]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
A joint network optimization framework to predict clinical severity from resting state functional MRI data. NeuroImage 206 (2020)
Conference and Workshop Papers
- 2024
- [c14]Yiming Chen, Niharika Shimona D'Souza, Akshith Mandepally, Patrick Henninger, Satyananda Kashyap, Neerav Karani, Neel Dey, Marcos Zachary, Raed Rizq, Paul Chouinard, Polina Golland, Tanveer F. Syeda-Mahmood:
Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound. MLMI@MICCAI (1) 2024: 300-309 - 2023
- [c13]Niharika Shimona D'Souza, Archana Venkataraman:
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. IPMI 2023: 53-65 - [c12]Satyananda Kashyap, Neerav Karani, Alexander Shang, Niharika Shimona D'Souza, Neel Dey, Lay Jain, Ray Wang, Hatice Akakin, Qian Li, Wenguang Li, Corydon Carlson, Polina Golland, Tanveer F. Syeda-Mahmood:
Feature Selection for Malapposition Detection in Intravascular Ultrasound - A Comparative Study. AMAI@MICCAI 2023: 165-175 - [c11]Niharika Shimona D'Souza, Hongzhi Wang, Andrea Giovannini, Antonio Foncubierta-Rodríguez, Kristen L. Beck, Orest B. Boyko, Tanveer F. Syeda-Mahmood:
MaxCorrMGNN: A Multi-graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction. ML4MHD 2023: 141-154 - 2022
- [c10]Niharika Shimona D'Souza, Hongzhi Wang, Andrea Giovannini, Antonio Foncubierta-Rodríguez, Kristen L. Beck, Orest B. Boyko, Tanveer F. Syeda-Mahmood:
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis. MICCAI (8) 2022: 287-297 - 2021
- [c9]Yu-Chung Peng, Niharika Shimona D'Souza, Brian Bush, Charles Brown, Archana Venkataraman:
Predicting Acute Kidney Injury via Interpretable Ensemble Learning and Attention Weighted Convoutional-Recurrent Neural Networks. CISS 2021: 1-6 - [c8]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. MICCAI (7) 2021: 625-636 - [c7]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. MIDL 2021: 119-130 - 2020
- [c6]Naresh Nandakumar, Niharika Shimona D'Souza, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman:
A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. MLCN/RNO-AI@MICCAI 2020: 34-44 - [c5]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. MICCAI (7) 2020: 437-447 - 2019
- [c4]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. IPMI 2019: 605-616 - [c3]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. MICCAI (3) 2019: 709-717 - 2018
- [c2]Naresh Nandakumar, Niharika Shimona D'Souza, Jeff Craley, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman:
Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields. CNI@MICCAI 2018: 88-98 - [c1]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. MICCAI (3) 2018: 163-171
Informal and Other Publications
- 2024
- [i14]Hamed Fayyaz, Abigail Strang, Niharika Shimona D'Souza, Rahmatollah Beheshti:
Multimodal Sleep Apnea Detection with Missing or Noisy Modalities. CoRR abs/2402.17788 (2024) - [i13]Yiming Chen, Niharika Shimona D'Souza, Akshith Mandepally, Patrick Henninger, Satyananda Kashyap, Neerav Karani, Neel Dey, Marcos Zachary, Raed Rizq, Paul Chouinard, Polina Golland, Tanveer F. Syeda-Mahmood:
Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound. CoRR abs/2408.04826 (2024) - [i12]Satyananda Kashyap, Niharika Shimona D'Souza, Luyao Shi, Ken C. L. Wong, Hongzhi Wang, Tanveer F. Syeda-Mahmood:
Modern Hopfield Networks meet Encoded Neural Representations - Addressing Practical Considerations. CoRR abs/2409.16408 (2024) - 2023
- [i11]Niharika Shimona D'Souza:
Bayesian Models of Functional Connectomics and Behavior. CoRR abs/2301.06182 (2023) - [i10]Niharika Shimona D'Souza, Archana Venkataraman:
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. CoRR abs/2303.14986 (2023) - [i9]Niharika Shimona D'Souza, Hongzhi Wang, Andrea Giovannini, Antonio Foncubierta-Rodríguez, Kristen L. Beck, Orest B. Boyko, Tanveer F. Syeda-Mahmood:
MaxCorrMGNN: A Multi-Graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction. CoRR abs/2307.07093 (2023) - 2022
- [i8]Niharika Shimona D'Souza, Hongzhi Wang, Andrea Giovannini, Antonio Foncubierta-Rodríguez, Kristen L. Beck, Orest B. Boyko, Tanveer F. Syeda-Mahmood:
Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis. CoRR abs/2210.14377 (2022) - 2021
- [i7]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. CoRR abs/2105.14409 (2021) - 2020
- [i6]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. CoRR abs/2007.01929 (2020) - [i5]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. CoRR abs/2007.01930 (2020) - [i4]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. CoRR abs/2007.01931 (2020) - [i3]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart H. Mostofsky, Archana Venkataraman:
Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations. CoRR abs/2008.12410 (2020) - [i2]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data. CoRR abs/2009.03238 (2020) - [i1]Naresh Nandakumar, Niharika Shimona D'Souza, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman:
A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. CoRR abs/2011.08813 (2020)
Coauthor Index
aka: Stewart Mostofsky
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