A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart Mostofsky; Archana Venkataraman (MICCAI (3), 2018)

Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields. - Naresh Nandakumar; Niharika Shimona D'Souza; Jeff Craley; Komal Manzoor; Jay J. Pillai; Sachin K. Gujar; Haris I. Sair; Archana Venkataraman (CNI@MICCAI, 2018)

A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart Mostofsky; Archana Venkataraman (IPMI, 2019)

Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart Mostofsky; Archana Venkataraman (MICCAI (3), 2019)

A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Nicholas F. Wymbs; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (MICCAI (7), 2020)

A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. - Naresh Nandakumar; Niharika Shimona D'Souza; Komal Manzoor; Jay J. Pillai; Sachin K. Gujar; Haris I. Sair; Archana Venkataraman (MLCN/RNO-AI@MICCAI, 2020)

A joint network optimization framework to predict clinical severity from resting state functional MRI data. - Niharika Shimona D'Souza; Mary Beth Nebel; Nicholas F. Wymbs; Stewart H. Mostofsky; Archana Venkataraman (NeuroImage, 2020)

Predicting Acute Kidney Injury via Interpretable Ensemble Learning and Attention Weighted Convoutional-Recurrent Neural Networks. - Yu-Chung Peng; Niharika Shimona D'Souza; Brian Bush; Charles Brown; Archana Venkataraman (CISS, 2021)

A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (MICCAI (7), 2021)

M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (MIDL, 2021)

A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Nicholas F. Wymbs; Joshua Robinson; Stewart Mostofsky; Archana Venkataraman (CoRR, 2021)

Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. - Niharika Shimona D'Souza; Mary Beth Nebel; Deana Crocetti; Joshua Robinson; Nicholas F. Wymbs; Stewart H. Mostofsky; Archana Venkataraman (NeuroImage, 2021)

Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis. - Niharika Shimona D'Souza; Hongzhi Wang 002; Andrea Giovannini; Antonio Foncubierta-Rodríguez; Kristen L. Beck; Orest B. Boyko; Tanveer F. Syeda-Mahmood (MICCAI (8), 2022)

mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. - Niharika Shimona D'Souza; Archana Venkataraman (IPMI, 2023)

Feature Selection for Malapposition Detection in Intravascular Ultrasound - A Comparative Study. - 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; et al. (AMAI@MICCAI, 2023)

MaxCorrMGNN: A Multi-graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction. - Niharika Shimona D'Souza; Hongzhi Wang 002; Andrea Giovannini; Antonio Foncubierta-Rodríguez; Kristen L. Beck; Orest B. Boyko; Tanveer F. Syeda-Mahmood (ML4MHD, 2023)

Bayesian Models of Functional Connectomics and Behavior. - Niharika Shimona D'Souza (CoRR, 2023)

Multimodal Sleep Apnea Detection with Missing or Noisy Modalities. - Hamed Fayyaz; Niharika S. D'Souza; Rahmatollah Beheshti (MLHC, 2024)

Geo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound. - 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 (MLMI@MICCAI (1), 2024)

Multimodal Sleep Apnea Detection with Missing or Noisy Modalities. - Hamed Fayyaz; Abigail Strang; Niharika Shimona D'Souza; Rahmatollah Beheshti (CoRR, 2024)

Fusing modalities by multiplexed graph neural networks for outcome prediction from medical data and beyond. - Niharika Shimona D'Souza; Hongzhi Wang 002; Andrea Giovannini; Antonio Foncubierta-Rodríguez; Kristen L. Beck; Orest B. Boyko; Tanveer F. Syeda-Mahmood (Medical Image Anal., 2024)

Modern Hopfield Networks meet Encoded Neural Representations - Addressing Practical Considerations. - Satyananda Kashyap; Niharika S. D'Souza; Luyao Shi; Ken C. L. Wong; Hongzhi Wang 002; Tanveer F. Syeda-Mahmood (UniReps, 2025)

Language Models Are Good Tabular Learners. - Zhenhan Huang; Kavitha Srinivas; Horst Samulowitz; Niharika S. D'Souza; Charu C. Aggarwal; Pin-Yu Chen; Jianxi Gao (Trans. Mach. Learn. Res., 2025)

Automatic Prompt Optimization for Knowledge Graph Construction: Insights from an Empirical Study. - Nandana Mihindukulasooriya; Niharika S. D'Souza; Md. Faisal Mahbub Chowdhury; Horst Samulowitz (CoRR, 2025)