| 2025 | MICCAI | BiSCoT: Behavior-Informed Subgroup-Consistent Connectome Template for Interpretable Brain Network Analysis. | Zijian Chen, Stefen Beeler-Duden, Sophie Lawson, Zachary J. Jacokes, John Darrell Van Horn, Kevin A. Pelphrey, Archana Venkataraman |
| 2025 | MICCAI | LLM-Powered Cross-Modal Alignment for Explainable Seizure Detection from EEG. | Maryam Riazi, Deeksha M. Shama, Archana Venkataraman |
| 2025 | MICCAI | Learning Explainable Imaging-Genetics Associations Related to a Neurological Disorder. | Jueqi Wang, Zachary J. Jacokes, John Darrell Van Horn, Michael C. Schatz, Kevin A. Pelphrey, Archana Venkataraman |
| 2024 | MICCAI | A Lesion-Aware Edge-Based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia. | Zijian Chen, Maria Varkanitsa, Prakash Ishwar, Janusz Konrad, Margrit Betke, Swathi Kiran, Archana Venkataraman |
| 2024 | MICCAI | QID | Zijian Chen, Jueqi Wang, Archana Venkataraman |
| 2024 | MICCAI | GAMing the Brain: Investigating the Cross-Modal Relationships Between Functional Connectivity and Structural Features Using Generalized Additive Models. | Arunkumar Kannan, Brian Caffo, Archana Venkataraman |
| 2024 | MICCAI | Uncertainty-Aware Bayesian Deep Learning with Noisy Training Labels for Epileptic Seizure Detection. | Deeksha M. Shama, Archana Venkataraman |
| 2023 | MICCAI | DeepSOZ: A Robust Deep Model for Joint Temporal and Spatial Seizure Onset Localization from Multichannel EEG Data. | Deeksha M. Shama, Jiasen Jing, Archana Venkataraman |
| 2022 | ICLR | A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease. | Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Archana Venkataraman |
| 2022 | MICCAI | RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis. | Naresh Nandakumar, Komal Manzoor, Shruti Agarwal, Haris I. Sair, Archana Venkataraman |
| 2021 | CISS | Cross-site Epileptic Seizure Detection Using Convolutional Neural Networks. | Danielle Currey, David Hsu, Raheel Ahmed, Archana Venkataraman, Jeff Craley |
| 2021 | CISS | 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 |
| 2021 | MICCAI | 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 |
| 2020 | Interspeech | Multi-Speaker Emotion Conversion via Latent Variable Regularization and a Chained Encoder-Decoder-Predictor Network. | Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman |
| 2020 | Interspeech | Non-Parallel Emotion Conversion Using a Deep-Generative Hybrid Network and an Adversarial Pair Discriminator. | Ravi Shankar, Jacob Sager, Archana Venkataraman |
| 2020 | MICCAI | 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 |
| 2020 | MICCAI | 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 |
| 2019 | Interspeech | VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English. | Jacob Sager, Ravi Shankar, Jacob Reinhold, Archana Venkataraman |
| 2019 | Interspeech | Automated Emotion Morphing in Speech Based on Diffeomorphic Curve Registration and Highway Networks. | Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman |
| 2019 | Interspeech | A Multi-Speaker Emotion Morphing Model Using Highway Networks and Maximum Likelihood Objective. | Ravi Shankar, Jacob Sager, Archana Venkataraman |
| 2019 | Interspeech | Weakly Supervised Syllable Segmentation by Vowel-Consonant Peak Classification. | Ravi Shankar, Archana Venkataraman |
| 2019 | MICCAI | Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks. | Jeff Craley, Emily Johnson, Christophe Jouny, Archana Venkataraman |
| 2019 | MICCAI | 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 |
| 2019 | MICCAI | Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework. | Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Karen Faith Berman, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman |
| 2019 | MICCAI | A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity. | Naresh Nandakumar, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman |
| 2018 | MICCAI | A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models. | Jeff Craley, Emily Johnson, Archana Venkataraman |
| 2018 | MICCAI | 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 |
| 2018 | MICCAI | 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 |
| 2017 | MICCAI | A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. | Archana Venkataraman, Nicholas F. Wymbs, Mary Beth Nebel, Stewart Mostofsky |
| 2013 | MICCAI | Detecting Epileptic Regions Based on Global Brain Connectivity Patterns. | Andrew Sweet, Archana Venkataraman, Steven M. Stufflebeam, Hesheng Liu, Naoro Tanaka, Joseph R. Madsen, Polina Golland |
| 2012 | MICCAI | From Brain Connectivity Models to Identifying Foci of a Neurological Disorder. | Archana Venkataraman, Marek Kubicki, Polina Golland |
| 2010 | CVPR | Robust feature selection in resting-state fMRI connectivity based on population studies. | Archana Venkataraman, Marek Kubicki, Carl-Fredrik Westin, Polina Golland |
| 2010 | MICCAI | Joint Generative Model for fMRI/DWI and Its Application to Population Studies. | Archana Venkataraman, Yogesh Rathi, Marek Kubicki, Carl-Fredrik Westin, Polina Golland |
| 2009 | ICASSP | Exploring functional connectivity in fMRI via clustering. | Archana Venkataraman, Koene R. A. Van Dijk, Randy L. Buckner, Polina Golland |
| 2008 | ACSSC | Spatial patterns and functional profiles for discovering structure in fMRI data. | Polina Golland, Danial Lashkari, Archana Venkataraman |
| 2008 | ICASSP | Signal approximation using the bilinear transform. | Archana Venkataraman, Alan V. Oppenheim |