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Employment (3)

Johns Hopkins University: Baltimore, MD, US

2016-08-01 to present | Assistant Professor (Electrical and Computer Engineering)
Employment
Source: Self-asserted source
Archana Venkataraman

Yale School of Medicine: CT, CT, US

2014-01-01 to 2016-04-30 | Postdoctoral Scholar (Radiology & Biomedical Imaging)
Employment
Source: Self-asserted source
Archana Venkataraman

Massachusetts Institute of Technology: Cambridge, MA, US

2012-10-01 to 2013-12-31 | Postdoctoral Fellow (Electrical Engineering and Computer Science)
Employment
Source: Self-asserted source
Archana Venkataraman

Education and qualifications (3)

Massachusetts Institute of Technology: Cambridge, MA, US

2007-09-01 to 2012-09-30 | PhD (Electrical Engineering and Computer Science)
Education
Source: Self-asserted source
Archana Venkataraman

Massachusetts Institute of Technology: Cambridge, MA, US

2006-09-01 to 2007-08-31 | MEng (Electrical Engineering and Computer Science)
Education
Source: Self-asserted source
Archana Venkataraman

Massachusetts Institute of Technology: Cambridge, MA, US

2003-09-01 to 2006-05-31 | BS (Electrical Engineering and Computer Science)
Education
Source: Self-asserted source
Archana Venkataraman

Professional activities (3)

Johns Hopkins University: Baltimore, MD, US

2018-12-01 to present | Assistant Professor (Mathematical Institute for Data Science)
Invited position
Source: Self-asserted source
Archana Venkataraman

Johns Hopkins University: Baltimore, MD, US

2017-08-01 to present | Assistant Professor (Department of Computer Science)
Invited position
Source: Self-asserted source
Archana Venkataraman

Johns Hopkins University: Baltimore, MD, US

2016-08-01 to present | Assistant Professor (Malone Center for Engineering in Healthcare)
Invited position
Source: Self-asserted source
Archana Venkataraman

Works (26)

BEATRICE: Bayesian fine-mapping from summary data using deep variational inference

Bioinformatics
2024-10-01 | Journal article
DOI: 10.1093/bioinformatics/btae590
Contributors: Sayan Ghosal; Michael C Schatz; Archana Venkataraman; Russell Schwartz
Source: check_circle
Crossref

A Diffeomorphic Flow-Based Variational Framework for Multi-Speaker Emotion Conversion

IEEE/ACM Transactions on Audio, Speech, and Language Processing
2023 | Journal article
DOI: 10.1109/TASLP.2022.3209948
Contributors: Ravi Shankar; Hsi-Wei Hsieh; Nicolas Charon; Archana Venkataraman
Source: check_circle
Crossref

EPViz: A flexible and lightweight visualizer to facilitate predictive modeling for multi-channel EEG

PLOS ONE
2023-02-27 | Journal article
DOI: 10.1371/journal.pone.0282268
Contributors: Danielle Currey; Murugappan M; Jeff Craley; David Hsu; Raheel Ahmed; Archana Venkataraman
Source: check_circle
Crossref

DeepEZ: A Graph Convolutional Network for Automated Epileptogenic Zone Localization From Resting-State fMRI Connectivity

IEEE Transactions on Biomedical Engineering
2023-01 | Journal article
DOI: 10.1109/TBME.2022.3187942
Contributors: Naresh Nandakumar; David Hsu; Raheel Ahmed; Archana Venkataraman
Source: check_circle
Crossref

Differences in functional connectivity distribution after transcranial direct‐current stimulation: A connectivity density point of view

Human Brain Mapping
2023-01 | Journal article
DOI: 10.1002/hbm.26112
Contributors: Bohao Tang; Yi Zhao; Archana Venkataraman; Kyrana Tsapkini; Martin A. Lindquist; James Pekar; Brian Caffo
Source: check_circle
Crossref

Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks

2019 | Book chapter
DOI: 10.1007/978-3-030-32251-9_28
Contributors: Jeff Craley; Emily Johnson; Christophe Jouny; Archana Venkataraman
Source: check_circle
Crossref

A Generative-Discriminative Basis Learning Framework to Predict Autism Spectrum Disorder Severity

ISBI: International Symposium on Biomedical Imaging
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data

MICCAI: Medical Image Computing and Computer Assisted Intervention
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

A Generative-Predictive Framework to Capture Altered Brain Activity in fMRI and its Association with Genetic Risk: Application to Schizophrenia

SPIE Medical Imaging
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

A Modified K-means Algorithm for Resting State FMRI Analysis of Brain Tumor Patients, as Validated by Language Localization

ISBI: International Symposium on Biomedical Imaging
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models

MICCAI: Medical Image Computing and Computer Assisted Intervention
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Refining Patient Specific Functional Networks In a Tumor Cohort via Markov Random Fields

CNI: Connectomics in Neuroimaging
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Robust Seizure Detection Using Coupled Hidden Markov Models

ISBI: International Symposium on Biomedical Imaging
2018 | Conference paper
Source: Self-asserted source
Archana Venkataraman

A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort

CNI: International Workshop on Connectomics in NeuroImaging
2017 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Bayesian Community Detection in the Space of Group-Level Functional Differences

IEEE Transactions on Medical Imaging
2016 | Journal article
Source: Self-asserted source
Archana Venkataraman

Pivotal Response Treatment Prompts a Functional Rewiring of the Brain Among Individuals with Autism Spectrum Disorder

NeuroReport
2016 | Journal article
Source: Self-asserted source
Archana Venkataraman

An Unbiased Bayesian Approach to Functional Connectomics Implicates Social-Communication Networks in Autism

NeuroImage Clinical
2013 | Journal article
Source: Self-asserted source
Archana Venkataraman

Detecting Epileptic Regions Based on Global Brain Connectivity Patterns

MICCAI: Medical Image Computing and Computer Assisted Intervention
2013 | Conference paper
Source: Self-asserted source
Archana Venkataraman

From Brain Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder

IEEE Transactions on Medical Imaging
2013 | Journal article
Source: Self-asserted source
Archana Venkataraman

From Brain Connectivity Models to Identifying Foci of a Neurological Disorder

MICCAI: Medical Image Computing and Computer Assisted Intervention
2012 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Joint Modeling of Anatomical and Functional Connectivity for Population Studies

IEEE Transactions on Medical Imaging
2012 | Journal article
Source: Self-asserted source
Archana Venkataraman

Whole Brain Resting State Functional Connectivity Abnormalities in Schizophrenia

Schizophrenia Research
2012 | Journal article
Source: Self-asserted source
Archana Venkataraman

Joint Generative Model for fMRI/DWI and its Application to Population Studies

MICCAI: Medical Image Computing and Computer Assisted Intervention
2010 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Robust Feature Selection in Resting-State fMRI Connectivity Based on Population Studies

MMBIA: IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis
2010 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Exploring Functional Connectivity in fMRI via Clustering

ICASSP: International Conference on Accoustics, Speech and Signal Processing
2009 | Conference paper
Source: Self-asserted source
Archana Venkataraman

Signal Approximation Using the Bilinear Transform

ICASSP: International Conference on Accoustics, Speech and Signal Processing
2008 | Conference paper
Source: Self-asserted source
Archana Venkataraman
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