Profiles

Archana Venkataraman, PhD

Associate Professor, Biostatistics - Boston University School of Public Health

(617) 358-6008
archanav@bu.edu
Photonics Building
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Biography

Archana Venkataraman is an Associate Professor of Electrical and Computer Engineering at Boston University. From 2016-2022, she was an Assistant Professor at Johns Hopkins University. Dr. Venkataraman directs the Neural Systems Analysis Laboratory and is affiliated with the Department of Biostatistics, the Department of Biomedical Engineering, the Center for Brain Recovery, and the Rafik B. Hariri Institute for Computing at Boston University. Dr. Venkataraman’s research lies at the intersection of biomedical imaging, artificial intelligence, and clinical neuroscience. Her work has yielded novel insights in to debilitating neurological disorders, such as autism, schizophrenia, and epilepsy, with the long-term goal of improving patient care. Dr. Venkataraman completed her B.S., M.Eng. and Ph.D. in Electrical Engineering at MIT in 2006, 2007 and 2012, respectively. She is a recipient of the MIT Provost Presidential Fellowship, the Siebel Scholarship, the National Defense Science and Engineering Graduate Fellowship, the NIH Advanced Multimodal Neuroimaging Training Grant, numerous best paper awards, and the National Science Foundation CAREER award. Dr. Venkataraman was also named by MIT Technology Review as one of 35 Innovators Under 35 in 2019.

Other Positions

  • Associate Professor, Electrical and Computer Engineering - Boston University College of Engineering

Education

  • Massachusetts Institute of Technology, PhD Field of Study: Electrical Engineering
  • Massachusetts Institute of Technology, ME/MEng Field of Study: Electrical Engineering
  • Massachusetts Institute of Technology, SB/ScB Field of Study: Electrical Engineering

Websites

Publications

  • Published on 10/1/2024

    Ghosal S, Schatz MC, Venkataraman A. BEATRICE: Bayesian fine-mapping from summary data using deep variational inference. Bioinformatics. 2024 Oct 01; 40(10). PMID: 39360993.

     Read At: PubMed
  • Published on 9/11/2024

    Srinivasan B, Venkataraman A, Raja SN. Artificial intelligence and pain management: cautiously optimistic. Pain Manag. 2024; 14(7):331-333. PMID: 39259215.

     Read At: PubMed
  • Published on 9/3/2024

    Chen Z, Varkanitsa M, Ishwar P, Konrad J, Betke M, Kiran S, Venkataraman A. A Lesion-aware Edge-based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia. ArXiv. 2024 Sep 03. PMID: 39279836.

     Read At: PubMed
  • Published on 8/22/2024

    Nandakumar N, Hsu D, Ahmed R, Venkataraman A. A DEEP LEARNING FRAMEWORK TO CHARACTERIZE NOISY LABELS IN EPILEPTOGENIC ZONE LOCALIZATION USING FUNCTIONAL CONNECTIVITY. Proc IEEE Int Symp Biomed Imaging. 2024 May; 2024. PMID: 39464200.

     Read At: PubMed
  • Published on 8/19/2024

    Albarqouni S, Baumgartner C, Dou Q, Konukoglu E, Menze B, Venkataraman A. Editorial for the Special Issue on the 2022 Medical Imaging with Deep Learning Conference. Med Image Anal. 2024 Dec; 98:103308. PMID: 39214771.

     Read At: PubMed
  • Published on 12/14/2023

    Ghosal S, Schatz MC, Venkataraman A. BEATRICE: Bayesian Fine-mapping from Summary Data using Deep Variational Inference. bioRxiv. 2023 Dec 14. PMID: 36993396.

     Read At: PubMed
  • Published on 10/1/2023

    Shama DM, Jing J, Venkataraman A. DeepSOZ: A Robust Deep Model for Joint Temporal and Spatial Seizure Onset Localization from Multichannel EEG Data. Med Image Comput Comput Assist Interv. 2023 Oct; 2023:184-194. PMID: 39526288.

     Read At: PubMed
  • Published on 9/14/2023

    Kobayashi Y, Peng YC, Yu E, Bush B, Jung YH, Murphy Z, Goeddel L, Whitman G, Venkataraman A, Brown CH. Prediction of lactate concentrations after cardiac surgery using machine learning and deep learning approaches. Front Med (Lausanne). 2023; 10:1165912. PMID: 37790131.

     Read At: PubMed
  • Published on 7/1/2023

    Wu S, Venkataraman A, Ghosal S. GIRUS-net: A Multimodal Deep Learning Model Identifying Imaging and Genetic Biomarkers Linked to Alzheimer's Disease Severity. Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul; 2023:1-4. PMID: 38083359.

     Read At: PubMed
  • Published on 6/8/2023

    D'Souza NS, Venkataraman A. mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. Inf Process Med Imaging. 2023 Jun; 2023:53-65. PMID: 39469414.

     Read At: PubMed

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