Archana Venkataraman

John C. Malone Assistant Professor 

Primary Appointment: Electrical and Computer Engineering

Research Interests

  • Functional Neuroimaging (fMRI, EEG)
  • Machine Learning & Probabilistic Inference
  • Network Modeling of the Brain
  • Integration of Imaging, Genetics and Behavioral Data

Archana Venkataraman, the John C. Malone Assistant Professor of Electrical and Computer Engineering, develops new mathematical models to characterize complex processes within the brain. She is core faculty in the Malone Center for Engineering in Healthcare, which aims to improve the quality and efficacy of clinical interventions, and she is affiliated with the Mathematical Institute for Data Science.

Venkataraman’s lab, the Neural Systems Analysis Laboratory (NSA Lab), concentrates on building a comprehensive and system-level understanding of the brain by strategically integrating computational methods, such as machine learning, signal processing and network theory, with application-driven hypotheses about brain functionality. Based on this approach, Venkataraman and her team aim toward a greater understanding of debilitating neurological disorders, with the long-term goal of improving patient care.

Current research projects include a National Science Foundation-supported plan to detect subsystems in the brain that are altered in the presence of a neurological disorder. This work takes a new look at brain pathology by trying to link the heterogeneous clinical manifestation of a neurological disorder to altered neural communication patterns in functional neuroimaging data. The project team includes researchers at the Kennedy Krieger Institute and the Lieber Institute for Brain Development. In addition to the mathematical framework, the project will address key clinical questions related to three of the most prevalent neurodevelopment disorders: autism, ADHD and schizophrenia.

Another research focus is epilepsy management. Epilepsy, one of the most prevalent neurological disorders, is resistant to medication in 20 to 40 percent of cases. Alternative therapies hinge on neurologists being able to detect and localize epileptic seizures in the brain. The NSA Lab is currently developing model-based techniques to automate this process and improve patient outcomes.

Venkataraman is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the MICCAI (Medical Image Computing and Computer Assisted Intervention) Society. She is a recipient of a CHDI Foundation grant on network models for Huntington’s Disease, the MIT Lincoln Lab campus collaboration award, the NIH Advanced Multimodal Neuroimaging Training Grant, the National Defense Science and Engineering Graduate Fellowship, the Siebel Scholarship and the MIT Provost Presidential Fellowship.

Venkataraman is a reviewer for the journals IEEE Transactions on Medical Imaging, Medical Image Analysis, NeuroImage, NeuroImage: Clinical, and PLoS One, as well as for machine learning conferences, such as MICCAI, the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) and the Conference on Information Sciences and Systems (CISS).

Venkataraman studied electrical engineering at the Massachusetts Institute of Technology, where she received her bachelor’s degree in 2006, a master’s degree in 2007 and her PhD in 2012. She completed postdoctoral work at MIT and the Yale School of Medicine before joining the faculty of the Whiting School of Engineering in 2016.

Awards and Honors

2016: Council of Early Career Investigators in Imaging (CECI2) Award

2013: CHDI Grant on Network Models for HD

2012: MIT Lincoln Labs Campus Collaboration Award

2011: NIH Advanced Multimodal Neuroimaging Training Program

2007: National Defense Science and Engineering Graduate Fellowship (NDSEG)

2007: Siebel Scholarship

2006: MIT Provost Presidential Fellowship

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