I am an Assistant Professor at the Department of Computational and Data Sciences (CDS) , Indian Institute of Science (IISc), Bangalore. 

I am the convenor of Biomedical image Analysis (BioMedIA) laboratory at CDS, IISc.

Prior to this, I was working as a postdoctoral research fellow at Athinoula A. Martinos Centre, Department of Radiology, Harvard Medical School and Massachusetts General Hospital. I received my doctorate degree at FMRIB, Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford. 

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EXPERIENCE

Assistant Professor (2022 – present) 

• • Department of Computational and Data Sciences, Indian Institute of Science, India

Postdoctoral Research Fellow 

• • Athinoula A. Martinos Centre, Massachusetts General Hospital and Harvard Medical School, United States

Postdoctoral Researcher 

• • Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford, United Kingdom

DPhil (PhD) in Biomedical Imaging 

• • FMRIB, Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, United Kingdom

     M.S. in Electrical Engineering 

• • Indian Institute of Technology Madras (IITM), India

FELLOWSHIPS / AWARDS

India Alliance DBT-Wellcome Trust Early Career Fellowship (2024-2028)

Project title: Development and evaluation of Imaging-based biomarkers for quantitative         assessment of Vascular Cognitive Impairment using Artificial Intelligence

Pratiksha Trust Young Investigator Award (2023-2025)

Oxford Indira Gandhi Graduate Scholarship (2018 - 2019)

Awarded by Somerville College, University of Oxford, UK.

     Awarded to up to 3 Indian students annually to pursue graduate studies at the University

of oxford.

Prem-Suki Foundation Scholarship (2015 - 2018)

Awarded by Somerville College, University of Oxford, UK.

Awarded to an Indian student annually to pursue graduate studies in Biomedical/Healthcare

sciences at University of  Oxford.

Guarantors of Brain Travel Award (2019, 2017)

Awarded by Organisation for Human Brain Mapping (OHBM) board for attending Annual

meetings of OHBM at Vancouver in 2017 & Italy in 2019.

Best poster Award (2018)

Won for poster titled "Improvements in the white Matter Hyperintensities Detection Algoithm 

using local adaptive threshold" at the Wellcome centre integrative neuroimaging

Neurodegeneration Day, University of  Oxford, UK.

• DS 216 (JAN-APR): Machine learning for data science: Course webpage 

• DS 216o (JAN-APR): Applied AI in Healthcare

• DS 261 (AUG-DEC): AI for medical imaging

• DS 261o (JAN-APR, online): AI for medical imaging

• Sundaresan, V.*, Arthofer, C., et al, “Automated Detection of Cerebral Microbleeds on MR images using Knowledge Distillation Framework.” Frontiers in Neuroinformatics, 17, p.1204186. (2023) [Paper]

• Sundaresan,V.*, Dinsdale,N.K., Jenkinson,M. & Griffanti,L. Omni-supervised domain adversarial training for white matter hyperintensity segmentation in the UK Biobank. International Symposium on Biomedical Imaging, 2022. ISBI 2022. 1-4 IEEE (2022). *Shared first authorship. [Paper]

• Dinsdale, N.K.*, Bluemke, E., Sundaresan, V. et al. Challenges for machine learning in clinical translation of big data imaging studies. Neuron (2022). [Preprint  /  Paper]

• Sundaresan, V.* et al.Automated Detection of Candidate Subjects with Cerebral Microbleeds using Machine Learning. Front. Neuroinform. 15, 80 (2022). [Paper]

• Sundaresan,V.* et al. Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images. Med Image Anal. 74, 102215 (2021). [Paper]

• Sundaresan,V.*, Zamboni,G., Rothwell,P.M., Jenkinson,M., & Griffanti,L. Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images. Med Image Anal. 73, 102184 (2021). [Paper]