A photo of Surya Prasath.

Assistant Professor, UC Department of Biomedical Informatics

513-636-2755

Biography & Affiliation

Biography

Surya Prasath, PhD, is a mathematician with expertise in the application areas of image processing and computer vision. He received his PhD in mathematics from the Indian Institute of Technology Madras, India in 2009 (defended in March 2010). He has been a postdoctoral fellow at the Department of Mathematics, University of Coimbra, Portugal, for two years. From 2012 to 2017 he was with the Computational Imaging and VisAnalysis (CIVA) Lab at the University of Missouri, USA and worked on various mathematical image processing and computer vision problems. He had summer fellowships/visits at Kitware Inc. NY, USA, The Fields Institute, Canada, and IPAM, University of California Los Angeles (UCLA), USA. His main research interests include nonlinear PDEs, regularization methods, inverse and ill-posed problems, variational, PDE based image processing, and computer vision with applications in remote sensing, biomedical imaging domains.

Research Interests

Image processing; computer vision; biomedical image analysis; machine learning

Academic Affiliation

Assistant Professor, UC Department of Biomedical Informatics

Department

Biomedical Informatics

Education

BSc: Mathematics, University of Madras, India, 1999-2002.

MSc: Mathematics, Indian Institute of Technology Madras, Chennai, India, 2002-2004.

PhD: Mathematics, Indian Institute of Technology Madras, Chennai, India, 2004-2009.

Postdoc: Mathematics, University of Coimbra, Portugal, 2009-2011.

Postdoc: Computer Science, University of Missouri-Columbia, Columbia, MO, 2012-2015.

Publications

Deep learning based computer-aided diagnosis for neuroimaging data: focused review and future potential. Prasath, VB S. Neuroimmunology and Neuroinflammation. 2018; 5:2-4.

Measuring Bone Density Connectivity Using Dual Energy X-Ray Absorptiometry Images. Chen, L; Prasath, VB S. International Journal of Fuzzy Logic and Intelligent Systems. 2017; 17:235-244.

Enhanced Multi-View Point Non-Negative Matrix Factorization Clustering for Clinical Documents Analysis. Sharma, D; V., V; Kubendiran, M; R., P. Biomedical and Pharmacology Journal. 2017; 10:2135-2143.