A photo of Surya Prasath.

Surya Prasath, PhD

  • Assistant Professor, UC Department of Pediatrics

About

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.

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.

Interests

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

Research Areas

Biomedical Informatics

Publications

A Durable Anatomy with Local Plasticity Enables Normal and Stress Hematopoiesis. Wu, Q; Zhang, J; Johnson, C; Weinhaus, B; Slaughter, A; Valladares-Nuñez, A; Sherman, A; Filippi, M; Vellai Badradoss, SP; Way, SS; et al. Blood. 2021; 138:297-297.

Computational Nuclei Segmentation Methods in Digital Pathology: A Survey. Hayakawa, T; Prasath, VB S; Kawanaka, H; Aronow, BJ; Tsuruoka, S. Archives of Computational Methods in Engineering. 2021; 28:1-13.

Optimal Nonlinear Signal Approximations Based on Piecewise Constant Functions. Diop, EH S; Boudraa, A; Prasath, VB S. Circuits, Systems, and Signal Processing. 2020; 39:2673-2694.

Adaptive total variation L1 regularization for salt and pepper image denoising. Thanh, DN H; Thanh, LT; Hien, NN; Prasath, S. Optik. 2020; 208.

Automatic body mass index detection using correlation of face visual cues. Bidani, S; Priya, RP; Vijayarajan, V; Prasath, VB S. Technology and Health Care. 2020; 28:107-112.

Effects of Distance Measure Choice on K-Nearest Neighbor Classifier Performance: A Review. Abu Alfeilat, HA; Hassanat, AB A; Lasassmeh, O; Tarawneh, AS; Alhasanat, MB; Salman, HS E; Prasath, VB S. Big Data. 2019; 7:221-248.

Multi-Class Segmentation of Lung Immunofluorescence Confocal Images Using Deep Learning. Isaka, S; Kawanaka, H; Aronow, BJ; Prasath, VB S. (2019) 00:2362-2368.

BREAK, MAKE and TAKE: an information retrieval approach. Pranav, A; Rajeshkannan, R; Vijayarajan, V; Prasath, VB S. Sadhana - Academy Proceedings in Engineering Sciences. 2019; 44.

Analysis of a robust edge detection system in different color spaces using color and depth images. Mousavi, SM H; Lyashenko, V; Prasath, VB S. Computer Optics. 2019; 43:632-646.

Systematic review and usability evaluation of writing mobile apps for children. Missen, MM S; Javed, A; Asmat, H; Nosheen, M; Coustaty, M; Salamat, N; Prasath, VB S. New Review of Hypermedia and Multimedia. 2019; 25:1-24.

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