Harish RaviPrakash

I'm a PhD student at the Center for Research in Computer Vision, University of Central Florida working with Dr. Ulas Bagci. My primary area of research is medical image analysis, focusing on brain image analysis. Other research interests include deep learning, survival prediction, object segmentation. 

EXPERIENCE

July 2019 - 

Pre-doctoral Fellow

National Institutes of Health Clinical Center

Working on identifying functional differences in epilepsy patients using task based fMRI.

Oct 2014 - July 2015

Internship

GroboMac

Developed an algorithm to detect cotton in farms. Constructed a stereo-vision setup to return the position of the detected cotton for a robotic arm to extract in real-time. 

Jun 2014 - Sep 2014

Internship

Kaybus

Worked to develop a text detection algorithm for Document Images. We developed an algorithm to detect Text lines using Haar DWT and used Tesseract OCR to extract the text from the image. Also tested HOG based approach to detect text lines in images.

Sep 2012 - Aug 2013

Research Assistant

Rensselaer Polytechnic Institute

1. Worked with Dr. John W. Woods to develop a Rate Allocation Algorithm for MDFEC. In this project we developed an algorithm to optimize non-convex SVC encoder data for optimal rate allocation.

2. Worked on National Science Foundation (NSF) Grant CNS - 1018398, "NeTS : Flexible Delivery of Streaming Video using Network-Aware MD-FEC Coding.

EDUCATION

Aug 2015-

PhD

University of Central Florida

Department of Computer Science

Advisor: Dr. Ulas Bagci

Thesis focusing on multimodal multi-dimensional brain image analysis

 Jan 2011-Dec 2011

Master of Science

Rensselaer Polytechnic Institute

Department of Electrical, Communications & Systems Engineering.

Advisor: Dr. John W. Woods

Thesis focused on Image denoising via Non-local Wiener filter.

2006-2010

Bachelor of Engineering

M.S. Ramaiah Institute of Technology

Department of Telecommunications Engineering 

UPDATES

• Guest lecture on machine learning  based MRI image analysis techniques. (Medical Image Computing (CAP 5516), Spring 2019)

• Invited talk at the Brain Awareness Symposium, UCF 2018.

• Awarded Certificate of Merit RSNA 2017

• Nominated for BCI Award 2017: Gold Standard for epilepsy/tumor surgery coupled with deep learning offers independence to a promising functional mapping modality.

• Nominated for Best Student Paper Award IEEE SMC 2017

• Nominated for Best Conference Paper Award IEEE SMC 2017

• Guest lecture on MRI and fMRI modalities and their associated pre-processing techniques. (Medical Image Computing (CAP 5937), Spring 2017)

• Florida Hospital Research Forum 2017: Poster

PUBLICATIONS

• "Deep Learning provides exceptional accuracy to ECoG-based Functional Language Mapping for epilepsy surgery." Harish RaviPrakash, Milena Korostenskaja, Eduardo Martinez Castillo, Ki Hyeong Lee, Christine Maria Salinas, James Baumgartner, Syed Muhammad Anwar, Concetto Spampinato, and Ulas Bagci.  Frontiers in Neuroscience, 2020.

• "A Survey on Recent Advancements for AI Enabled Radiomics in Neuro-Oncology." Syed Muhammad Anwar, Tooba Altaf, Khola Rafique, Harish RaviPrakash, Hassan Mohy-ud-Din, and Ulas Bagci. Radiomics and Radiogenomics in Neuro-oncology, 2020.

• "Computerized Analysis of Brain MRI Parameter Dynamics in Young Patients With Cushing Syndrome—A Case-Control Study." Amit Tirosh, Harish RaviPrakash, Georgios Z. Papadakis, Christina Tatsi, Elena Belyavskaya, Lyssikatos Charalampos, Maya B. Lodish, Ulas Bagci, and Constantine A. Stratakis. The Journal of Clinical Endocrinology & Metabolism 105, no. 5 (2020): dgz303.

• "Gold standard for epilepsy/tumor surgery coupled with deep learning offers independence to a promising functional mapping modality." Milena Korostenskaja, Harish Raviprakash, Ulas Bagci, K. H. Lee, P. C. Chen, C. Kapeller, Christine Salinas, Michael Westerveld, A Ralescu, J Xiang, James Baumgartner. In Brain-Computer Interface Research, pp. 11-29. Springer, Cham, 2019.

• "Deep Learning for Functional Brain Connectivity: Are We There Yet?" Harish RaviPrakash, Arjun Watane, Sachin Jambawalikar, and Ulas Bagci. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, pp. 347-365. Springer, Cham, 2019.

• "Virtual Radiologists: Current Status of Deep Learning in Radiology and Its Future Trends" Sarfaraz Hussein, Aliasghar Mortazi, Harish RaviPrakash, Naji Khosravan, George .Z. Papadakis, Uygar Teomete, Ulas Bagci. Annual Meeting of the Radiological Society of North America (RSNA) 2018. 

• "Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks" Burt, Jeremy R., Neslisah Torosdagli, Naji Khosravan, Harish RaviPrakash, Aliasghar Mortazi, Fiona Tissavirasingham, Sarfaraz Hussein, and Ulas Bagci. The British journal of radiology 91, no. xxxx (2018): 20170545

• "Deep Learning Applications in Radiology: Recent Developments, Challenges and Potential Solutions" Sarfaraz Hussein, Aliasghar Mortazi, Harish RaviPrakash, Jeremy R. Burt, Ulas Bagci. Annual Meeting of the Radiological Society of North America (RSNA) 2017. 

• "Automatic Response Assessment in Regions of Language Cortex in Epilepsy Patients Using ECoG-based Functional Mapping and Machine Learning" Harish RaviPrakash, Milena Korostenskaja, Ki Lee, James Baumgartner, Eduardo Castillo, Ulas Bagci. IEEE International Conference on Systems, Man and Cybernetics (IEEE SMC) 2017.

• "Deep Learning in Radiology: Recent Advances, Challenges and Future Trends" Sarfaraz Hussein, Harish RaviPrakash, Uygar Teomete, Ulas Bagci. Annual Meeting of the Radiological Society of North America (RSNA) 2016.

COURSES