Dharani Vasantha Kumar

Detail-oriented and diversely skilled specialist in Data science and healthcare domain with 7 years of experience offering expertise in problem-solving, data analysis and customer service. Focuses with data-driven and technology-focused approach. Communicates clearly with stakeholders and builds consensus around well-founded models. As a specialist in data science, confident and knowledgeable in Machine learning, generative AI, process validation and business need analysis while updating the latest technology. Areas of healthcare expertise includes Medical Device specialization, procurement and project management, ISO standards, Quality Management systems, R&D promoting technical excellence in the field of Biomedical and Bioengineering. Adept at learning new technologies and processes for driving success. Proven track record of successfully managing multiple projects and developing innovative solutions.

Azure Machine Learning - Mindtree

• Awarded with the "Star Excellence award for Q3" through effectively maintaining QMS in Medtronic.
• Received the "Best performer" badge for 7 consecutive months out of 11 months post training for complaint handling in Medtronic.
• Specially recognized for the procurement of Radiation Oncology equipment in AIMS, Kochi for detailed Research study and documentation.
• Received scholarship during Post-Graduation and Under-graduation for securing the top academic score.
• Has been awarded the "The Best Paper Award" for the presentation of Paper on "A Non-Invasive NIR Sensor for Urinary Bladder Fullness Detection" in the National Conference JCECON’15 at Chennai

• Training: Philips Healthcare Systems, Chennai: (05/2016 – 07/2016)
• Internships: Global Hospitals and Healthcity, Chennai & Apollo Specialty Hospitals, Chennai: (06/2013 – 06/2013)
• Hospital Visits: Sankara Nethralaya, Chennai (2014)
• Hospital Training: Dr. Kamakshi Memorial Hospital, Adyar Cancer Institute, Tagore Medical College & Hospital, Chennai (2014)

Publication Title: Improved Microaneurysm Detection in Fundus Images For Diagnosis Of Diabetic Retinopathy

Author(s): DHARANI V guided by LAVANYA R

Published date: 27th September, 2017

Publisher: Advances in Signal Processing and Intelligent Recognition Systems - Springer, Cham 

Link:  https://link.springer.com/chapter/10.1007/978-3-319-67934-1_17 

Project Description: Developed a Computer-Aided Diagnosis (CAD) system for early detection of diabetic retinopathy (DR) using digital fundus photography (DFP). The proposed CAD system is intended for detection of microaneurysms (MA) which are the earliest indicators of DR; CAD systems for MA detection involve two stages: coarse segmentation for candidate MA detection and fine segmentation for false positive elimination. The proposed method has been validated using a set of 20 fundus images from the DIARETDB1 database. The Free Response Operating Characteristics (FROC) curve was demonstrated for the proposed system.