Sirish is a data scientist with a background in Computer Science, Software Engineering, and Statistics. Prior to joining CCL, he was a Biostatistician at West Virginia University (WVU) Heart & Vascular Institute. His work has focused primarily in applying echocardiographic imaging and information with artificial intelligence and machine learning. He has also founded a non-profit organization with a focus on empowerment, healthcare, and education. He has partnered with WVU internal medicine to provide education and training to healthcare professionals in remote and rural areas of Nepal and West Virginia to promote diagnostic capabilities in rural areas using pocket ultrasound and telemedicine.
Sirish enjoys using advanced data analytics techniques and machine learning algorithms to solve complex problems and bring novel ideas in real-world scenarios. He has been involved in assessing vascular diseases using topological data analysis, radiomics technique for feature phenotyping of dysfunctional myocardium, and organizing outreach events utilizing novel digital health technologies in rural West Virginia.
Sirish’s primary focus is on applying machine learning and artificial intelligence into new and existing leadership development efforts. He provides research and advanced analytical support for various internal and external projects. He is interested in bringing novel analytical methods, machine learning, and natural language processing and understading to leadership development.
Areas of Expertise
Topological Data Analysis, Machine Learning, Software Prototyping
M.S. in Statistics from West Virginia University
B.S in Computer Science from Fairmont State University, West Virginia
Select External Publications
- Casaclang-Verzosa, G., Shrestha, S., Khalil, M. J., Cho, J. S., Tokodi, M., Balla, S., Alkhouli, M., Badhwar, V., Narula, J., Miller, J. D., & Sengupta, P. P. (2019). Network Tomography for Understanding Phenotypic Presentations in Aortic Stenosis. JACC: Cardiovascular Imaging, 12(2), 236–248.
- Dey, D., Slomka, P. J., Leeson, P., Comaniciu, D., Shrestha, S., Sengupta, P. P., & Marwick, T. H. (2019). Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review. Journal of the American College of Cardiology, 73(11), 1317–1335.
- Sengupta, P. P., & Shrestha, S. (2018). Machine Learning for Data-Driven Discovery. JACC: Cardiovascular Imaging, 0–2.
- Shrestha, S., & Sengupta, P. P. (2018). The Mechanics of Machine Learning: From a Concept to Value. Journal of the American Society of Echocardiography, 31(12), 1285–1287.