Technical / Research Assistants

Shivani Sawant is a Research Assistant specializing in Medical Image Analysis using Deep Learning. Holding a Master of Science in Statistics from Washington State University and a Bachelor of Engineering in Computer Science from Savitribai Phule Pune University, Shivani brings a unique blend of statistical expertise and technical proficiency to her role. Her primary research interest centers around uncertainty quantification in Convolutional Neural Networks, driven by the aim to enhance the trustworthiness and reliability of deep learning models used in the biomedical domain.

In her current role, she engages in interdisciplinary research by combining mathematics, statistics, computer science and human anatomy to work on statistical shape modelling and building deep learning models for orthopaedic applications, with a focus on femoroacetabular impingement.

Kaustubh Kulkarni received the bachelor’s degree in engineering from Mumbai University, and the MSc degree from Auburn University. He worked at Siemens Research Labs in India and the USA. He was a researcher INRIA, Grenoble, France and Computer Vision Center, Universitat Aut onoma de Barcelona. Following which he worked on the problems of designing speech recognition engines on highly noisy speech data for defence applications. He has experience working in medical image analysis, action recognition, speech recognition, and emotion recognition. At SCMIA, he is working on learning multimodal deep learning models for early detection of Alzheimer's disease.