About

Shefali Srivastava is a highly motivated and academically inclined individual currently pursuing her Master's degree in Computer Vision from the Robotics Institute, School of Computer Science at Carnegie Mellon University. She has a strong interest in research in Artificial Intelligence and Computer Vision and is actively seeking internships in Computer Vision, Deep Learning, and Machine Learning for Computer Vision for the summer of 2022. Shefali has a Bachelor of Engineering degree in Information Technology and has worked as a Software Development Engineer in the Digital Marketing division of Adobe Systems. In her current role as a Member of Technical Staff II at Adobe, she is working on the development of a fully automated flow service that allows users to ingest third-party data onto cloud storage. She has also worked on developing a connector service to ingest data from multiple third-party sources onto Adobe Cloud to support data analysis for Adobe Digital Marketing services. She has closely collaborated with ETL vendors on ETL-SDK provided by Adobe to ingest data in Adobe standard XDM format onto Adobe Cloud. She has also implemented a framework for data transfer to One Data Model as part of a cross-company partnership of Open Data Initiative between Adobe, Microsoft, and SAP. Shefali has also worked as a Research Intern at the University of Georgia Franklin College of Arts and Sciences, where she worked on the problem of matching highly disparate image pairs. She developed a deep spectral correspondence scheme for harnessing the representational power of local feature descriptors to derive a complex high-level global shape representation for the task of matching disparate images. She also proposed a benchmark dataset with a large number of image pairs. The proposed scheme enjoys invariance to affine parameters afforded by global shape cues along with robustness to occlusion infused by low-level feature descriptors. Shefali's education history includes a Master's degree in Computer Vision from Carnegie Mellon University, a Bachelor of Engineering degree in Information Technology from NSIT, and a High School degree from Delhi Public School - Dwarka, where she scored 96%. She has a strong tech stack that includes Computer Vision, Software Engineering, Research Science, ETL, Deep Learning, and ML. With a relevant experience of 3.85 years, Shefali is a valuable addition to any team.