Dr. Snigdha Sen
Senior Assistant Professor, School of Computer Engineering
Professional Summary
Education
PhD, Data Science & Deep Learning
2019–2024
Indian Institute of Information Technology Allahabad
M.Tech, Information Technology
2007–2009
Jadavpur University, Kolkata
B.E., Information Technology
2001–2005
University Institute of Technology, University of Burdwan
Interests
My research sits where machine learning meets large scientific datasets.
Astroinformatics. Sky surveys produce far more objects than can be measured spectroscopically. I develop deep learning models — from scalable neural networks on Spark to interpretable CNN-transformer hybrids — that estimate galaxy redshifts from photometry, handle heavily imbalanced astronomical data, and cluster galaxy images, as well as language models for textual astronomical data.
Explainable AI for space science. I work on making deep models trustworthy for safety-critical settings such as satellite telemetry anomaly detection.
Computer vision and deep learning. With my students I build CNN, U-Net and transformer models for image steganography, medical image segmentation, object detection and video captioning.
Big data and applied AI. I study scalable data processing with Spark and apply machine learning in healthcare, materials science and social good — work that has led to funded projects and patents in emergency-response systems.
I guide 4 doctoral scholars at MAHE, along with M.Tech and B.Tech projects. Students and collaborators interested in these areas are welcome to get in touch.
Astronomical big data processing using machine learning: A comprehensive review
