iHARP Research Assistant | UMBC Ph.D. Candidate
Email: saivika1@umbc.edu
See me at Google Scholar Citation Page, LinkedIn
Research Interests
- Spatiotemporal Data
- Anomaly detection
- Deep Learning Models
Short Biography
Sai Vikas Amaraneni is a Ph.D. student in Information Systems at UMBC, specializing in machine learning and high-performance computing for climate applications. His research focuses on Antarctic Sea Ice Prediction and studying Sterodynamic effects across U.S. coastal regions.
Research Summary
Sai is currently working on improving sea ice predictions over the Antarctic region using deep learning models. Parallely, he is studying salinity variations across the three US Coastal regions to understand how salinity plays a role in rising sea levels along with temperature. For both works, he is using satellite observations covering more than 15 years. His goal is to validate and improve the accuracy of modeled climate data, enabling him to assist policymakers in making reliable projections.
Publications
- Amaraneni, S. V. (2025, April). Predicting Antarctic Sea Ice Concentration using ConvLSTM. Poster presented at COEIT Research Day, University of Maryland, Baltimore County (UMBC). Recipient of the Doctoral Research Poster Award.
- Amaraneni, S. V., Devnath, M. K., Chakraborty, S., & Janeja, V. (2024, December). Forecasting sea ice extent with a Patch-CNN model: Daily to two-week predictions. Presented at the AGU Fall Meeting, Washington, DC. (Session C14A-06)
Last updated 17 June 2025