Principal Investigator
Professional Profile: Dr. Akshara P. Byju is an expert in advanced image processing and deep learning for geospatial analysis. She earned her Ph.D. in Information and Communication Technology (ICT) from the University of Trento, Italy. Her diverse academic background includes an M.Sc. in Geo-informatics from a collaborative program between the University of Twente and the Indian Institute of Remote Sensing (IIRS), and a B.Tech. in Computer Science from the University of Kerala.
Research & Experience: Dr. Byju has an extensive international research footprint, having served as a Visiting Researcher with the Remote Sensing Image Analysis (RSiM) Group at Technische Universität Berlin, Germany. Her professional experience includes roles as an Image Analyst for the New York University Stern Urbanization Project and as a GIS Consultant at the Infrastructure Development Finance Company.
Current Focus: As the Lead of the LHFIC-Earth project, she guides research in learned satellite image compression and task-oriented remote sensing. Her work is dedicated to developing innovative computational methodologies that address real-world challenges in disaster management and urban planning.
Research Fellow
Research Focus: Pioneering research in learned satellite image compression, with a focus on preserving critical regions of interest (ROI) within latent representations. Dedicated to improving the efficiency and utility of geospatial data through advanced computational techniques.
Experience & Background: An experienced Software Developer with over 5 years of industry expertise in intelligence-driven solutions and web-based system development. Holds an M.Tech in Computer Science and Engineering.
Technical Expertise: Proficient in Python, C++, JavaScript, and Node.js. Skilled in deep learning frameworks (PyTorch, TensorFlow, Keras)and geospatial tools like GDAL. Certified in Deep Learning (DeepLearning.AI) and Geodata Processing (IIRS).
Join Our Team: Internship Positions
Internship positions aim at introducing undergraduate and postgraduate students to research. You will be working on Deep Learning / Image compression / Computer Vision using Python. We expect quick learning and hard-working candidates to respond.
Eligibility
Students with a good track record completing 2nd or 3rd year B.Tech/B.E., or 1st year Masters in Mathematics, Statistics, Computer Science, or Signal Processing.
Note: Only students interested in working for more than six months are welcome.
Selection Process
Selection is based on academic track record and aptitude for research. Please mail your resume to begin the process.