About

Siddhant Baldota is a highly skilled computer science graduate student with a passion for deep learning and computer vision. He is currently pursuing his Master of Science in Computer Science at the University of California, San Diego and is a software intern at Maxlinear. Siddhant is also a graduate student researcher at the San Diego Supercomputer Center where he has been working on applying various deep learning and image processing techniques to detect and localize smoke from camera images. Siddhant is proficient in Python, Linux and Bash Programming, C, C++, Java, Git, Pytorch, Tensorflow, Apache MxNet, and developing algorithms. He has also worked as a student researcher at UCL, where he gained experience in computer vision and medical imaging research. In his current role at Maxlinear, Siddhant has optimized XP10 Compression time by exploring redundancies in the existing algorithm by 50%. He has also executed time analysis of XP10 data compression using C and Python. Siddhant's past experience includes working as a graduate student researcher at the San Diego Supercomputer Center, where he worked under Mai H Nguyen and was advised by Prof. Garrison Cottrell. He was responsible for incorporating different data sources to improve precision and recall, investigating methods for efficient training, and analyzing errors for performance improvement and model explainability. Siddhant's tech stack includes software engineering, research science, deep learning, Python, computer vision, image processing, Tensorflow, Pytorch, and Java. He has relevant experience of 0.93 years and is committed to developing his skills and knowledge in the field of computer science.