Kunal Burgul is a data scientist with 8 years of experience applying machine learning, deep learning, and computer vision to real-world engineering problems, currently at ParallelDots in Hyderabad. He has led a defense-funded project to detect hardware Trojans in PCB X-ray images, owning data acquisition, image stitching improvements, feature engineering, and EDA using Python tooling like NumPy, Pandas, and Scikit-learn. His background spans research roles and production-focused work, with hands-on model building and serving using TensorFlow, PyTorch, and Keras, plus practical systems experience deploying MongoDB and securing data partitions. Kunal combines academic rigor—WorldQuant and Udacity trainings in applied data science and NLP—with a pragmatic engineering mindset, often bridging hardware imaging pipelines and ML stacks to deliver deployable solutions.
8 years of coding experience
3 years of employment as a software developer
Applied Data Science Module I and II, Applied Data Science Module I and II at WorldQuant University
Nanodegree, NLP Foundation, Nanodegree, NLP Foundation at Udacity
Bachelor of Engineering - BE, Computer Science, Bachelor of Engineering - BE, Computer Science at Walchand Institute of Technology, Solapur
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