About

Aaditya Asati is an experienced Data Science Researcher with over five years of experience in the field. He has a strong background in machine learning, deep learning implementation, Mechatronics, Robotics, virtual reality, and Automation Engineering. Aaditya has a demonstrated history of solving industrial problems with state-of-the-art techniques. Currently working as a Data Scientist at Jio, Aaditya has previously worked as a Researcher at TCS Research & Innovation, where he developed algorithms for assembly area segmentation using Pointnet++ network. He also implemented a Gaussian mixture regression-based algorithm for controller action in assembly and designed a multi-object handling gripper for handling various packages of different shapes and sizes. Aaditya also developed a pybullet environment to test the algorithms with vision and force feedback. Before joining TCS, Aaditya worked at Subros as an Industrial Engineer. Here, he learned about the working HVAC systems and manufacturing processes involved in the components of an HVAC system. He contributed to removing production waste by finding bottlenecks and streamlining production lines. Aaditya also implemented the KAIZEN workshop for encouraging improvements on the lines by the line engineers and implemented energy-efficient methods for material movements across the lines. Aaditya holds a Master of Technology (M.Tech.) focused on machine learning, deep learning implementation, Mechatronics, Robotics, virtual reality, and Automation Engineering from Indian Institute of Technology, Patna, and a Bachelor of Technology (BTech) in Mechanical Engineering from National Institute of Technology Silchar. Aaditya is proficient in several programming languages and tools, including Python, SQL, Keras, Seaborn, OpenCV, Scikit, Tensorflow, Hadoop, and Postgres. He has also worked on several machine learning techniques, including Neural Networks, Search, SVM, Random Forest, and Computer Vision. With his extensive experience and expertise, Aaditya is a valuable asset to any team looking to solve complex industrial problems using machine learning and deep learning techniques.