Summary
Arindam Chowdhury is a researcher and engineer with a PhD from Purdue and eight years of experience applying deep learning, computer vision, and robotics to real-world problems across autonomous driving, medical imaging, and manufacturing automation. Currently at Nissan North America, he focuses on improving 3D lidar point-cloud processing to reliably detect vehicles, bikes, and pedestrians for self-driving decision systems. His background spans industry roles at KLA and Intel and academic projects that delivered high-accuracy segmentation and detection systems (including 93–94% accuracy in pathology and object classification tasks). He has hands-on expertise with Python, C++, TensorFlow, PyTorch, ROS, OpenCV and point-cloud tools, and a track record of translating research prototypes into embedded and production proofs of concept. Notably, he built a low-cost Raspberry Pi–based digital pathology demonstrator and has contributed vision algorithms that enhanced prosthetic and robotic perception in safety-critical settings. Based in Sunnyvale, he blends deep academic rigor with practical engineering to push perception systems toward robust field deployment.
8 years of coding experience
10 years of employment as a software developer
Indian Institute of Technology Madras
High School, High School at Nava Nalanda
Doctor of Philosophy - PhD, Deep Learning, Computer Vision, Robotics and Automation, Doctor of Philosophy - PhD, Deep Learning, Computer Vision, Robotics and Automation at Purdue University
Bachelor of Technology - BTech, Electronics and Communications Engineering, Bachelor of Technology - BTech, Electronics and Communications Engineering at West Bengal University of Technology
English, Hindi, Bengali