About

Arun Kumar Patil is a Principal Engineer specializing in Computer Vision and Machine Learning at Target, with over 16 years of relevant experience. He is a problem solver with a proven track record of building high-quality products in retail analytics, video/image content understanding, and computational photography using machine learning, computer vision, and heterogeneous computing technologies. His work has translated into multiple patents, showcasing his expertise in the field. Currently, Arun is working at Target, where he is solving complex retail problems using computer vision and machine learning algorithms at scale. He is responsible for intelligent image and video dataset creation, model building for different retail use cases, and architecting for large-scale deployment. Prior to joining Target, Arun worked as a Principal Data Scientist at Sharechat, where he was responsible for content understanding and content-based tag prediction and NSFW flagging. He also worked on song-to-lyrics alignment for multiple Indian languages, accurate image segmentation, and beats extraction from music and timed visual response to beats and templatization of the effect. Before Sharechat, Arun worked as a Software Development Manager at Xilinx, where he developed AI kernel Scheduler for heterogeneous compute systems in data centers and contributed to CNN compiler for different FPGA-based inference engines targeted at embedded and data center. He also led the software stack and DNN quantization and retraining for the HLS-based implementation of DNN inference engine on FPGAs. He has open-sourced CHaiDNN, a software library for deep neural network inference on FPGAs. Arun holds a Bachelor's degree in Electronics and Communication from Vishveshwaraiah Technological University. His technical skills include Computer Vision, Machine Learning, Image Segmentation, Data Scientist, Research Scientist, Object Detection, Software Engineer, AI, CNN, and Object Detection. Arun is a highly skilled professional with a passion for solving complex problems using cutting-edge technologies.