About

Anurag Syal is a highly skilled Computer Vision and Machine Learning professional with over 6 years of relevant experience in the field. He holds a Master of Science in Electrical Engineering from the University of Southern California, Los Angeles. Anurag is a quick and analytical learner with a detail-oriented approach to Machine Learning applications development. He has hands-on experience with the Machine Learning Engineering tech stack, including Pytorch, TensorFlow, Keras, Caffe, OpenCV, Pandas, Numpy, scikit-learn, and others. Anurag has a working knowledge of deploying ML models on-cloud using AWS, Docker, AirFlow, and others, as well as on-device using Swift (iOS) and C++. He loves to code with an insatiable desire to learn more and has 1+ year of working knowledge on Unity3D (C#). Anurag has 3+ years of experience in Data Science and Data Analytics. Currently, Anurag is working as a Lead Machine Learning Engineer at aedit, where he has developed a hybrid deep learning algorithm to predict product pose in Wayfair images. He has achieved categorical accuracy of 74.6% for 8-Zone angle class prediction and an accuracy of 64% in top-22.5° for regressed value of angle. Anurag has also liaised with stakeholders to identify high revenue and high volume Wayfair products, identified deliverables, pipeline, and high-risk items. He has augmented the training dataset by generating synthetic data using 3D models of selected products by scripting in 3DS MAX, reducing dependency on offshore resources and tagging time by 60%. Anurag has engineered software pipeline for automatic tagging and ad-hoc tagging of new images, reducing turn-around time from 4 weeks to 2 days. Anurag has previously worked as a Machine Learning Engineer at Wayfair and as a Computer Vision Engineer at USC Viterbi School of Engineering. At Wayfair, he developed a hybrid deep learning algorithm to predict product pose in Wayfair images, augmented the training dataset, and engineered software pipeline for automatic tagging and ad-hoc tagging of new images. At USC Viterbi School of Engineering, Anurag implemented an Augmented Reality (AR) Sandbox in Unity, where he was responsible for terrain-mapping, projector-camera calibration, 3D point cloud projection mapping, and making the project Unity-compatible. Anurag's tech stack includes ML