About

Aayush Agrawal is a highly skilled Senior AI Engineer with over 5 years of experience in the information technology and services industry. He is currently working at Pactera EDGE, where he is responsible for building shrinkage detection for an American Retail company to identify theft. Aayush has used Yolo v5 for product detection and SORT algorithm for tracking the products and getting the total count in the entire transaction. Before his current role, Aayush worked as an AI Engineer at Pactera EDGE, where he developed a Trade Promotion solution for an American food company to predict and optimize sales based on promotions for Spain and the Netherlands market. The core solution uses the Autoregressive Distributed lag model (ADL) to predict sales. He used Genetic Algorithm for optimizing the promotions. The Uplift Sales is split into the following components: Cannibalisation, Competitor Switching, Category Expansion, Retailer Switching, and Category Expansion. Aayush has also worked at Nova IQ as an AI Engineer, where he completed a project on the LineHaul Optimisation problem using Deep Deterministic Policy Gradient (DDPG), which is a state-of-the-art Deep Reinforcement learning method. He also built a model for speech to text for a client working in the defense domain. Aayush is highly skilled in R, Public Speaking, Shell Scripting, TensorFlow, and Analytical Skills. He has a Bachelor of Technology (B.Tech.) focused on Mining Engineering from the National Institute of Technology Raipur. Aayush's tech stack includes AI, TensorFlow, and Reinforcement Learning. He is a strong engineering professional with a demonstrated history of working on complex AI projects.