Arvind Singh Chandel
About Arvind Singh Chandel
Arvind Singh Chandel is a Senior Machine Learning Engineer specializing in research and development, currently working at STL - Sterlite Technologies Limited. He has extensive experience in deep learning, video analytics, and big data technologies, with a strong academic background in machine learning and computer science.
Current Role at Sterlite Technologies
Arvind Singh Chandel serves as a Senior Machine Learning Engineer in the Research and Development department at Sterlite Technologies Limited (STL) since 2022. His role involves developing machine learning models and leveraging advanced technologies to enhance the company's research initiatives. He is based in Pune, Maharashtra, India, where he contributes to projects that focus on innovative solutions in the field of machine learning.
Previous Experience at Euclid Innovations
Prior to joining Sterlite Technologies, Arvind worked as a Senior Machine Learning Engineer at Euclid Innovations from 2020 to 2022. During his tenure in Bengaluru, Karnataka, India, he utilized OpenCV and deep neural network (DNN) models to convert IP camera video feeds into actionable insights aimed at improving retail profitability. This experience contributed to his expertise in applying machine learning to real-world applications.
Educational Background
Arvind Singh Chandel has a solid educational foundation in machine learning and computer science. He earned his Master’s Degree in Machine Learning from Shri G S Institute of Technology & Science from 2007 to 2010. He also holds a Bachelor’s Degree in Computer Science and Engineering from Northern India Engineering College, which he completed from 2003 to 2007. Furthermore, he is pursuing a Ph.D. in Machine Learning and Deep Learning at OP Jindal University, where he has been a research scholar since 2017.
Research and Projects
Arvind has been involved in various research projects that focus on deep learning applications. He developed a deep learning model to capture live inventory from retail stores, enhancing operational efficiency. Additionally, he conducted a research project aimed at designing and implementing a model to quantify human face acceptability. His work demonstrates a commitment to advancing the field of machine learning through practical applications and research.
Technical Skills and Expertise
Arvind possesses a wide range of technical skills in machine learning and deep learning. He is proficient in various deep architectures, including Vision Transformer (ViT), VGG, Inception, ResNet, and FaceNet. His expertise extends to pose estimation and action recognition technologies, as well as video analytics frameworks such as Deepstream and Gstreamer. He is experienced in utilizing cloud platforms like AWS and GCP for scalable machine learning solutions, and employs ML CI-CT-CD platforms for continuous integration and deployment.