abhinav anurag

Abhinav Anurag has a diverse range of work experience in various roles and companies. In 2013, during their education at BITS Pilani, they worked as a Founding Engineer for various startups, including Techture, Knowledge Ashram, and Cocociti. In 2014, they became a Web Team Member for the CodeChef BITS Pilani Campus Chapter, where they developed and hosted web events and assisted other associations with web applications. Abhinav also served as the Webmaster for the Association For Computing Machinery, BITS Pilani Chapter, from 2014 to 2015, where they were responsible for designing the chapter website. In 2015, they participated in the Google Summer of Code (GSoC) as a Student for Sugar Labs, implementing WebSocket solutions for a Real-time Collaborative Learning Platform for Kids. Abhinav also served as the Projects Coordinator for the Google Developers Group from 2014 to 2015, mentoring members in developing applications and projects across various computer fields. In 2015, they started working at HERE Technologies as a Senior Software Engineer, focusing on projects related to Record Deduplication and utilizing Java 8. From 2016 to 2018, they transitioned to the role of Software Engineer at HERE Technologies, where they gained experience with heavy-load REST services using Apache Spring and AWS services, as well as batch processing using MapReduce and Apache Spark. Abhinav then took on the role of Lead Backend Engineer at BitClass starting in 2020 and is currently serving as the Co-Founder and CTO of Schmooze since 2021.

Abhinav Anurag completed their education from 2000 to 2012 at Loyola High School, where they obtained their Intermediate degree. Following that, they attended the Birla Institute of Technology and Science, Pilani from 2012 to 2016, earning their Bachelor of Engineering (BE) degree. Additionally, they obtained two certifications: "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" from Coursera Course Certificates in May 2020, and "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" from Coursera in December 2017.