About

Sharan Chandra is a highly motivated and passionate engineer with a Bachelor's degree in Electronics and Communication Engineering from the National Institute of Technology, Tiruchirappalli. He has a strong desire to learn and explore new technologies, and is always looking for opportunities to tackle complex problems using innovative approaches. Currently, Sharan is a Member of Technical Staff at Oracle, where he works in the Operations Insights team. He has ideated product functionalities for ADDM analytics from the ground up, presented and defended several ideas to top stakeholders in the company, built a new forecasting pipeline for the capacity planning offering from OPSI, and considered costing POVs and product implications among potential customers. He is responsible for analyzing resource usage of databases/hosts across the enterprise, forecasting future demand for resources based on historical trends, comparing SQL performance across databases and identifying common patterns, analyzing AWR statistics for database performance, diagnostics, and tuning across a fleet of databases. Prior to this, Sharan worked as a Summer Intern at Oracle and as a Research Assistant at the National Institute of Technology. He worked on cutting-edge research in the areas of virtual sensors, 5G technology, and wireless communication, and was responsible for innovating, building, and deploying end-to-end solutions using deep learning, generative adversarial networks, reinforcement learning, and computational intelligence (ant colony optimization). As part of the Virtual Sensors project, he devised and wrote a novel heuristic clustering algorithm inspired by ant colonies. Sharan's education history includes a Bachelor of Technology degree in Electronics and Communication Engineering from NIT Tiruchirappalli, as well as secondary education from Maharishi Vidya Mandir Sr. Sec. School and Sir Mutha School (affiliated to CBSE). Sharan's tech stack includes skills such as software engineering, SQL, research science, reinforcement learning, adversarial networks, and deep learning. With 1.35 years of relevant experience, he is a highly skilled and motivated engineer who is always looking for new challenges and opportunities to grow.