Panav Setia

Panav Setia is a skilled software engineer with extensive experience in machine learning, full-stack development, and agile methodologies. Starting as a Machine Learning Intern at Seceon Inc. in 2017, Panav developed algorithms that significantly improved statistical calculation speeds and assisted in cyber security efforts. A subsequent internship at Optum involved engineering algorithms to enhance big data query speeds using Scala, Hive, and Spark. At IBM, Panav contributed to the creation of a full-stack SIEM application and utilized Splunk's Machine Learning capabilities for data analysis. Currently, as a Software Engineer at Meta, Panav serves as a Technical Lead, managing a team to build an integrated knowledge graph application that has notably reduced problem diagnosis times. Panav holds a Bachelor of Computer Science from the University of Massachusetts, Amherst.