About

Sharat Chandra Madanapalli is a highly skilled Head of Data Science with expertise in data analysis, applied machine learning, and distributed networked systems. He has developed tools to collect and analyze datasets, drawing insightful observations, and translating these insights into trained AI and Machine Learning models to automate and improve processes and systems. Sharat is well-versed in building distributed back-end systems that scale using programmable networks and technologies like SDN and NFV. Sharat holds a PhD in Computer Science from UNSW Sydney, where his research focused on building data-driven models to understand and improve user's Quality of Experience (QoE) on the internet. He graduated with honors in the top 2% of his class at BITS Pilani, India, with a Bachelor's degree in Computer Science. Sharat has worked as a Data Engineer at Canopus Networks, where he developed data-driven systems that work at scale. He built data pipelines (ETL) by extracting relevant metrics from VNFs, built Machine Learning pipelines to continuously train and deploy models, and analyzed and visualized real-time streaming data to generate valuable insights. As a PhD student at UNSW, Sharat measured, monitored, and managed internet traffic and the associated user-experience by building systems and methods that are scalable and inexpensive. His PhD thesis involved three major contributions: detection and monitoring of internet applications using pattern recognition on network data, inference of the user experience in real-time using statistical modeling and machine learning, and optimizing resource allocation to improve the experience across classes of internet traffic. Currently, Sharat is an Academic Guest at ETH Zurich, where he is working with Prof. Laurent Vanbever's group to investigate ways to use programmable packet scheduling to improve QoE of Internet applications. Sharat's tech stack includes Data Science, ML, AI, Data Engineering, Backend, and ETL. With 4.29 years of relevant experience, Sharat is a highly skilled and accomplished Data Scientist with a passion for developing innovative solutions that drive business success.