Vice President, Machine Learning
Rajendra Koppula is co-founder and VP of Machine Learning at Manifold, where he helps our teams design and architect Machine Learning solutions. He ensures that we build robust, production-scale ML pipelines using best practices and modern technologies, and works to enhance the team’s engineering talent by cultivating a continuous learning culture. He has extensive domain knowledge in the IoT, wireless systems, and medical device spaces. His technical knowledge ranges from open-source tools in the Python ecosystem to cloud technologies like Kubernetes and Spark. Recent ML product successes include a system that can predict song popularity by geography for a public media company, a novel augmented reality experience for a consumer electronics company, and a predictive model of patient outcomes using data from a connected medical device.
Prior to Manifold, Raj was a Staff Engineer in the 3G/4G Cellular Group at Qualcomm, where his work focused on developing statistical and wireless signal processing solutions. Code developed by his team now runs on millions of mobile devices worldwide. Over the course of a decade in that position, he gained a deep technical understanding of mobile and IoT devices—as well as an appreciation for their resource-constrained nature—and learned what it takes to ship products at scale.
Raj has a BE in Electronics and Communication Engineering, and MS degrees in both Electrical Engineering and Statistics from Northern Illinois University. He also holds multiple professional certifications, including the MIT Big Data certification and the USF Fast.ai Deep Learning certification.
|Sensors Expo & Conference||How to Optimize Physical Assets with Machine Learning||Jun. 27
San Jose, CA
|AnacondaCon||Scalable Machine Learning Pipelines with Dask||Apr. 3–5
|AnacondaCon||Lean AI for Predictive Maintenance||Apr. 8–11