Contagion Science Seminar feat. Zane Reynolds (TORC Robotics)
Zane Reynolds is an experienced software engineering leader specializing in software development and machine learning. Currently Head of Data Systems at TORC Robotics, he leads multiple teams and directs the strategy for large-scale data systems, including designing and managing a petabyte-scale AWS Data Lake and developing data pipelines for autonomy development. His background includes managing software development teams at Amazon, delivering features for high-scale distributed services, and architecting ML systems and data tools at Virginia Tech's Biocomplexity Institute. Zane holds an MS in Computer Science from the University of South Florida and is known for building strong teams and driving results.
Title: Data Loops: A Framework for the Continuous Improvement of ML Algorithms
Abstract: Operating complex systems that involve ML algorithms, AI, and even humans requires a feedback loop. Feedback loops are frequently overlooked, but are essential to improving the systems over time. This talk looks at two examples: a data loop for Advanced Driver Assistance Systems (ADAS) and a data loop for software development. We will explore the key components of the loops and practical approaches to building effective data loops that drive measurable improvements in complex systems.
Agenda:
11:00-12:00: Presentation
12:00-1:00pm: Networking Lunch
1:00-4:00pm: Individual Meetings