Speaker: Anita Sengupta
Dr. Sengupta is an aerospace engineer, rocket scientist, and veteran of the space program. She worked for NASA for 16 years where her engineering projects included her PhD research on developing the ion propulsion system for the Dawn Mission (currently in the main asteroid belt), the supersonic parachute that landed the Curiosity rover on Mars, and the Cold Atom Laboratory an atomic physics facility now on board the International Space Station.
After leaving NASA she led the development of the hyperloop as senior vice president of engineering systems at Virgin Hyperloop, a technology that can enable ground based travel in excess of airline speed. Her current engineering adventure is designing electrified autonomous VTOL air taxis for urban aerial transport, as Chief Product Officer and Vice President of Business Development at Airspace Experience Technologies. As an engineering savvy executive and pilot, she is now leading the mobility solutions for smart cities by eliminating congestion and reducing the carbon footprint of air travel.
Dr. Sengupta received her MS and PhD in Aerospace Engineering from the University of Southern California, where she is also a Research Associate Professor of Astronautics and Space Technology. In her spare time she is an avid pilot, motorcyclist, scuba diver, snowboarder, hiker, long distance runner, and Sci-Fi fan.
Keynote : The Future of Transportation
2019 Tracks
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Groking Timeseries & Sequential Data
Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.
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Deep Learning in Practice
Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.
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AI Meets the Physical World
Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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Solving Software Engineering Problems with Machine Learning
Interesting machine learning use cases changing how we develop software today, including planned topics touching on infrastructure optimization, developer experience, security, and more.
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Predictive Architectures in the Real World
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.