In a world where big data is continuously touted as "the new oil" and U.S. companies are shutting their websites down rather than following increased European privacy rules, why should we care or worry about privacy? Is privacy dead? If not, should we work to preserve it? In this talk, we'll dive into privacy for data science and why ensuring privacy for machine learning contributes to creating more ethical and fair models. We'll dive into research related to fair-and-private machine learning algorithms and privacy-preserving models, showing that caring about privacy and working to preserve user privacy in your machine learning workflows can help ensure a better model overall and support a more ethical product design.

In the evening keynote for QCon.ai, Dr. Sengupta discusses the future of transportation with an eye towards how machine learning and AI will help shape our future. 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.