Gabriel Bianconi

Unknown

Bio

Gabriel is a machine learning scientist with experience in applying cutting-edge academic research to solve real-world problems.

He began his training as a B.S. & M.S. student in computer science at Stanford University, where he received multiple academic distinctions, including the President’s Award for Academic Excellence.

He was one of ten students to graduate with honors in computer science in his undergraduate class at Stanford. His thesis investigated quantum deep learning algorithms using NASA’s D-Wave quantum computer, and was selected for a presentation at the AQC 2017 Conference in Tokyo, Japan.

During his master’s program, he conducted research at the Stanford Partnership in AI-Assisted Care, a joint lab between the Stanford Computer Science Department (Prof. Fei-Fei Li – Chief Scientist of Cloud AI/ML at Google) and the Stanford School of Medicine (Prof. Arnold Milstein). His research focused on improving clinical care and reducing monitoring costs in hospitals by leveraging machine learning and computer vision, and resulted in a first-author manuscript selected as Top 10 Research Paper at the NIPS Machine Learning for Health 2017 Workshop.

Gabriel also has extensive software engineering experience. At Google and Facebook, he worked on backend infrastructure for enterprise tools responsible for billions of dollars in revenue. He’s also created an advertising supply-side platform that handled millions of ad requests per day, built an algorithmic trading platform and quantitative strategies for cryptoasset markets that handled over US$10M in volume, and held positions at startups and investment firms.