Jay Buckingham

Jay combines the technical skills of a Ph.D. Machine Learning Scientist with the seasoned maturity from 20+ years in industry. He has delivered data-driven insights and value to Fortune 500 companies and startups across a range of industries. Prior to joining Ars Quanta as Chief Data Scientist, he was the Senior Research Data Scientist at Zignal Labs, helping their enterprise customers understand and reach out to their customers by training neural networks to determine the topics and sentiment of millions of social media, news and blog posts about these enterprise companies. Prior to that he worked on Apple’s autonomous car project as a Research Scientist experimenting with a range of deep learning architectures, training the neural networks to recognize a range of objects in scenes.

His work has focused on creating machine learning systems for pattern recognition, primarily in the domains of image understanding and text classification. He has worked on projects as diverse as developing machine learning systems to detect spam for Microsoft and infer key life events like getting married from social media posts for Hearsay Systems, to detecting important classes of objects in images as Chief Scientist for iComprehend.