Where I express personal thoughts in words
Carl Gold, the Chief Data Scientist at Zuora, has a Ph.D. from the California Institute of Technology and first-author publications in leading Machine Learning and Neuroscience journals. Before coming to Zuora, he spent most of his post-academic career as a quantitative analyst on Wall Street. Now a data scientist, Carl has written a book about using insights from data to reduce customer churn, to be released in December 2020 entitled "Fighting Churn With Data."
Jessie J. Smith (Jess) is a second-year Ph.D. student in the Department of Information Science at the University of Colorado Boulder. Her Ph.D. research focuses on AI ethics, machine learning fairness and bias, and ethical speculation in the computer science classroom. Since receiving her Bachelor's in Software Engineering, Jess works to engage in public scholarship about her research to encourage transparency and interdisciplinary dialogue about technology's unintended consequences. She is also the co-host and co-creator of The Radical AI Podcast.
Luis Serrano is a Quantum AI Research Scientist at Zapata Computing. He is the author of the book Grokking Machine Learning and maintains a popular YouTube channel to explain machine learning in pedestrian terms. Luis has previously worked in machine learning at Apple and Google, and at Udacity as the head of content for AI and data science. He has a Ph.D. in mathematics from the University of Michigan, a master's and bachelor's from the University of Waterloo, and worked as a postdoctoral researcher in mathematics at the University of Quebec at Montreal.
Frank Kane is the owner of Sundog Education, teaching machine learning and data science online to over 500,000 students worldwide. Before Sundog, Frank spent nine years at Amazon as a senior engineer and senior manager, specializing in recommender systems and running IMDb's engineering department. Frank also worked in the early days of video game development, dating back to the adventure games of Sierra Online in the early '90s, and has also developed computer graphics software for flight simulators and military simulators around the world. Today Frank is focused on the world of online education, living in the Orlando Florida area with his family.
Amita Kapoor is an Associate Professor in a college at the University of Delhi. She has 20+ years of teaching experience. She is the co-author of various best-selling books in the field of Artificial Intelligence and Deep Learning. A DAAD fellow, she has won many accolades, with the most recent Intel AI Spotlight award 2019 in Europe. As an active researcher, she has more than 50 publications in international journals and conferences. She is extremely passionate about using AI for the betterment of society and humanity in general.
Shreya Shankar is a computer scientist living in the Bay Area. She is interested in making machine learning work in the real world. She currently works at Viaduct — an applied machine learning startup — but most recently, she researched at Google Brain. She graduated from Stanford University with a B.S. in computer science, concentrating on systems. She's finishing her M.S. in computer science, concentrating on artificial intelligence.
One of the best virtual conferences that I attended over the summer is Spark + AI Summit 2020, which delivers a one-stop-shop for developers, data scientists, and tech executives seeking to apply the best data and AI tools to build innovative products. I learned a ton of practical knowledge: new developments in Apache Spark, Delta Lake, and MLflow; best practices to manage the ML lifecycle, tips for building reliable data pipelines at scale; latest advancements in popular frameworks; and real-world use cases for AI.
Francesca Lazzeri, Ph.D., is an experienced scientist and machine learning practitioner with over 12 years of academic and industry experience. She is the author of several publications, including technology journals, conferences, and books. She currently leads an international team of cloud advocates and developers at Microsoft, managing an extensive portfolio of customers in the academic/education sector, and building intelligent automated solutions on the Cloud.
Before joining Microsoft, she was a research fellow at Harvard University in the Technology and Operations Management Unit. She is also an advisory board member of the Global Women in Data Science (WiDS) initiative, a machine learning mentor at the Massachusetts Institute of Technology and Columbia University, and an active member of the AI community.
Patricia Thaine is a Computer Science Ph.D. Candidate at the University of Toronto and a Postgraduate Affiliate at the Vector Institute researching privacy-preserving natural language processing, with a focus on applied cryptography. Her research interests also include computational methods for lost language decipherment.
She is the Co-Founder and CEO of Private AI, a Toronto- and Berlin-based startup creating a suite of privacy tools that make it easy to comply with data protection regulations, mitigate cybersecurity threats, and maintain customer trust.
