Presentation: ML/AI Panel

Track: Modern CS in the Real World

Location: Pacific DEKJ

Duration: 2:55pm - 3:45pm

Day of week: Tuesday

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Abstract

This is your chance to hear from the experts: ML platform builders and longtime users. What makes ML different from other types of applications and why does it require special tooling? How did they get started and what tools would they use if they were starting today? Where is the low-hanging fruit and how do they recommend acquiring those initial quick wins? Join us to learn what you should watch out for in the initial stages, while you're still learning core concepts.

Moderator: Michelle Casbon

Speaker: Chris Albon

Director of Data Science @DevotedHealth

I am the Director of Data Science at Devoted Health, using data science and machine learning to help fix America’s health care system. Previously, I was Chief Data Scientist at the Kenyan startup BRCK, cofounded the anti-fake news company New Knowledge, created the data science podcast Partially Derivative, led the data team at the humanitarian non-profit Ushahidi’s, and was the director of the low-resource technology governance project at FrontlineSMS. I also wrote Machine Learning For Python Cookbook (O’Reilly 2018) and created Machine Learning Flashcards.

I earned a Ph.D. in Political Science from the University of California, Davis researching the quantitative impact of civil wars on health care systems. I earned a B.A. from the University of Miami, where I triple majored in political science, international studies, and religious studies.

Find Chris Albon at

Speaker: June Andrews

AI @Stitch Fix

Dr. June Andrews works on AI Instruments at Stitch Fix. Previously, she led building a Monitoring & Diagnostics platform for GE’s airplane engines in use today. The platform has since been extended to turbines in renewable energy and power plants. At Pinterest, June created the Signals Program, a feature store, supporting over 50 ML engineers. At LinkedIn, she supported growth and engagement during a 50% gain in membership. June holds degrees in applied mathematics, computer science, and electrical engineering from UC Berkeley and Cornell. Her hobbies include teaching at Berkeley and serving on advisory boards.

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Speaker: Paige Bailey

Product Manager (TensorFlow) @Google

Paige Bailey is the product manager for Swift for TensorFlow

Prior to her role as a PM in Google Brain, Paige was developer advocate for TensorFlow core; a senior software engineer and machine learning engineer in the office of the Microsoft Azure CTO; and a data scientist at Chevron. Her academic research was focused on lunar ultraviolet, at the Laboratory for Atmospheric and Space Physics (LASP) in Boulder, CO, as well as Southwest Research Institute (SwRI) in San Antonio, TX.

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Speaker: Melanie Warrick

Senior Developer Relations Engineer Company @Google

Melanie Warrick is currenlty at Google driving applied machine learning and Cloud advocacy efforts and servers on the board of the non-profit, Techtonica. She has an extensive career making sense of data working as an engineer and business leader. She implemented machine learning applications at Change.org and built neural net software platform at a start-up. Before becoming a software engineer, she worked for over 10 years in business consulting at firms such as Accenture on projects for Fortune 500 companies and non-profits like CARE and Oxfam. She is driven to solve problems with data and technology and has a passion for including others in the space.

Find Melanie Warrick at

Speaker: Amy Unruh

Staff Developer Relations Engineer @Google Cloud Platform

Amy Unruh is a Staff Developer Relations Engineer for the Google Cloud Platform, where she focuses on machine learning and data analytics, as well as other Cloud Platform technologies. Amy has an academic background in CS/AI, and has also worked at several startups, done industrial R&D, and published a book on App Engine.

Find Amy Unruh at

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Tracks

Monday, 11 November

Tuesday, 12 November

Wednesday, 13 November