At the end of March, join us in San Francisco for an evening of lightning talks! Stitch Fix & friends from Virta Health, GitHub, & Lineage Logistics presents six short talks ranging from clothing personalization to machine learning reproducibility.

SCHEDULE

6:00 - 6:30 : people arrive
6:30 - 6:35 : Intro
6:35 - 7:20 : talks
* 6:35 - 6:50 : Anna
* 6:50 - 7:05 : Tiferet
* 7:05 - 7:20 : Anahita
7:20 - 7:35 : mingling / break
7:35 - 8:20 : talks
* 7:35 - 7:50 : Erin
* 7:50 - 8:05 : Molly
* 8:05 - 8:20 : Chloe
8:20 - 9:15 : mingling

BIOS & ABSTRACTS

Anna Schneider (Stitch Fix)

Bio: Anna is currently a Manager of Data Science on the Merch Algorithms team at Stitch Fix. Previously she was cofounder & CTO of a nonprofit that reduces the carbon footprint of smart devices.

Talk: Stitch Fix is a personalization company, & in order to send clients something they'll love, it first needs to stock merch that each client will love. Anna will talk about the algorithms her team uses to personalize the inventory assortment.

Anahita Hassanzadeh (Stitch Fix)

Bio: Anahita uses her optimization background to solve operations problems at Stitch Fix. Prior to Stitch Fix, she worked on digital agriculture & retail revenue management.

Talk: Anahitas talk is about Stitch Fixs unique styling operations problems. Shell talk about Stitch Fixs approach for choosing the right day to style a clients Fix & the right stylist for the clients particular aesthetic.

Erin Boyle (Stitch Fix)

Bio: Erin is a data scientist on the Stitch Fix AI Instruments team.

Talk: Erins talk will discuss modeling & interpreting the latent style preferences of Stitch Fix clients. It will also comment on the value of modular data products to benefit & align a growing company.

Molly Davies (Virta Health)

Bio: Molly Davies is a data scientist at Virta Health & a recent Stitch Fix Algorithms team alum.

Talk: Mollys talk will share an approach to variable importance that works well with a wide range of machine learning algorithms & makes it easy to compare binary & continuous variables to each other.

Tiferet Gazit (GitHub)

Bio: Tiferet develops machine learning algorithms at GitHub, & is passionate about the positive impact that AI can have on society. She currently engineers deep learning solutions to problems in NLP & semantic understanding of source code, & previously worked in medical computer vision.

Talk: How can we democratize access to software development? This talk will discuss how machine learning can bridge the gap between natural language & code, empowering everyone to reap the benefits of computing.

Chloe Mawer (Lineage Logistics)

Bio: Chloe Mawer is a Principal Data Scientist at Lineage Logistics, the largest temperature-controlled warehouse owner & operator in the world & responsible for storing a third of the US food supply. She is also an adjunct lecturer at Northwestern University, where she teaches future data scientists what they need to know to take a machine-learning-based solution from proof of concept to production.

Talk: In this talk, Chloe will cover the ingredients necessary for developing reproducible machine learning models, which will enable effective & speedy deployment, allow for team members to build on & leverage your work, & make life easier for your future self.