SDM Conference 2021

Data Science for Retail and E-Commerce Workshop

May 1 (Virtual)


Wai Gen Yee

Head of Data Science, Grubhub

Wai Gen Yee is the former Head of Data Science at Grubhub and focuses on Martech (Marketing Technology), specifically email marketing, paid search, and paid social. He also has several collaborations across different company functions, such as Finance and Technology. Prior, he was Chief Data Scientist at Sears, focusing on pricing and promotion strategies. He was also Chief Scientist at Orbitz Worldwide, where he built the machine learning and personalization function. He received his Ph.D. from Georgia Tech.

Experience in Upper and Middle Sales Funnel Optimization Using Lift Modeling and Embeddings

This talk covers two trendy techniques in improving e-commerce performance - neural network embeddings and lift modeling. It will describe how they were applied in e-commerce for search result ranking and email marketing to drive significant business improvement.

Vineet Abhishek


Vineet Abhishek manages the machine learning team for Snapchat ads ranking. Previously he co-founded an AI startup (, Alchemist Accelerator class 18), led product search ranking and A/B testing at Walmart Labs, and architected algorithmic bidding for sponsored ads campaigns at Adchemy (acquired by Walmart Labs). He holds a Ph.D. from the University of Illinois at Urbana-Champaign, M.S. from Stanford University, and B.Tech from IIT Kanpur (India).

Learnings from deep learning for Snapchat Ads

The nuances of deep learning training dynamics, ad auction selection bias and ever-changing ad inventory have shaped Snapchat machine learning model evolution for ads ranking. We share key learnings from training, A/B testing, debugging and deploying hundreds of large scale deep learning models.

Alessandro Magnani

Distinguished Data Scientist, Walmart Labs

Computer Vision in E-commerce

In e-commerce product content, especially product images have a significant influence on customer journey from product discovery to evaluation and final purchase decision. With the recent advances of AI powered by GPUs, Walmart has invested in infrastructure and best practices geared toward improving the customer experience for E-commerce. In this talk, we will show applications of computer vision in E-commerce. Specifically, we will discuss product classification, attribute extraction, content filtering, asset optimization, and visual search and recommendation.


10:30 AM EST


Faizan Javed
10:35 AM EST

Keynote 1

Experience in Upper and Middle Sales Funnel Optimization Using Lift Modeling and Embeddings

Wai Gen Yee, Grubhub (slides)
11:30 AM EST

Online Fashion Commerce: Modelling Customer Promise Date

Preethi V, Nachiappan Sundaram and Ravindra Babu Tallamraju (paper)
12:00 PM EST

A Game Theoretic Algorithm for Elite Customer Identification in Online Fashion E-Commerce

Chandramouli Kamanchi, Gopinath Ashok Kumar, Girish Satyanarayana and Ravindra Babu Tallamraju (paper)
12:30 PM EST

Explore Gather

1:00 PM EST

Keynote 2

Learning from deep learning for Snapchat Ads

Vineet Abhishek, Snap
2:00 PM EST

Named Entity Recognition for E-commerce Queries

Bhushan Ramesh Bhange, Xiang Cheng, Mitchell Bowden, Priyanka Goyal, Thomas Packer and Faizan Javed (paper)
2:30 PM EST

A Cognitive User Model for E-commerce Search

Sahiti Labhishetty, Chengxiang Zhai, Suhas Ranganath and Pradeep Ranganathan (paper)
3:00 PM EST


3:30 PM EST

Keynote 3

Computer Vision and E-Commerce

Alessandro Magnani, Walmart Labs (slides)
4:30 PM EST

Detecting and Correcting Real World Errors in Ecommerce Search

Jared Moore, Mingzi Cao and Rongkai Zhao (paper)
5:00 PM EST

An Opportunistic Bandit Approach for User Interface Experimentation

Nader Bouacida, Amit Pande and Xin Liu (paper)
5:30 PM EST

Query Rewrite for Low Performing Queries in E-commerce based on Customer Behavior

Meng Zhao, Morgan White and Faizan Javed (paper)