Sujoy Roy (AWS) – Building Machine Learning Solutions: A Working Backwards Approach

EVENT DATE
16 Apr 2024
Please refer to specific dates for varied timings
TIME
1:30 pm 2:30 pm
LOCATION
SUTD Think Tank 9/10 (Building 1, Level 4) 8 Somapah Road

Abstract

Working Backwards is Amazon’s process of discovery and invention that delivers customer delight. Whether it is research or product building, at the Generative Al Innovation Center, AWS, we take a working backwards approach starting with the user/customer. This talk will discuss the different stages of this working backwards approach to research and building a production ready machine [earning (ML) solution. With specific examples of ML based products/solutions we dive deep into how to start with a business problem and build a minimum valuable product (MVP) using machine learning. As part of this we will also discuss a few AWS ML products/services and AWS open sourced software that helps with building such MVPs.

Speaker’s Profile

Sujoy Roy, Ph.D
Principal-Applied Scientist
Generative Al Innovation Centre (GenAIIC), AWS

Sujoy Roy, Ph.D. is a princioal applied scientist with the Generative Al Innovation Centre (GenAlIC) at AWS. He is a Tech lead for the GenAlIC team at APJ and has led several customer projects in APJ under different industry verticals namely manufacturing, retail, adTech, telco, finance, logistics, software/internet etc. He has over 18+ years of academic and industry experience building and deploying ML based solutions for business problems. Prior to AWS, he was a senior researcher at SAP, designing and building SAPs Business Intelligence Solution. Prior to that he has been a senior research scientist with the Institute for Infocomm Research, A*STAR, Singapore working on several academic and industry collaborations which include being PI for several projects under the IPTV Testbed initiative of NGNBN project in Singapore, Content Metadata Generation and Recommendation solution projects with NBC Universal and Comcast (contributor to Comcast Xfinity personalised recommender solution). He holds a Ph.D. in computer science from the National University of Singapore and a MS in computer science from the Indian Institute of Technology, Delhi. His research interests are in the fields of computer vision, multimedia, search and recommender systems. He has published 70+ publications in peer reviewed journals and conferences and granted 6 patents in the US.

To register, please click the link: https://forms.office.com/r/Lqpr5A5Sq9 or scan the QR code below the poster.

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