Sep 9–12, 2019
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Vijay Srinivas Agneeswaran

Vijay Srinivas Agneeswaran
Director, Data Sciences, Walmart Labs

Website | @a_vijaysrinivas

Vijay Srinivas Agneeswaran is a director of data sciences at Walmart Labs in India, where he heads the machine learning platform development and data science foundation teams, which provide platform and intelligent services for Walmart businesses around the world. He’s spent the last 18 years creating intellectual property and building data-based products in industry and academia. Previously, he led the team that delivered real-time hyperpersonalization for a global automaker, as well as other work for various clients across domains such as retail, banking and finance, telecom, and automotive; he built PMML support into Spark and Storm and realized several machine learning algorithms such as LDA and random forests over Spark; he led a team that designed and implemented a big data governance product for a role-based fine-grained access control inside of Hadoop YARN; and he and his team also built the first distributed deep learning framework on Spark. He’s been a professional member of the ACM and the IEEE (senior) for the last 10+ years. He has five full US patents and has published in leading journals and conferences, including IEEE Transactions. His research interests include distributed systems, artificial intelligence, and big data and other emerging technologies. Vijay has a bachelor’s degree in computer science and engineering from SVCE, Madras University, an MS (by research) from IIT Madras, and a PhD from IIT Madras and held a postdoctoral research fellowship in the LSIR Labs, Swiss Federal Institute of Technology, Lausanne (EPFL).


1:45pm2:25pm Thursday, September 12, 2019
Location: 230 A
Vijay Srinivas Agneeswaran (Walmart Labs), Abhishek Kumar (Publicis Sapient)
Vijay Agneeswaran and Abhishek Kumar explore multilabel text classification problems, where multiple tags or categories have to be associated with a given text or documents. Multilabel text classification occurs in numerous real-world scenarios, for instance, in news categorization and bioinformatics (such as the gene classification problem). Read more.
  • Intel AI
  • O'Reilly
  • Amazon Web Services
  • IBM Watson
  • Dataiku
  • Dell Technologies
  • Intuit
  • Gamalon
  • Hewlett Packard Enterprise
  • MapR Technologies
  • Sisu Data
  • Intuit

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