May 04 to 05 2015, Santa Clara, USA.


Speaker "Vijay Agneeswaran" Details

Name :
vijay agneeswaran
Company :
Title :
Director of Technology
Topic :

Distributed Deep Learning Framework over Apache Spark

Abstract :

The talk gives the basics of deep learning and outlines motivation for a distributed implementation. It describes a distributed deep learning framework that we have implemented over Apache Spark, including changes made to Spark and possible further improvements. The talk also details an audio sentiment analyzing application that we have built over the framework – this uses a MFCC extractor to extract important features from the speech, passes it through a Hidden Markov Model to handle fluctuations in pronunciation and passes HMM output to a recurrent neural tensor network for sentiment classification. Key takeaways for the audience include:

1.       From ANN to Deep learning – quick overview of the field.

2.       Applications of deep learning.

3.       Motivation for distributed deep learning and overview of our distributed deep learning framework over Spark.

4.       Detailed overview of the application – sentiment analysis of audio data using the framework.

Profile :

Dr. Vijay Srinivas Agneeswaran has a Bachelor’s degree in Computer Science & Engineering from SVCE, Madras University (1998), an MS (By Research) from IIT Madras in 2001, a PhD from IIT Madras (2008) and a post-doctoral research fellowship in the LSIR Labs, Swiss Federal Institute of Technology, Lausanne (EPFL). He has joined as Director of Technology in the data sciences team of SapientNitro. He has spent the last ten years creating intellectual property and building products in the big data area in Oracle, Cognizant and Impetus. He has built PMML support into Spark/Storm and realized several machine learning algorithms such as LDA, 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.  He and his team have also built the first distributed deep learning framework on Spark. He is a professional member of the ACM and the IEEE (Senior) for the last 10+ years. He has four full US patents and has published in leading journals and conferences, including IEEE transactions. His research interests include distributed systems, data sciences as well as Big-Data and other emerging technologies. He has been an invited speaker in several national and International conferences such as O'Reilly's Strata Big-data conference series. He lives in Bangalore with his wife, son and daughter and enjoys researching history and philosophy of Egypt, Babylonia, Greece and India.


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