Corporate Talk



Ernesto Zamora Ramos

(Intel Corporation, USA)

Bio: Ernesto Zamora Ramos is a deep learning software engineer for Intel Corporation. His work entails the creation of cutting edge innovation on Intel’s large silicon offering of accelerators, general and specialized, for artificial intelligence, neural network training, and inference. Dr. Zamora received his Ph.D. in Computer Science from the University of Nevada, Las Vegas in 2017 for his work in computer vision and artificial neural networks. He worked under NSF grants for machine learning applications to solar panel energy optimization and he has several publications in artificial intelligence and computer vision on IEEE and other journals and conferences.

Title of the talk: The Prevalence of Artificial Neural Networks in Everyday Life.

Abstract: As technology and electronics permeate most aspects of our lives today, many people have increased access to an electronic device that has the capability to perform some prediction or reach a decision, either on the device itself or in the cloud. We would be surprised to know how many of these decisions are reached by applying some form of artificial neural network that has replaced some classical statistical algorithm. State of the art neural networks have managed to surpass human capabilities in their task, and the best products apply these to stay competitive. This talk will discuss how neural networks have been replacing many classical and statistical algorithms from pattern recognition to image processing, and can be found applied to many and least likely applications. It will also discuss some current industry challenges on implementation, training and deployment of neural networks, current solutions, and research opportunities to overcome these challenges.


Important Deadlines

Full Paper Submission:31st October 2019
Acceptance Notification: 30th November 2019
Final Paper Submission:15th December 2019
Early Bird Registration: 15th December 2019
Presentation Submission: 31st December 2019
Conference: 6 - 8 January 2020

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•    Conference Proceedings will be submitted for publication at IEEE Xplore Digital Library
•    Best Paper Award will be given for each track
•    There will be two workshops on- i. Data Analysis and ii. IoT on Jan 8, 2020
•    There will be Corporate Exhibitions and Product Display for the last two days of the conference.
•    Conference Record No- 47524