CSE session : Continual Learning Machines | Shiv Nadar University
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CSE session : Continual Learning Machines

Event Date: 
Thursday, April 7, 2022 -
12:0013:00

The Department of Computer Science and Engineering invites you to a session titled ‘Continual Learning Machines’ by Mr. Sunny Manchanda, Director at DRDO Young Scientist Laboratory - Artificial Intelligence. The talk is scheduled on April 7, 2022, from 12:00 Noon.

Mr. Sunny Manchanda, is a computer scientist who graduated from IIT Delhi specializing in Artificial Intelligence. In academia he along with Prof. Aaditeshwar Seth were driven towards finding answers to India‘s Development Story using AI technologies like Satellite Data Analysis in order to contribute towards data-driven policymaking. He has also been working in the domain of complex airborne systems for the past decade on the AEW&C Netra Team. As a computer scientist he was initially chosen to work in the Aerospace domain of Indian Defence Research and was awarded the coveted Vice-Chancellor Commendation Certificate for top position in Aeronautics stream at the prestigious Indian Defence Training School at Pune. Mr.  Sunny Manchanda is one of the youngest Directors of DRDO and was picked by the Principal Scientific Advisor to the Prime Minister and the DRDO top brass to head the new DRDO Young Scientist Laboratory for Artificial Intelligence (DYSL-AI). He is currently driven to establish DYSL-AI as a global research laboratory with focus on Vision, Speech and Language Technology.

Abstract 
It has been a human endeavour to build AI with the capability to learn new skills over time akin to learning in intelligent beings. This in deep learning AI research community, generally referred to as Continual learning, has seen a lot of interest and excitement in the recent past. While the AI community is taking rapid strides on reaching and at times surpassing human level intelligence on narrow tasks, the need for continual learning is more apparent than ever.

This talk will try to cover some ground on the recent progress in the techniques and algorithms for continual learning in deep networks and motivate why such a paradigm is fundamental to build the next generation of intelligent machines.

Thursday 07, Apr 2022
12:00 PM - 01:00 PM

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