Department of Electronics and Communication Engineering, Sai Vidya Institute of Technology, Bengaluru in association with IEEE SVIT Student Chapter conducted Webinar on the topic “Machine Learning”.

Date of the Event: 10th August 2020 at 10:00 AM

Speaker Details :Prabuchandran K.J. is an Assistant Professor at IIT Dharwad. He completed Ph.D. from the Department of Computer Science and Automation, IISc in the area of Reinforcement Learning. Post his PhD, Prabuchandran worked as Research Scientist at IBM Research Labs, India for an year and half on change detection algorithms for multivariate compositional data. After that he pursued his postdoctoral research at IISc, Bangalore as an Amazon-IISc Postdoctoral scholar for an year and half on Multi-agent Reinforcement Learning and Stochastic Optimization algorithms. His research lies in the intersection of reinforcement learning, stochastic control & optimization, Machine Learning, Bayesian Optimization and stochastic approximation algorithms. His research interest also focuses on utilizing techniques from these fields in solving problems arising in applications like wireless sensor networks, traffic signal control and social networks.

Online webinar Platform: Google Meet Application Webinar meeting Link: https://bit.ly/IEEESVITMLWebinarLive

Timings: 10:00 AM to 11:00 AM

Total Number of Registrations: 120+

More than 120+ participants are registered for the webinar and more than 120 Participants actively participated from various Industry professional’s/ Faculty member’s/ Research scholars/ students from many reputed institutions were witnessed the webinar. The webinar is started at 10:00 AM with formal Welcome for the speaker, Dr.Prabuchandran K.J by Ms.Nandana, Vice Chair-IEEE SVIT student branch,.

The speaker Dr.Prabuchandran K.J, gave interesting talk on the review of machine learning and Deeplearning . Machine learning involves a lot of complex math and coding that, at the end of the day, serves a mechanical function the same way a flashlight, a car, or a computer screen does. When we say something is capable of “machine learning”, it means it’s something that performs a function with the data given to it and gets progressively better over time. A deep learning model is designed to continually analyze data with a logic structure similar to how a human would draw conclusions. To achieve this, deep learning applications use a layered structure of algorithms called an artificial neural network. The design of an artificial neural network is inspired by the biological neural network of the human brain, leading to a process of learning that’s far more capable than that of standard machine learning models. All the participants are appreciated the talk and mentioned as very informative session. Vote of thanks was given EshanyaBhat, Joint ChapterChair ,IEEE CS/IS ,SVIT student branch.

Chief Coordinator: Dr. Narayan K, Advisor, IEEE SVIT Student Branch, Dean (R&D) and Professor Department of ECE

Head of the Department: Prof. Vikramathithan A C, Department of ECE

Faculty Coordinators

1.Dr. Venkatesha M–Branch Counselor, IEEE SVIT Student Branch

2.Mr. Pavan Kumar E, Assistant Professor, Department of ECE

3.Ms. Monisha Raj, Assistant Professor, Department of ECE

Student Coordinators

1.Mr. Sourabh Bhat, Student secretary, IEEE SVIT student Branch

2.Ms. Bina R, Student Chair, IEEE SVIT Student Branch