Welcome Address  

Dr.Rama Vaidyanathan gave the welcome address to the gathering and informed about the interdisciplinary research activities and the academic industry collaboration at the University on the precepts of Innovation and Entrepreneurship.   

 

Presidential Address

Dr.G.Gopala Krishnnan, ProVost, Dr.MGR Edu. & RI informed about the need for innovation and technology transfer. He also insisted about the interdisciplinary research as the need for the hour. 

 

Plenary Session - Dr.Venil Sumantran, Scientific Advisor, Dr.APJCoE   

The talk examined statistics on PhD’s, research output, and ranking of Indian Universities. A few ‘top Indian scientists’ and their work was highlighted. Issues regarding quality and quantity of research was addressed. Some hurdles faced by Indian scientists and how we (at MGRU), can adapt was discussed.  “Open Science” is a valuable resource that has changed the way to do research. How can to tap this useful resource at  MGRU ? was highlighted. The talk also included a quiz on Indian scientists who made major contributions to global science in recent years and in the past.     

 

A session on Design Thinking by Dr. Rama Vaidyanathan

A Crash course on Innovative thinking for a group of 40 students was conducted by Dr. Rama Vaidhyanathan, Director(R&D). The workshop covered all the aspects of why and how to think out of the box. Students engaged themselves in activities to come up with different ideas. They also learnt the Design thinking methodology for prototyping.  The importance of Empathising with people facing a problem, defining the problem and then ideating! They were also taught to do this with some examples.

 

Business Simulation by Dr. Arun Kumar J

Lead by Arun Sir and his team the Simulation game was a hit.  There was a record of 76 participants.  As each team worked to produce paper ships they had to handle the Pollution Control Board and ISO Certification.  The pollution control Board went around with a Noise Detection kit and any team which made more than 70 deci bell sound was fined!  The Bank suddenly announced a demonetization drive and all Rs. 100 had to be returned.

 

Business Model Preparation by Dr. J. Arun Kumar J

In the afternoon, the selected students assembled with their team members. They were then given with some worksheets. The worksheets contained blanks for creating a roadmap and to plan for building up their own start-up. The students were given half an hour to discuss with their team members and come with a proper business model. After which the students had a one on one session with the expertise from the industry who gave them a view on the alterations to be done. They were again given a half an hour of time to make modifications and do the final pitch.

 

Pitch Camp by Mr. H Mohamed Rizwan

The pitch camp was aimed to gather ideas and products that can be commercialized in near future, such that, the students gain a platform of self-sustainability as soon as they finish their academic career. The students had to present their idea to the jury with crisp slides.

 

A session on Deep learning and neural network

Mr.Srivardhan Reddy Surya

Manager-Data Science and AI

Entigence Corporation 

In this technical talk, Deep learning and its algorithms which emerged in recent years which brought a new wave to machine learning, and making artificial intelligence and human and computer interaction advanced in recent years was unwarped.

In Deep Learning information was given on the Computer vision, its science and technology, the  methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical information, image understanding from image data using models constructed with the help of geometry and statistics.

How images use convolution neural network (CNN or ConvNet) which is a class of deep neural networks, most commonly applied to analyzing visual imagery. It was also informed on how Convolutional networks were inspired by biological processes and the mathematical theory behind Pooling, Convolution, Convolutional layers and how to normalize the data and many more mathematical concepts and also the relation between Regression models(Linear and Logistic Regression) and Neural Networks like Perceptron,Multi layered Perceptron and also various activation functions like Identity, Sigmoid and Rectified linear units(ReLU) activation functions and the mathematics behind and also how Sigmoid and Tanh will create vanishing gradient problem when dealing with deep neural networks.

In-depth understanding on CNN architectures like AlexNet and VGGNet and also various scenarios. What is the benchmark for validating the algorithms.Role of ImageNet (large visual database).

Image recognition using various CNN architecture, process of detecting and identifying an object or a feature present in images. and also extract features from images like colors, edges, gradients and several intelligent methods.

I will also talk about the role of research students in deep learning Computer Vision, areas where patents can be created, research publications and what industry is expecting from research students. Role of electronics and mechanical engineers to take deep learning to next level robotics where and how deep learning helps in reducing the most tedious manual works. Most importantly i will talk about how to gather data and tune your data in order to fetch more accuracy for your deep neural networks.