Prof. P. J. Narayanan of Director, International Institute of Information Technology

India’s IT competencies have brought significant international attention in terms of investments. In the tenure of 2000-2020, FDI or Foreign Direct Investment was about $ 39.4 Billion. Major areas of investment under the IT and ITES umbrella lies in Artificial Intelligence, Blockchain, Internet of Things or IoT, RPA or Robotic Process Automation, and other diverse fields under the same folds of technology.

In this session the participants will be able know about the following information:

India, as compared to other western countries, in the past has been considered as slow when it comes to IT and ITES development but with the Government now taking stringent steps to fast forward the implementation of new technologies. Joining hands with the Indian Government, AeoLogic, is now one of the most chief companies in the country that works to strategise, implement and execute the next generation tech like Artificial Intelligence, Smart Cities, Blockchain, Internet of Things, and more.

Biography:

1. J. Narayanan(born 1963 in Alwaye, Kerala) is a professor at the International Institute of Information Technology, Hyderabad, and the institute's current director since April 2013. He is known for his work in computer vision (3D reconstruction, structure-from-motion, computational displays), computer graphics (ray-tracing of implicit surfaces, dynamic scenes), and parallel computing on the GPU (graph algorithms, string sorting, ML techniques like graph cuts, ANN and clustering, as well as several computer vision tasks). Narayanan has contributed to the areas of computer vision, computer graphics and parallel processing. In computer vision his early work on 3D recovery of dynamic scenes through virtualized reality has resulted in tremendous growth in 3D capture to be available to end users. Capture of 3D has now become common place through the Microsoft Kinect and other commodity sensors. He pioneered the use of innovative platforms like the GPU for common computer vision applications such as graph cuts, neural networks, clustering etc. Use of the GPU in computer vision has culminated in the GPUs making Deep Learning practical for several applications. His work on general parallel computing involving CPUs and GPUs has also been recognized worldwide.