Age, Biography and Wiki
P. J. Narayanan was born on 1963, is an An indian computer scientist. Discover P. J. Narayanan's Biography, Age, Height, Physical Stats, Dating/Affairs, Family and career updates. Learn How rich is he in this year and how he spends money? Also learn how he earned most of networth at the age of 61 years old?
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He is a member of famous computer with the age 61 years old group.
P. J. Narayanan Height, Weight & Measurements
At 61 years old, P. J. Narayanan height not available right now. We will update P. J. Narayanan's Height, weight, Body Measurements, Eye Color, Hair Color, Shoe & Dress size soon as possible.
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Dating & Relationship status
He is currently single. He is not dating anyone. We don't have much information about He's past relationship and any previous engaged. According to our Database, He has no children.
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P. J. Narayanan Net Worth
His net worth has been growing significantly in 2023-2024. So, how much is P. J. Narayanan worth at the age of 61 years old? P. J. Narayanan’s income source is mostly from being a successful computer. He is from . We have estimated P. J. Narayanan's net worth, money, salary, income, and assets.
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$1 Million - $5 Million |
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Pending |
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Under Review |
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computer |
P. J. Narayanan Social Network
Timeline
P. 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 obtained his B. Tech degree in computer science and engineering from Indian Institute of Technology, Kharagpur in 1984.
He moved to University of Maryland for graduate studies in 1986.
He worked as a research faculty member at the Robotics Institute of Carnegie Mellon University.
He was instrumental in building the virtualized reality system that for the first time captured dynamic events in 3D from multiple points of view.
The events so captured could be integrated into a virtual reality environment for visualization and manipulation.
Narayanan graduated with a master's degree from University of Maryland, College Park, US in 1989 and obtained his Ph.D in computer science from University of Maryland, College Park, US in 1991 where he worked with Prof. Larry Davis.
Narayanan started his career in the Lipi group of the R&D group of CMC Ltd and helped design the second generation hardware for their Indian language word processor.
He joined the Centre for Artificial Intelligence and Robotics (CAIR), a DRDO lab, in 1996.
He headed the Computer Vision and Virtual Reality groups of CAIR and was instrumental in initiating several VR applications for DRDO and the defence.
He moved to IIIT-Hyderabad in 2000 and established the Centre for Visual Information Technology (CVIT), which has grown into the largest research group in India in the areas of computer vision, graphics, and medical image processing.
Prof. Narayanan has played crucial roles in several editions of the Indian Conference on Computer Vision, Graphics, and Image Processing (ICVGIP).
He was also instrumental in bringing the Asian Conference on Computer Vision (ACCV) to Hyderabad in 2006.
He has been an Area Chair for ICCV, CVPR, ACCV, IJCAI, etc.
He was appointed the Co-Chair of the ACM India Council when it was formed.
He became the first President of ACM India in 2012 and is the Chair of the ACM India Research Board from 2014.
He has played several roles in the Association for Computing Machinery including being in the Nominations Committee and the committee to decide on the Outstanding Contributions to ACM award.
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.
