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Arun Iyengar does research, development, and consulting in cloud computing and artificial intelligence at IBM's T.J. Watson Research Center. He has performed a considerable amount of past work in Web performance, caching, as well as fault-tolerant computing and high availability. His activities involve computer science research leading to publications and patents as well as software engineering leading to products, solutions for customers, and open source software.
Arun's work has been incorporated into several products (by IBM and other companies) as well as commonly used open source software. His caching and load balancing techniques are widely used to improve performance for Web sites and distributed applications. He has also developed widely used techniques for dynamically generating Web content which have been incorporated into Web content management systems as well as a widely used method for preserving state on the Web without using cookies. More recently, he has written software for improving the performance, functionality, and usability of cloud services. He is currently developing machine learning software for real data prediction problems faced by customers.
Arun's work has been incorporated into several products (by IBM and other companies) as well as commonly used open source software. His caching and load balancing techniques are widely used to improve performance for Web sites and distributed applications. He has also developed widely used techniques for dynamically generating Web content which have been incorporated into Web content management systems as well as a widely used method for preserving state on the Web without using cookies. More recently, he has written software for improving the performance, functionality, and usability of cloud services. He is currently developing machine learning software for real data prediction problems faced by customers.
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International Conference on Trust, Privacy and Security in Intelligent Systems and Applicationspp.307-313, (2023)
IEEE Transactions on Mobile Computingno. 7 (2023): 4000-4015
Proc. VLDB Endow.no. 8 (2021): 1262-1275
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