NIT Andhra Pradesh partners with LinkedIn for research and development

NEW DELHI: The National Institute of Technology (NIT) Andhra Pradesh has signed an agreement with LinkedIn to facilitate collaborative research and development.

Under the agreement, a research grant will be awarded to the principal investigator Karthick Seshadri and the co-investigator Nagesh Bhattu Sristy, both assistant professors at NIT Andhra Pradesh, for solving open research problems in enabling intelligent and elastic cloud computing.

Also Read | IIT Delhi start-up designs stronger, durable fabric for National Flag

The objectives of the agreement include:

• To nurture and create a talent-pool with a niche skill set in Cloud Computing and the broad domains of Machine Learning and Statistical Modeling for data analytics and training them to be industry-ready.
• To produce a PhD student out of this project with a strong skill set to solve contemporary problems in Distributed Systems Engineering and Computing
• To publish research articles in impact journals of high repute with the findings from this collaborative work
• To inculcate the culture of organizing faculty development programs on Cloud Computing by sharing the findings of this project with the peer research groups and faculty across India

Speaking about this initiative, C S P Rao, director, NIT Andhra Pradesh, said, “The association of the two organisations would enable joint research in the niche area of intelligent cloud computing and in fostering research to address industry relevant problems by the academia.”

“I appreciate the researchers at NIT Andhra Pradesh for providing an extensive training to their research team on Statistical Modeling, Cloud Computing and Machine Learning, to impart the necessary technical-know-how for meeting the objectives of the first MoU,” he added.

Also Read | Republic Day 2022: IIT Guwahati drones start-up to perform show at event in Assam

Chidambaran Kollengode, director, Data and AI Platforms division of LinkedIn, said, “Scaling is a big challenge in the cloud environment and a truly elastic model is typically viewed as a financial optimization problem; however, we have attempted to explore the technical implications underlying this problem. To address the problem of scaling, there is a need for an efficient workload characterization model. I am happy to remark that this collaboration has been very promising and fruitful in our steps to realize a truly elastic cloud.”