works for HPE(Hewlett-Packard Enterprise) in the HPC(High-Performance Computing) R&D division
The seminar was about Math behind sciences in coordination with Mr.G.V.K.Madhav, who works for HPE(Hewlett-Packard Enterprise) in the HPC(High-Performance Computing) R&D division. The event was hosted by AAC on 30th March, 2019 from 02:15 P.M. to 03:45 P.M.
It was attended by the students aspiring to reap their career in the field of Data science.
The seminar was attended by the students in the bachelor’s program. A student of AAC opened the seminar and welcomed Mr.G.V.K.Madhav by introducing him to the audience.
G.V.K.Madhav works for HPE(Hewlett-Packard Enterprise) in the HPC (High- Performance Computing) R&D division, working specifically on qualifying accelerator servers of HPE with NVIDIA and AMD GPUs. He has expertise in OpenCL, CUDA frameworks and develops codes used for evaluating the efficiency and benchmarking of accelerators or GPUs. He graduated from IISc with an MTech degree in Computational Science from the Department of Computational and Data Sciences.
His Master's thesis work at IISc on using GPUs for improving the performance of LiFE(Linear Fascicle Evaluation) software got published as a poster at “OHBM (Organization for Human Brain Mapping) 2018 Conference. He also has a Post-Graduate degree in Mathematics from Osmania University and a Post-Graduate level degree in Computer Science from IETE.
The main objective of the seminar was to introduce students about data science and its applications in various sectors
At the seminar the presentation made by Mr.G.V.K.Madhav includes the following information.
Extending a matrix to span more than two dimensions results in a tensor. Tensors are data structures that represent multi-way data that is found in many modern applications. Recently, tensors have become popular in communities such as data mining, recommender systems, and health informatics [8,10,17]. Tensor factorization can be used to find a low rank representation of sparse data, which provides insights not usually obvious in the original dimensionality. A tensor field is a tensor-valued function of position in space. The use of tensor field allows us to present physical laws in a clear, compact form. He gave a clear explanation about tensors and their applications in daily life.
Finally, the seminar was very interactive and around 80 participants were present. Students were enlightened with clear understanding, about Data Science. Students were provided with several ideas to implement using tensors and were motivated to get into Data science based real time project for better life.