About Centre
Faculty
Research
Events/Activities
About Centre
NVIDIA
RCOEM in association with NVIDIA has set-up the 1st Centre of Excellence in Artificial Intelligence and Deep learning (AI & DL) in centre India. Core purpose of this centre is to build a high throughput AI compute infrastructure to create a pool of skilled manpower in Deep Learning, Machine Learning, Data Science and Analytics to conduct research and development based on industry relevant live use cases.
The key expected outcomes are as follows:
Main gains for the students: Immersive – Learning Environments, University Innovation Fellowships; Employability, Start-Up Based Entrepreneurship.
Main gains for the faculty: Knowledge Upgradation, Work with leaders in technology, Enhanced Research Activities and scope for Consultancy.
Main gains for the institution: Laboratories with support for Train – The –Trainers using the Instructor – Led Model.
Short term goals
- To conduct focused research leading to publication in reputed conferences/journals, research proposals.
- To develop state of art training facilities in the focused area
- To develop innovative solutions in specialized domain
Long term goals
- To make this Centre of Excellence self-sustainable through the revenue generation from Research grants and Consultancy
- To have strong Industry linkages by National and International collaborations
Training program.
3_NVIDIATrainingReportFaculty
Facilities
- NVidia Dgx DL Workstation
- Intel Xeon E5-2698v4 2.2 Ghz 20 Core
- 4 X Tesla V100 (500 Tflops)
- 128GB System GPU Memory
- 256 GB DDR4 RAM
- Data 3 x 1.92 TB SSD RAID 0
- OS 1 x 1.92 TB SSD
- Dual 10 GBASE-T (RJ 45)
- 3X DisplayPort 4K resolution
- 2 x eSata 2x USB 3.1 , 4 x USB 3.0
- Ubuntu Desktop Linux OS
- DGX Recommended GPU Driver CUDA Toolkit
- NVIDIA Deep Learning Teaching Kit that includes Syllabus examples, Labs Exercises, Quizzes etc
- Free Access to NVIDIA Deep Learning GPU Training System (DIGITS).
- NVIDIA-CUDA-Toolkit
Research
Research
1. Research Project
Title: Development of Coal Quality Exploration Technique based on Convolutional Neural Network and Hyperspectral Images
Collaborating Agency: CSIR-Central Institute of Mining & Fuel Research Nagpur
Project Coordinator: Dr. M.B.Chandak
Project Co-coordinator: Dr. S. Hira
Project Grant/ Amount : 103 Lakhs
2. SCI Publications
- Lalit Agrawal, Dattatraya Adane, “Improved Decision Tree Model for Prediction in Equity Market Using Heterogeneous Data”. IETE Journal of Research, DOI Paper DOI:10.1080/03772063.2021.1982415), Published on 29th September, 2021
- P.J. Assudani, P. Balakrishnan “An efficient approach for load balancing of VMs in cloud environment”, Applied Nanoscience (2021), Springer- SCIE and SCOPUS indexed Journal, impact factor: 4.604.
- Swati Hira, Anita Bai, “An Intelligent hybrid deep belief network model for predicting students employability”, Soft Computing, Springer, Apr 21, https://doi.org/10.1007/s00500-021-05850-x
- Khushboo Khurana, Umesh Dehpande, “Video Question-Answering Techniques, Benchmark Datasets and Evaluation Metrics Leveraging Video Captioning: A Comprehensive Survey”, IEEE Access, Feb-21. Volume: 9, Page(s): 43799 – 43823, DOI: 10.1109/ACCESS.2021.3058248
- S Hira, A Bai, S Hira, “An automatic approach based on CNN architecture to detect Covid-19 disease from chest X-ray images”, Applied Intelligence 51 (5), 2864-2889, Nov-20.
- Pravin Sonsare, C.Gunvathi, “Investigation of Machine Learning Techniques on Proteomics: A Comprehensive Survey”, Progress in Biophysics and Molecular Biology, Dec-19, Volume 149,pp55-69, doi.org/10.1016/j.pbiomolbio.2019.09.004
- S. R. Vij, D. Mukhopadhyay and A. J. Agrawal, “Automated Negotiation in E Commerce: Protocol Relevance and Improvement Techniques”, Computers, Materials & Continua CMC, vol.61, no.3, pp.1009-1024, Dec 2019.
- Shailendra S. Aote, A. Potnurwar, “An automatic video annotation framework based on two level keyframe extraction mechanism”, Multimedia Tools & Applications, Springer. Jun 2019, DOI: https://doi.org/10.1007/s11042-018-6826-3, vol 78, issue 11, pp. 14465–14484.
- Harmeet Kaur Khanuja, Dattatraya Adane, “Monitor and Detect Suspicious Transactions With Database Forensic Analysis”, Journal of Database Management, Volume 29, Issue 4, October-December 2018.
- Dr. M. B. Chandak, Jayant Karnjekar, “Uniform Query Framework for Relational and NoSQL Databases”, Computer Modeling in Engineering and Science, Vol. 113- Issue 2, Dec2017.
- Madhuri A. Tayal, M. M. Raghuwanshi and Latesh Malik. “ATSSC: Development of an Approach based on Soft Computing for Text Summarization”, Elsevier, Science direct journal, Computer Speech and Language, Volume: 41 (2017) pg 214–235, Impact Factor: 1.324
- Dr. Swati Hira, Anita Bai, “Recurrence Based Similarity Identification of Climate Data”, Discrete Dynamics in Nature and Society, Hindavi Publications, https://doi.org/10.1155/2017/7836720, Jul 2017.
- Shailendra S. Aote, M.M.Raghuwanshi, L.G.Malik, “Improved Particle Swarm Optimization Based on Natural flocking Behaviour”, Arabian Journal of Science & Engineering, Springer. DOI:10.1007/s13369-015-1990-5, vol 41, Mar 2016, pp. 1067-1076.
3. Research Domains and Groups
Events/Activities
Events / Activities
- First training on NVIDIA DGX Station including Installation was conducted on 05/10/2020 from 10.30 am to 8.15 pm. Mr. Hariharan Venugopal from NVIDIA has delivered the training. Total 18 faculties have participated in the training from CSE/MCA department. Topics were covered during the training are Docker and Container processes, NVIDIA NGC – Account creation and usage, Features of NVIDIA DGX station, Server Installation, How to use dgx – (creating NGC container, Creating Doc container, pushing data to dgx box and processing it and getting the back the results).
- Second training on NVIDIA DGX Station was conducted on 03/11/2020 virtually from 10.30 am to 4.30 pm. Mr. Hariharan Venugopal from NVIDIA has remotely joined for delivering the training. Total 14 faculties have participated in the training from CSE/IT department. The topics were covered during the training were Recap of Docker and Container process, How to use dgx – (creating NGC container, Creating Doc container, pushing data to dgx box and processing it and getting the back the results ), Access and use of NVIDIA NGC Kubernetics overview, How to use GPUs, Mixed precision.
- Training sessions on “Problem solving using Nvidia GPU” : Dr. Shailendra S. Aote and Dr. Ramchand Hablani from department of computer science and engineering have organized training sessions on problem solving using Nvidia GPU under Centre of Excellence in Artificial Intelligence and Deep Learning on 23 Mar, 25 Mar and 1 Apr 2021. The session was conducted for all the faculties of RCOEM and VI semester CSE students. How to access GPU, Significance of GPU for problem solving, study of computational time variations on CPU and GPU, Neural network performance on CPU and GPU were the contents for the same. Around 70 participants were present during each seminar.
