DATA SCIENCE LABORATORY

The Data Science (DS) laboratory was started in the year of 2018. It is equipped with GPU-based machines to conduct intensive research and to solve complex computational problems.

People

Dr. Dipti P. Rana

Lab In-charge

Ph. D. Scholars

Ms. Vaishnavee Rathod (D20CO004)
Ms. Anjali More (DS15CO008)
Mr. Mathe John Kenny Kumar (DS18CO001)
Ms. Pranita Mahajan (DS18CO004)

Gallery

DS Lab
DS Lab
DS Lab
DS Lab
DS Lab
DS Lab

Research Project Areas

Influence Identification and Ranking in Scholarly Data

Satellite Data Mining

Legal Document Recommendation System

Imbalanced Data Mining

Publication

1. V. V. Rathod, D. P. Rana and R. G. Mehta, "An Extensive Review of Deep Learning Driven Remote Sensing Image Classification Models," 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT), Kannur, India, Oct. 2022, pp. 762-774, doi: 10.1109/ICICICT54557.2022.9917583.
2. Dipti Rana, Charmi Shah, Yamini Kabra, Ummulkiram Daginawala and Pranjal Tibrewal, "Hierarchical Earthquake Prediction Framework", International Conference on Paradigms of Communication, Computing and Data Sciences (PCCDS 2022), Malaviya National Institute of Technology Jaipur, India, July 05-07, 2022. (ACCEPTED)
3. A. S. More and D P Rana, "Review of Random Forest Classification Techniques to Resolve Data Imbalance," IEEE 1st International Conference on Intelligent Systems and Information Management (ICISIM), Aurangabad, India, 2017, pp 72-78, 2017. DOI: 10 1109/ICISIM 2017 8122151. (Best Paper Award) (SCOPUS)
4. Anjali S. More, and Dipti P. Rana, and Isha Agarwal, Random Forest Classifier Approach for Imbalanced Big Data Classification for Smart City Application Domains, International Journal of Computational Intelligence & IoT, Vol. 1, No. 2, 2018. SSRN: https://ssrn.com/abstract=3354727
5. Anjali S. More, and Dipti P. Rana, ”An Experimental Assessment of Random Forest Classification Performance Improvisation with Sampling and Stage Wise Success Rate Calculation”, ELSEVIER Procedia Computer Science 167, pp. 1711–172, 2020. DOI: https://doi.org/10.1016/j.procs.2020.03.381 (SCOPUS)
6. Anjali S. More, and Dipti P. Rana, ” Performance Enrichment through Parameter Tuning of Random Forest Classification for Imbalanced Data Applications”, Elsevier Journal Materials-Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.12.020 (SCOPUS)
7. Anjali S. More, and Dipti P. Rana, "Review of Imbalanced Data Classification and Approaches Relating to Real-Time Applications." Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance, edited by Dipti P. Rana and Rupa G. Mehta, IGI Global, pp. 1-22, 2021. DOI: https://doi.org/10.4018/978-1-7998-7371-6.ch001 (SCOPUS)
8. Agarwal, I., Rana, D., & More, A., "Predicting the Veracity of Fake Information on Smart Media for Reducing Misinformation Diffusion" (2018). International Journal of Computational Intelligence & IoT, Vol. 1, No. 2, 2018, Available at SSRN: https://ssrn.com/abstract=3354570
9. Rana, D., Agarwal, I., & More, A. (2018, December). "A Review of Techniques to Combat The Peril of Fake News". In 2018 4th IEEE International Conference on Computing Communication and Automation (ICCCA), pp. 1-7, 2018. (SCOPUS)
10. Mahajan P., Rana D. "Investigating Clinical Named Entity Recognition Approaches for Information Extraction from EMR". In: Mehta M., Fournier-Viger P., Patel M., Lin J.CW. (eds) Tracking and Preventing Diseases with Artificial Intelligence. Intelligent Systems Reference Library, vol 206, 2022. Springer, Cham. https://doi.org/10.1007/978-3-030-76732-7_7 (SCOPUS)
11. Kenny Kumar M.J., Rana D. "High Average Utility Itemset Mining: A Survey" In: Chaki N., Pejas J., Devarakonda N., Rao Kovvur R.M. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 56. PP. 347-374, Springer, Singapore, 2021. https://doi.org/10.1007/978-981-15-8767-2_30. (SCOPUS)
12. Mathe John Kenny Kumar and Dipti Rana, "High Average Utility Itemset Mining: A Survey", In: Chaki, N., Pejas, J., Devarakonda, N., Rao Kovvur, R.M. (eds) Proceedings of 3rd International Conference on Computational Intelligence & Data Engineering (ICCIDE-2020), Hyderabad, India, June 12-13, Lecture Notes on Data Engineering and Communications Technologies, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-15-8767-2_30

Equipment

GPU Cooler Master

Processor : 6th Gen Intel Core i7
Motherboard : Asus H110, Memory : 16GB DDR4
HDD : 2TB SATA,
Graphic Card : NVIDIA 4GB 1050 TI
Cabinet : Cooler Master
Monitor : HP 22” IPS LED

DELL Optiplex 990

Intel Core i5
3.10 GHz Processor
4GB RAM
500GB HDD
17” TFT LCD

Contact


COED-111,
1st Floor , New Docs Building,
SVNIT , Surat - 395007
Gujarat , India