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Santosh Thakur
Assistant Professor
santosh.thakur@mahindrauniversity.edu.in
Thakur Santosh is an Assistant Professor in the Centre for Life Sciences at Mahindra University. He earned the Doctor of Philosophy in Knowledge Capturing and Analysis of Big Data from Department of Computer Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad. He has nine years of experience in teaching and research.
2021
- Ph.D from Indian Institute of Technology (Indian school of Mines), Dhanbad in 2021.
2012
- M.Tech (CSE) from Jawaharlal Nehru Technological University -Hyderabad -in 2012.
2022
- Assistant Professor in Woxsen University, Hyderabad from June-2021 to July-2022.
2021
- Assistant Professor in DIT University, Dehradun from Jan- 2013 to Feb-2021.
Journals :
2022
- Thakur, S., Dharavath, R., Shankar, A., Singh, P., Diwakar, M., & Khosravi, M. R. (2022). RST-DE: Rough Sets-Based New Differential Evolution Algorithm for Scalable Big Data Feature Selection in Distributed Computing Platforms. Big Data.
2020
- Thakur, S., Dharavath, R., & Edla, D. R. (2020). Spark and Rule-KNN based scalable machine learning framework for EEG deceit identification. Biomedical Signal Processing and Control, 58, 101886.
- Santosh, T., Ramesh, D., & Reddy, D. (2020). LSTM based prediction of malaria abundances using big data. Computers in Biology and Medicine, 124, 103859.
- Santosh, T., & Ramesh, D (2020). Machine Learning Approach on Apache Spark for Credit Card Fraud Detection Machine Learning Approach on Apache Spark for Credit Card Fraud Detection.
2019
- Thakur, S., & Dharavath, R. (2019). Artificial neural network-based prediction of malaria abundances using big data: A knowledge capturing approach. Clinical Epidemiology and Global Health, 7(1), 121-126.
Conferences :
2019
- Santosh, T., & Ramesh, D. (2019, May). DENCLUE-DE: Differential Evolution Based DENCLUE for Scalable Clustering in Big Data Analysis. In International Conference on Computer Networks and Inventive Communication Technologies(pp. 436-445). Springer, Cham.
2018
- Thakur, S., & Dharavath, R. (2018). KMDT: A Hybrid Cluster Approach for Anomaly Detection Using Big Data. In Information and Decision Sciences(pp. 169-176). Springer, Singapore.
2017
- Santosh, T., & Ramesh, D. (2017, October). Spark Based ANFIS Approach for Anomaly Detection Using Big Data. In International Conference on Next Generation Computing Technologies(pp. 450-458). Springer, Singapore.
Current research interests in the areas of Data Science, Machine learning and Blockchain.