• Ph. D. (Computer Science Engineering), USICT, GGSIPU, NEW DELHI 
• M. Tech. (CSE), Amity University, Noida, Uttar Pradesh
• UGC NET and GATE qualified
• Master of Computer Applications
• B. Sc.(H) Physics

• Assistant Professor, ARSD College, University of Delhi since January 2011 

• Quantum Computing
• Mathematical Modelling of Infectious Disease Dynamics and Prediction
• Machine Learning
• Artificial Neural Network
• Numerical Optimization and Operations Research
• Mathematical modeling of infectious disease dynamics and prediction

[1] L. K. Shrivastav and R. Kumar, “Empirical analysis of impact of weather and air pollution parameters on COVID-19 spread and control in India using Machine Learning Algorithm”, Wireless Personal Communications (SCIE, Impact Factor: 2.01), Springer, 2023, DOI: https://doi.org/10.1007/s11277-023-10367-7.

[2] L. K. Shrivastav and R. Kumar, “Adaptive trio-ensemble deep neural network for high-frequency stock price prediction”, Wireless Personal Communications (SCIE, Impact Factor: 2.01), Springer (Under process, preprint version available), 2022.

[3]   L. K. Shrivastav and S. Jha, "A gradient boosting machine learning approach in modeling the impact of temperature and humidity on the transmission rate of COVID-19", Applied Intelligence, Springer, 2020, https://doi.org/10.1007/s10489-020-01997-6

[4].  L. K. Shrivastav and R. Kumar, "Gradient Boosting Machine and Deep Learning approaches in big data analysis: a case study of stock market", Journal of Information Technology Research, IGI Global, Volume 15, Issue 1, Article 1, 2022 DOI: 10.4018/JITR.2022010101.

[5].  L. K. Shrivastav and R. Kumar, "An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning methods for Stock Price Prediction", Journal of Information Technology Research, IGI Global, Volume 15, Issue 1, Article 2, 2022, DOI: 10.4018/JITR.2022010102.

[6]   L. K. Shrivastav and R. Kumar, "High Frequency Stochastic Data Analysis using Machine Learning Framework - A Comparative Study", Cognitive Computing Systems Applications and Technological Advancements, Apple Academic Press, Taylor & Francis, pp 1-29, 2021.

[1]   L. K. and R. Kumar "An Empirical Analysis of Stock Market Price Prediction using ARIMA and SVM,", 6th International Conference on Computing for Sustainable Global Development (INDIACom), pp 173-178, IEEE, 2019.

[2]   L. K. Shrivastav and R. Kumar, "A Novel Approach towards the Analysis of Stochastic High Frequency Data Analysis using ARIMA Model", International Journal of Information Systems & Management Science, Vol. 2, No. 2, Elsevier,2019 .

[3]   L. K. Shrivastav and R. Kumar, "A comprehensive survey of applications of Machine Learning Techniques in Stock Market Prediction", International Conference on "Computing for Sustainable Global Development, pp. 2316-2321,  IEEE, 2018.

[4]  A. Puri and L. K. Shrivastav, "Converting Thought to Speech Using Deep Learning Algorithms", 5th International Conference on "Computing for Sustainable Global Development", 14th - 16th March, IEEE, 2018.

• Member, College Information Technology Cell (ITC)
• Member, College NIRF Committee
• Member, College Website Committee
• Member, College Technical Team
• Member, College Online Help and Grievances Committee
• Member, College Seminar Committee
• Member, College Admission Committee
• Member of (IAASSE) International Association of Academicians.