Ms. Sarishty Gupta

Education

• M.Tech (Computer Science & Engineering) from National Institute of Technology (NIT), Jalandhar in July,2016.
• B.Tech (Computer Science & Engineering) from Kurukshetra University in July, 2013.

Other Qualifications

• GATE (Computer Science & Information Technology) with 98.9 percentile in 2014 

Biography

In my teaching experience, I have taught Object Oriented Programming, Computer Systems and Programming, Software Development Fundamentals, Software Engineering, Data Structures & Algorithms, Operating System, Software Development Principles and Practices, Fundamentals of Computer Programming    

Work Experience

Teaching Experience:

• Presently working as an Assistant Professor in the Department of Computer Science & Information Technology at Jaypee Institute of Information Technology (JIIT), Sector 62, Noida, U.P. from 03-08-2017 to till date.
• Worked as Guest Faculty in Department of Computer Science, in Malaviya National Institute of Technology (MNIT), Jaipur from January-May, 2017.

Interest Area

• Software Engineering: Program comprehension, static and dynamic program analysis, software evolution, calling context profiling, Data Analytics.

Publications

• Sarishty Gupta, Paramvir Singh. "Comprehending scenario-level software evolution using calling context trees." In 2017 International Conference on Information Technology (ICIT), pp. 125-130. IEEE, 2017.
• Saquib NadeemHashmi, Harsh Gupta, Dhruv Mittal, Kaushtubh Kumar, Aparajita Nanda, and Sarishty Gupta. "A lip reading model using CNN with batch normalization." In 2018 eleventh international conference on contemporary computing (IC3), pp. 1-6. IEEE, 2018.
• Charu Goyal, Vaibhav Aren, and Sarishty Gupta. "Outlier Detection Using Trust Assessment Scheme in Wireless Sensor Networks." In High Performance Vision Intelligence, pp. 71-81. Springer, Singapore, 2020
• A. Chandak, A. Singh, S. Mishra and S. Gupta, "Virtual Bazar-An Interactive Virtual Reality Store to Support Healthier Food Choices," 2022 1st International Conference on Informatics (ICI), 2022, pp. 137-142, doi: 10.1109/ICI53355.2022.9786879.
• Aggarwal, A., Kushwaha, A.K., Rastogi, S., Lal, S., Gupta, S. (2022). Characterization and Prediction of Various Issue Types: A Case Study on the Apache Lucene System. In: Khanna, A., Gupta, D., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1394. Springer, Singapore. https://doi.org/10.1007/978-981-16-3071-2_7
• Nanda, A., Manju, Gupta, S. (2022). Breast Cancer Prediction Models: A Comparative Study and Analysis. In: Poonia, R.C., Singh, V., Singh Jat, D., Diván, M.J., Khan, M.S. (eds) Proceedings of Third International Conference on Sustainable Computing. Advances in Intelligent Systems and Computing, vol 1404. Springer, Singapore. https://doi.org/10.1007/978-981-16-4538-9_41
• Nanda, A., Tuteja, S., & Gupta, S. (2022). Machine learning based analysis and prediction of college students' mental health during COVID-19 in India. In Artificial Intelligence, Machine Learning, and Mental Health in Pandemics (pp. 167-187). Academic Press.