Ms. Preeti Agarwal

Assistant Professor,

School of Technology Management & Engineering

PhD (CS, Jamia Millia Islamia)- Thesis Submitted, M.Tech (CSE, Uttrakhand Technical University), B.Tech – with Hons (CS, Kurukshetra University)

Email: preeti.agarwal@nmims.edu

Major Achievements, Awards and Honors

• Thrice Qualified UGC – NET exam Dec 2013, June 2018, and Dec 2018.
• Twice Qualified GATE exam with 98.05 and 97 percentiles.
• Second rank holder in M.Tech.
• Teaching Excellence award by COER University, Roorkee (2012-13).
• Best research paper award in Smart Cities—Opportunities and Challenges: ICSC 2019 (pp. 231-244). Springer Singapore. 

Teaching Experience

13 Years 

Teaching Interest

Design and analysis of algorithms, Database Systems, Big Data analytics, Internet of Things, Deep Learning and Machine Learning. 

Professional Activities

• Reviewer of various SCI/SCIE, Scopus indexed journals and International Conferences.
• ACM membership.
• Member of organizing committee of various International Conferences.
• Guided 02 M.Tech Dissertations.
• Paper Setter for UTU, Dehradun. 

Research Publications

• Agarwal, P., & Alam, M. (2022). Edge optimized and personalized lifelogging framework using ensembled metaheuristic algorithms. Computers and Electrical Engineering, 100, 107884, Elsevier. (SCIE/Scopus, IF=4.3)
• Agarwal, P., & Alam, M. (2023). A Lightweight Neuromorphic CNN for Human Activity Recognition on Edge Device. In 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 632-637). IEEE.
• Agarwal, P., & Alam, M. (2023) "Knowledge Mapping of Human Activity Recognition Techniques for Assistive Living”. International Journal of Sensors, Wireless Communications, and Control, Volume 13(4), pp. 203-225, Bentham Science.
• Agarwal, P., & Alam, P. "Mapping the Landscape of Research on Human Activity Recognition for Chronic Disease Management.” Artificial Intelligence in Biomedical and Healthcare Informatics. Elsevier. (In Press)
• Agarwal, P., & Alam, M. (2022). Quantum-Inspired Support Vector Machines for Human Activity Recognition in Industry 4.0. In Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1 (pp. 281-290). Springer Singapore.
• Agarwal, P., & Alam, M. (2021). Exploring Quantum Computing to Revolutionize Big Data Analytics for Various Industrial Sectors. In Big Data Analytics (pp. 113-130). Taylor and Francis
• Agarwal, P., & Alam, M. (2020). A lightweight deep learning model for human activity recognition on edge devices.Procedia Computer Science, 167, 2364-2373.
• Agarwal, P., & Alam, M. (2020). Investigating IoT middleware platforms for smart application development. In Smart Cities—Opportunities and Challenges: Select Proceedings of ICSC 2019 (pp. 231-244). Springer Singapore.
• Agarwal, P., & Alam, M. (2020). Open service platforms for IoT. Internet of Things (IoT) Concepts and Applications, 43-59, Springer Singapore.