Dr. Smitha Rajagopal

Dr. Smitha Rajagopal earned her PhD from the Manipal Academy of Higher Education (MAHE). She also holds master’s and bachelor’s degrees from BMS College of Engineering, Bengaluru, and Presidency College, Bengaluru, respectively.

Her PhD dissertation is a fusion of cloud computing and machine learning, with a focus on deploying a cloud-based intrusion detection and prevention system. She has published her research in esteemed journals such as IEEE Access and Security and Communication Networks. In a relatively short span of time, her work has garnered numerous citations, showcasing its impact. Her H-index reflects a consistent track record of influential research.

• S. Rajagopal, P.  P.  Kundapur and K.  S.  Hareesha,  "Towards  Effective   Network Intrusion  Detection:  From  Concept  to  Creation  on  Azure  Cloud,"  in  IEEE  Access, Volume 9, 2021.
• Smitha Rajagopal,   Poornima   Panduranga   Kundapur,   Katiganere   Siddaramappa Hareesha,    "A    Stacking    Ensemble    for    Network    Intrusion    Detection    Using Heterogeneous Datasets", Security and Communication Networks, vol. 2020.
• Rajagopal, Smitha, Katiganere Siddaramappa Hareesha, and Poornima Panduranga Kundapur. "Optimizing Pair Programming in a Scholastic Framework:  A Design Pattern Perspective." J. Comput. Sci. 13, no. 6 (2017): 199-210.
• Rajagopal, Smitha,   Poornima   Panduranga   Kundapur,   and   Hareesh   Katiganere Siddaramappa.  "A predictive model for network intrusion detection using stacking approach." International Journal of Electrical and Computer Engineering, vol. 10, no. 3 (2020): 2734.
• Rajagopal, Smitha, Katiganere Siddaramappa Hareesha, and Poornima Panduranga Kundapur. "Performance   analysis   of   binary   and   multiclass   models using   azure machine learning."  International Journal of Electrical & Computer Engineering (2088-8708) 10, no. 1 (2020).
• Smitha, Rajagopal, K. S. Hareesha, and Poornima Panduranga Kundapur. "A machine learning approach   for   web   intrusion   detection:   MAMLS   perspective."   In   Soft Computing and Signal Processing, pp. 119-133. Springer, Singapore, 2019.
• Rajagopal, Smitha, Katiganere Siddaramappa Hareesha, and Poornima Panduranga Kundapur. "Feature Relevance Analysis and Feature Reduction of UNSW NB-15 Using Neural Networks on MAMLS." In Advanced Computing and Intelligent Engineering, pp. 321-332. Springer, Singapore, 2020.

Patents

• System and Method for Network Intrusion Detection, filed on September 26 2021 (Indian Patent), Status: Published, PCT/IB2021/062303
• A system for Feature Relevance Analysis and Feature Reduction on Microsoft Azure Machine learning studio, German patent, Status: Granted, 202023100327

Workshops / FDPs attended

• Two-Day workshop  on  Machine  learning  organized  under  the  aegis  of  Dr.  T.M.A.  Pai Endowment, Data Analytics and Cloud Computing on 9th and 10th October 2015.
• One-Day National  Workshop  on  Cyberspace  Security:  Digital  India  Context  held  at  NITK, Surathkal on 17th October 2015.
• One-week National level faculty development program on Machine Learning conducted at JNTUH, Hyderabad from April 11-16, 2016.
• Two-week short   course   on   Certified   Ethical   Hacking   organized   by   Indian   Institute   of Information Technology and Management, Kerala during November 23-December 4, 2015 at Thiruvananthapuram.
• three-Day workshop on Open-source Network Experimentation (ONE-2017) conducted at NITK, Surathkal during June 1st to 3rd, 2017.
• One-Day faculty development program on Machine Learning held at MIT, Manipal on 22-11-2019.
• Two-Day workshop   on   Clustering   in   Machine   Learning   held   at   MIT,   Manipal during September 26-27, 2016.
• Two-day workshop  on  Cloud  computing  held  at  Mangalore  University  on  4th  and  5^th February, 2015 in association with IIT, Bombay.
• Statistics for Data Analytics (Series-1) conducted by Rajagiri School of Arts & sciences, Kochi, Kerala, 3rd to 7th August 2021
• Technology Roadmap  for  Emerging  Future  conducted  by  CDAC  Pune,  17th-18th  July and23rd-25th July 2021
• VGST sponsored four days online FDP on Recent trends in computational intelligence and analytics conducted by RVCE, Bangalore, 17th to 20th January 2022
• Short Term   Training   Program   (STTP)   on   “Art   of   Algorithm   Writing   and   Computer Programming” conducted by NIT, Warangal, 24th to 28th January 2022
• One Week Faculty Development Programme on "Disruptive Technologies and Challenges in Data Science,  Artificial  Intelligence  and Machine  learning"  conducted  by  Dayananda  Sagar College of Engineering, Bangalore.
• Workshop On Capacity Building Program in Cybersecurity & Its Investigation Date: 01-10 May 2023.

Awards Won

• Dr. T M A Pai PhD scholarship, 2015

Poster Presentation

• Presented a research poster at the Manipal Research Colloquium -2018.

Paper Presentation

• Presented a paper “A Generalized Predictive Analytics Workflow for Intrusion Detection on Microsoft Azure” at the Manipal Research Colloquium -2018.