Prof. Atul Bengeri


NAME : Prof. Atul Bengeri
DESIGNATION : Professor of Practice
QUALIFICATION : B.E, M.S (BITS, Pilani), Ph.D (Pursuing)

  • Ph. D. (Pursuing), SPPU, Pune
  • MS (Software Systems), BITS, Pilani, 2002.
  • PG in Computer Applications, University of Mysore, 1997
  • B.E (Polymer Science and Technology Engineering), SJCE, Mysore, 1996.

OVERVIEW OF PROFILE :

An Industry-Academia-Entrepreneur, Coach and Mentor with extensive experience in the Corporate world having worked in Fortune 500 MNCs like Siemens, Intel, Dell-EMC and also associated with Academia across India and Asia-Pacific region having worked closely with a few International Universities like Victoria University & RMIT University - Australia, Sunway University - Malaysia, National University of Singapore (NUS) and Singapore Management University - Singapore Kellog’s University – US, ISB, IIT-Palakkad, IIMK – India.

An EdTech, HealthTech, AgriTech, SmartTech Techpreneur having been an integral part of the UG, PG and Executive Education sector with Universities in the APAC region.

FORE FRONT AREA OF RESEARCH : Digital Transformation, IoT, Big Data, Machine Learning, Deep Learning, AI.
EMAIL ID : atul.bengeri@mitaoe.ac.in
CONTACT NO : 02030253500
EXPERIENCE : Teaching: 18, Industry: 25, Research: 15


  • GATE 2012 Qualified.
  • Nominated for “Best Researcher Award” under the category of International Research Awards on Cybersecurity and Cryptography.

RESEARCH PROJECTS

  • “Development of Application program to simplify the use of Unified Development Control and Promotion Regulations Maharashtra State” (Seed funding received Rs. 2.2 Lakhs in 2022).
  • “Feature relevance analysis for traffic classification in flow based intrusion detection system” (Seed funding received 60K in 2018.

PUBLICATIONS

  • “Feature selection using principal component analysis and genetic algorithm”, Journal of Discrete Mathematical Sciences and Cryptography (eSCI and Scopus Journal), Volume-23, Issue-2, 2020, pp.-595-602.
  • Ensemble of Bio-inspired Algorithm with Statistical Measures for Feature Selection to Design a Flow-Based Intrusion Detection System”, The International Journal of Next-Generation Computing (eSCI), Volume-13, Issue-4, 2022, pp.-901-912.
  • “Ensemble of Statistically Based Methods for Identifying Features in Intrusion Detection System”, DEGRES JOURNAL, ISSN NO:0376-8163, vol. 9, Issue 4, 2024, ISSN NO:0376-8163

BOOK CHAPTERS


  • “Feature Engineering for Flow‐Based IDS”, Book Title- Wireless Communication Security, Publisher- John Wiley & Sons, Inc., 2022, pp. 69-90.

INTERNATIONAL CONFERENCES

  • “Feature Selection Based on Hall of Fame Strategy of Genetic Algorithm for Flow-Based IDS”, In: Shukla, S., Unal, A., Kureethara, J.V., Mishra, D.K., Han, D.S. (eds) Data Science and Security. Lecture Notes in Networks and Systems, vol. 290. Springer, Singapore.
  • "An Intrusion Detection System for Zero-Day Attacks to Reduce False Positive Rates," 2022 International Conference for Advancement in Technology (ICONAT), 2022, pp. 1-6.
  • "Ensemble Based Feature Selection Technique for Flow Based Intrusion Detection System," 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 2022, pp. 1-4.
  • "Performance-Based Feature Selection Using Decision Tree," 2019 International Conference on Innovative Trends and Advances in Engineering and Technology (ICITAET), 2019, pp. 135-138.
  • "Ensemble-Based Filter Feature Selection Technique for Building Flow-Based IDS," 2021 2nd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS), 2021, pp. 324-328.

PAPERS ACCEPTED FOR PUBLICATION

  • “Exploring the Efficiency: A Comprehensive Analysis of Machine Learning Algorithms in WEKA Software” accepted for Special Issue On: Data Analytics For Sustainable Management Systems, Journal Of Statistics And Management Systems (JSMS).