Birla Institute of Technology, Mesra
Faculty Image

Dr. Mansi Gupta

Joined Institute on : 11-Aug-2023

  • Assistant Professor
  • Computer Science
  • Ph.D., M.Tech, B.Tech
Contact Address

Same as Permanent Address

Itki Road, Bazra, Ranchi - 834005

  • Phone Office - 8580164644
  • Phone Residence - N.A.
  • Email - gmansi@bitmesra.ac.in
Work Experience

Teaching : 3 Years

Research : 3.5 Years

Individual: 1 Years
Professional Background

 

  • Assistant Professor, Department of Computer Science, Birla Institute of Technology, Mesra (Lalpur) from 4th November’2024 till date.
  • Visiting Assistant Professor, Department of Computer Science, Birla Institute of Technology, Mesra (Lalpur) from 11th August 2023 to November’24
  • Worked as an Assistant Professor in Dept. of Faculty of Science and Technology, ICFAI University, Jharkhand from Feb’2023 to August’23.
  • Full Time (IRF) PhD Research Scholar (July 2019 – Jan 2023) at Dept. of Computer Science & Engineering, Birla Institute of Technology, Mesra.
  • Worked as an Assistant Professor in Dept. of Computer Science, Institute of Professional Excellence & Management (IPEM), Ghaziabad from July’2017- Nov’2018.

 
Research Areas

Software fault prediction, Software Engineering, Machine Learning, Neural Networks 
Publications
  1. K. Kouser, A. Priyam, M. Gupta, S. Kumar, and V. BHATTACHARJEE, “Genetic Algorithm based optimization of Clustering Algorithms for the Healthy Aging Dataset,” May 2024, doi: 10.20944/preprints202405.1663.v1.(SCIE)
  2. M. Gupta, K. Rajnish, and V. Bhattacharjee, “Software fault prediction with imbalanced datasets using SMOTE-Tomek sampling technique and Genetic Algorithm models,” Multimedia Tools and Applications, vol. 83, no. 16, pp. 47627–47648, Oct. 2023, doi: 10.1007/s11042-023-16788-7.(SCIE)
  3. M. Gupta, K. Rajnish, and V. Bhattacharya, “Effectiveness of Ensemble Classifier Over State-Of-Art Machine Learning Classifiers for Predicting Software Faults in Software Modules,” Machine Learning, Image Processing, Network Security and Data Sciences, pp. 77–88, 2023, doi: 10.1007/978-981-19-5868-7_7 (Scopus).
  4. M. Gupta, K. Rajnish, and V. Bhattacharjee, “Cognitive Complexity and Graph Convolutional Approach Over Control Flow Graph for Software Defect Prediction,” IEEE Access, vol. 10, pp. 108870–108894, 2022, doi: 10.1109/access.2022.3213844 (SCIE).
  5. K. Rajnish, V. Bhattacharjee, and M. Gupta, “A Novel Convolutional Neural Network Model to Predict Software Defects,” Fundamentals and Methods of Machine and Deep Learning, pp. 211–235, Jan. 2022, doi: 10.1002/9781119821908.ch9 (Scopus).
  6. M. Gupta, K. Rajnish, and V. Bhattacharjee, “Impact of Parameter Tuning for Optimizing Deep Neural Network Models for Predicting Software Faults,” Scientific Programming, vol. 2021, pp. 1–17, Jun. 2021, doi: 10.1155/2021/6662932 (SCIE).
  7. M. Gupta, K. Rajnish, and V. Bhattarcharjee, “Predicting Software Cost Through Entity–Relationship Diagrams: An Empirical View,” Lecture Notes in Electrical Engineering, pp. 561–567, Nov. 2020, doi: 10.1007/978-981-15-7486-3_51 (Scopus).
  8. A. G. Dinker, V. Sharma, M. Gupta, and N. Singh, “Multilevel authentication scheme for security critical networks,” Journal of Information and Optimization Sciences, vol. 39, no. 1, pp. 357–367, Nov. 2017, doi: 10.1080/02522667.2017.1374745.(ESCI)