Dr. Kusum Lata

Dr. Kusum Lata is Assistant Professor at Delhi School of Management, DTU. She has done her B. Tech in Computer Science and Engineering from Punjab Technical University, Punjab and Master of Engineering (M.E.) in Computer Technology and Applications from Delhi College of Engineering, University of Delhi (Presently Delhi Technological University). She has completed her Ph.D. in Computer Science and Engineering from Delhi Technological University. She has qualified UGC-NET in Computer Science and Applications. She has more than 10 years of teaching and research experience. She has published papers in various reputed International Journals like Software Quality Journal, Soft Computing, Neurocomputing and International Conferences.  Her area of interest includes Machine Learning, Data Mining, Data Analytics, Database Management Systems, Improving Software Quality, Definition and Validation of Software Metrics. She has been recognized with commendable research award for excellence in research from DTU in 2020 and 2021. 

 

• Assistant Professor, HMR Institute of Technologu and Managemnt, Affilaited to Guru Gobind Singh Intraprastha University, Delhi ( July 2008-July 2014)
• Assistant Progessor, Department of Computer Sc. & Engg., Delhi Technological University, Delihi (July 2014- Sept 2018)
• Assistant Professor, USME, East Delhi Campus, Delhi Technological University, Delhi Technological University, Delihi (Sept 2018- Aug. 2025)
• Assistant Professor, Delhi School of Management, Delhi Technological University, Delhi Technological University, Delihi (Aug. 2025-Till Date)

 

• Machine Learning
• Data Warehousing and Data Mining
• Programming using Python
• Object Oriented Programming
• Applied Business Analytics and Intelligence
• Database Management Systems
• E-Learning and Knowledge Management
• Business Intelligence
• Management Information Systems
• E-Commerce
• Algorithm Design and Analysis
• Programmin using C 
• Operating System
• Software Engineering
• Computer and Programming Fundamentals

Member, IEEE

• Malhotra, Ruchika, and Kusum Lata. "An empirical study on predictability of software maintainability using imbalanced data." Software Quality Journal 28.4 (2020): 1581-1614. (SCIE)
• Malhotra, Ruchika, and Kusum Lata. "A systematic literature review on empirical studies towards prediction of software maintainability." Soft Computing 24, no. 21 (2020): 16655-16677.(SCIE)
• Malhotra, Ruchika, and Kusum Lata. "An exploratory study for predicting maintenance effort using hybridized techniques." In Proceedings of the 10th innovations in software engineering conference, pp. 26-33. 2017.
• Malhotra, Ruchika, and Kusum Lata. "An empirical study to investigate the impact of data resampling techniques on the performance of class maintainability prediction models." Neurocomputing 459 (2021): 432-453. (SCIE)
• Malhotra, Ruchika, and Kusum Lata. "Handling class imbalance problem in software maintainability prediction: an empirical investigation." Frontiers of Computer Science 16 (2022): 1-14. (SCIE)
• Malhotra, Ruchika, and Kusum Lata. "On the application of cross-project validation for predicting maintainability of open source software using machine learning techniques." In 2018 7th international conference on reliability, Infocom technologies and optimization (trends and future directions)(ICRITO), pp. 175-181. IEEE, 2018.
• Sharma, Nidhi, Anchal Pathak, B. Latha Lavanya, Naval Garg, and Kusum Lata. "Exploring the psychometric properties of personal optimism and self-efficacy optimism-extended (POSO-E) scale among Indian teachers." Benchmarking: An International Journal 30, no. 7 (2023): 2234-2247. (Scopus Indexted)
• Lata, Kusum, and Naval Garg. "Predicting non-violent work behaviour among employees using machine learning techniques." International Journal of Conflict Management 34, no. 5 (2023): 931-944. (ABDC A)
• Malhotra, Ruchika, and Kusum Lata. "Using ensembles for class-imbalance problem to predict maintainability of open source software." International Journal of Reliability, Quality and Safety Engineering 27, no. 05 (2020): 2040011. (ESCI)
• Rao, Kunal, Pawan Raj Gopal, and Kusum Lata. "Computational analysis of machine learning algorithms to predict heart disease." In 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 960-964. IEEE, 2021.
• Malhotra, Ruchika, and Kusum Lata. "Improving software maintainability predictions using data oversampling and hybridized techniques." In 2020 IEEE Congress on Evolutionary Computation (CEC), pp. 1-7. IEEE, 2020.
• Malhotra, Ruchika, and Kusum Lata. "Analysis of hybridized techniques with class imbalance learning for predicting software maintainability." International Journal of Reliability, Quality and Safety Engineering 30, no. 02 (2023): 2350006. (ESCI)
• Lata, Kusum. "On the efficacy of boosting-based ensemble learning techniques for predicting employee absenteeism." In Computational Intelligence: Select Proceedings of InCITe 2022, pp. 179-187. Singapore: Springer Nature Singapore, 2023.
• Lata, Kusum, and Naval Garg. "Predicting Leadership Flexibility Using Supervised Learning Techniques." Global Journal of Flexible Systems Management (2025): 1-16. (ABDC A)
• Tayal, Charu, Rajesh Sharma, and Kusum Lata. "Examining maternal healthcare service utilization as a determinant of child health outcomes in India: Demographic and Health Survey 2019–21." Children's Health Care (2025): 1-22.
• Tayal, Charu, Rajesh Sharma, and Kusum Lata. "Association between women’s autonomy and reproductive health outcomes in India." Journal of Medicine, Surgery, and Public Health 4 (2024): 100156.
• Tayal, Charu, Rajesh Sharma, and Kusum Lata. "Concomitant Factors Influencing Breastfeeding Practices in India: Evidence from Demographic and Health Survey 2019–21." Global Social Welfare (2025): 1-14. (ESCI)
• Malhotra, Ruchika, and Kusum Lata. "Tackling the Imbalanced Data in Software Maintainability Prediction Using Ensembles for Class Imbalance Problem." Advances in Interdisciplinary Research in Engineering and Business Management (2021): 391-399.

 

Computer Graphics and Multimedia, TechIndia Publications

• Received Commendable Research Award From Delhi Technogocial University, 2020
• Received Commendable Research Award From Delhi Technogocial University, 2021