Nidhi Srivastava
Assistant Professor

With an impressive 15 years of professional experience, Dr. Nidhi Srivastava has contributed significantly to the academic community. Her expertise in Machine Learning has likely translated into impactful research, innovative teaching methods, and the development of cutting-edge curricula. Throughout her career, she has undoubtedly stayed abreast of the latest advancements in the dynamic field of ML, ensuring that her knowledge remains current and relevant.
Dr. Nidhi Srivastava is a distinguished expert at the forefront of technology, armed with a comprehensive academic journey encompassing BCA, MCA, M.Tech, and a PhD. Her research focus on Machine Learning, Artificial Intelligence, and Data Sciences underscores her commitment to innovation. Dr. Srivastava’s impressive publication record reflects her analytical prowess and groundbreaking contributions. Her remarkable academic journey is an inspiration, poised to shape the future of technology.
Beyond her academic contributions, Dr. Nidhi Srivastava’s professional journey may also include collaboration with industry experts, participation in conferences, and the publication of research papers. Such activities are crucial for bridging the gap between academia and industry, showcasing her commitment to practical applications of ML.

Qualification

  • PhD from Banasthali Vidyapith
    – Topic “Intelligent system design to predict software defect using Machine Learning”.
  • M.Tech from Karnataka State Open University, Mysure, 2010.
  • MCA from Guru Gobind Singh Indrapratha University, Delhi, 2006
  • BCA from Guru Gobind Singh Indrapratha University, Delhi, 2003.

Nidhi-Srivastava

Publications in Refereed Journals

  • A Survey Paper on: Discussing Factors of Web Technology with ML got published in JIMS 8i International Journal.
  • Srivastava, N., Agarwal, M. & Lamba, T. (2020). A Survey: Machine learning approach used in industry for bug prediction. High Technology Letters Journal 26 (9)/ 1812.
  • ABPET: An Automatic Software Bug Prediction using Ensemble Learning Technique. Neuro Quantology (ISSN 1303-5150), Volume 20,2022.

National Publications in Conferences

  • Social Engineering –The State of art Publised in Techno Tryst 2017.
  • Challenges And Security Issues In Cloud Published in NCETIT 2012.
  • “Experiential Learning”- An Innovative Learning Horizon Published in National Conference on “Striving & thriving towards diffusion of student-Driven Research in Science and Technology for inspired Learning” in the year 2014.
  • An overivew of the state-of-the-art Social Engineering: Attacks and their Management Published in NCETIT 2017.
  • Mobile Adhoc Networks: Challenges & Security issues Published in NCETIT 2018.

International Publications in Conferences

  • Srivastava, N., Lamba, T., & Agarwal, M. (2019, November). Comparative analysis of different machine learning techniques. In International Conference on Futuristic Trends in Networks and Computing Technologies (pp. 245-255). Springer, Singapore.[Springer Publication]
  • Srivastava, N., Agarwal, M., Bhardwaj, V., & Lamba, T. (2022, April). Optimization of Bug Detection Model (OBDM): By Evaluating Performance Metric using Artificial Intelligence. In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1423-1430). [IEEE Publication]
  • N. Srivastava, M. Agarwal, S. Arora and T. Lamba, “OPABP-Optimizing Parameters, to Improve Accuracy in Bug Prediction using Machine Learning,” 2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST), Delhi, India, 2022, pp. 1-6, doi: 10.1109/AIST55798.2022.10064852. [Scopus Indexed].

Patent Published

  • Patent Application Number 202311031989: Method for Prediction of Automatic Software Bug Using Ensemble Learning Technique.
  • Patent Application Number 202311031990: Method for Prediction of Bug for Optimizing Parameters and Improving Accuracy using Machine Learning.

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