+91-120-2594300/400
Academic Experts
Academic Experts
Ankita Verma
ASSISTANT PROFESSOR (SR GRADE)
ankita.verma@mail.jiit.ac.in
Biography

Dr. Ankita Verma holds a Ph.D. in Computer Science & Engineering from Jawaharlal Nehru University (JNU), New Delhi (2018). Prior to that, she earned her M.Tech in. Computer Science & Engineering from JNU, securing the first rank (2012–2014), and a B.Tech. in Computer Science & Engineering from United College of Engineering and Research (U.P.T.U). Currently, she serves as a faculty member at JIIT Noida, where she has been contributing to the academic community since September 2017. Her research interests include Machine Learning, Pattern Recognition, Social Network Analysis, and Computational Intelligence.

Dr. Verma has received prestigious recognition, including the Senior Research Fellowship (SRF) and Junior Research Fellowship (JRF) from the University Grants Commission (UGC). She also secured the first rank in the JNU entrance exam for M.Tech. admission in 2012. With over three years of teaching experience, Dr. Verma has taught a variety of core subjects such as C++ Programming, Discrete Mathematics, Artificial Intelligence, Machine Learning, Data Science and Nature Inspired Computing. She has successfully supervised numerous undergraduate and postgraduate projects and theses. Currently, three Ph.D. scholars are pursuing their research under her guidance. Dr. Verma has authored several research papers published in reputed national and international journals and conferences. Her work primarily focuses on the development and application of machine learning algorithms to real-world problems, contributing to advancements in both theoretical and applied aspects of her field.

Research Highlights

Dr. Ankita Verma’s research interests span Machine Learning, Pattern Recognition, Social Network Analysis, Computational Intelligence, Intelligent Systems, and Large-Scale Graph Analysis. During her PhD, she focused on detecting communities in heterogeneous social networks, addressing the complexity introduced by diverse entity and relation types. Recently, she has extended her work to recommender systems, sentiment analysis, and machine learning applications for sustainable development goals.

Areas Of Interest
  • Machine Learning
  • Pattern Recognition
  • Social Network Analysis
  • Computational Intelligence
  • Meta-heuristic Optimization
Publications

Verma, A., & Bharadwaj, K. K. (2017). Identifying community structure in a multi‐relational network employing non‐negative tensor factorization and GA k‐means clustering. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(1). 1-26.

  1. Verma, A., & Kumar, S. (2021). Routing protocols in delay tolerant networks: Comparative and empirical analysis. Wireless Personal Communications, 118(1), 551-574.
  2. Savita, Verma, A. Eigen Vector Centrality (EVC) Routing for Delay Tolerant Networks: A Time Associated Matrix-Based Approach. Wireless Pers Commun 128, 1217–1233 (2023). https://doi.org/10.1007/s11277-022-09996-1
  3. Verma, A., Agarwal, A., Rathore, M., Bisht, S., & Singh, D. (2023). Preferential Selection of Software Quality Models Based on a Multi-Criteria Decision-Making Approach. International Journal of Software Innovation (IJSI), 11(1), 1-13.
  4. Singh, D., & Verma, A. (2025). An Overview of Heterogeneous Social Network Analysis. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 15(2), e70028.