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Academic Experts
Dr. Bhavana Bansal

Biography


I hold a Ph.D. in Computer Science and Engineering with a specialization in meta-heuristic techniques for omics data analysis, along with an M.Tech and B.Tech in Computer Science. I am currently working as an Assistant Professor (Senior Grade) at JIIT Noida. I also have prior teaching experience as an Assistant Professor at KIET Group of Institutions Ghaziabad. My academic and research work focuses on machine learning, artificial intelligence, and optimization techniques, with multiple publications in reputed SCI/SCOPUS-indexed journals and conferences. 

Research Highlights

My research focuses on applying optimization-driven machine learning techniques to complex biomedical data, particularly in multi-omics integration, clustering, and gene regulatory network reconstruction. I proposed an enhanced Honey Badger Algorithm for multi-view subspace clustering, improving consensus representation and clustering accuracy across heterogeneous datasets. I also developed adaptive and chaotic variants of the Gorilla Troops Optimizer (GTO)-guided Non-negative Matrix Factorization (NMF) for effective multi-omics data fusion and cancer subtype discovery, addressing challenges of high dimensionality and data heterogeneity. 

Additionally, I introduced an intelligent framework for reconstructing gene regulatory networks with controlled behavior, enabling better modeling of gene interactions. Overall, my work demonstrates the effectiveness of combining metaheuristic optimization with machine learning to deliver robust, scalable, and interpretable solutions for biomedical data analysis and precision medicine. 

Areas of Interest
  • Machine Learning
  • Artificial Intelligence
  • Computational Intelligence
Publications
  •  Bhavana Bansal, Anita Sahoo, “Enhanced honey badger algorithm for multi-view subspace clustering based on consensus representation”, Soft Computing, Publisher: Springer, 2025, Indexed in: SCIE.
  • Bhavana Bansal, Anita Sahoo, “Multi-omics data fusion using adaptive GTO guided Nonnegative matrix factorization for cancer subtype discovery”, Computer Methods and Programs in Biomedicine, Vol. 228, 2022, 107246, ISSN 0169-2607, https://doi.org/10.1016/j.cmpb.2022 .107246., Publisher: Elsevier, Indexed in: SCI.
  • Bhavana Bansal, Anita Sahoo, “Chaotic driven gorilla troops optimizer based NMF approach for integrative analysis of multiple source data”. Int. j. inf. Tecnol, 2022. https://doi.org/10.1007/s41870-022-00928-7. Publisher: Springer, Indexed in: SCOPUS.
  • Bhavana Bansal, Aparajita Nanda, Anita Sahoo, “Intelligent Framework with Controlled Behavior for Gene Regulatory Networks Reconstruction”, International Journal of Information Retrieval Research (IJIRR), 12(1), 1-17, 2022. http://doi.org/10.4018/IJIRR.2022010104, Publisher: IGI Global, Indexed in: ESCI.