JIIT

Academic Experts

Dr. Anita Sahoo

Associate Professor

anita.sahoo@jiit.ac.in

Biography

Dr. Anita Sahoo is an Associate Professor in the Department of Computer Science & Engineering and Information Technology, with over 26 years of teaching experience. She completed her Ph.D. in Medical Image Analysis in March 2017 and holds M.Tech. and B.E. degrees in Computer Science & Engineering.

She has taught core computer science subjects across undergraduate and postgraduate levels and has actively contributed to academic planning, student mentoring, and faculty development initiatives. Her professional journey reflects a consistent focus on quality teaching, research engagement, and collaborative development.

She is presently engaged in academic and research responsibilities, guiding doctoral scholars and participating in funded projects. She has served in multiple academic institutions, bringing with her a strong foundation in technical education and curriculum delivery.

Her career combines academic excellence with research-driven innovation, aiming to bridge theoretical foundations with practical applications in intelligent computing and data science.

Educational Qualifications

Ph.D (Computer Science & Engineering) from JIIT, NOIDA, March 2017., M.Tech. (Computer Science & Engineering) from U.P.T.U., B.E. (Computer Science & Engineering) from Utkal University, Odisha.

Research Highlights

Dr. Anita Sahoo’s research is focused on computational intelligence, quantum machine learning, and multimedia data analytics, particularly in the domain of medical image analysis. Her work addresses complex problems in pattern recognition, classification, and knowledge discovery using intelligent frameworks.

She has published over 45 research papers in reputed international journals and conferences and is currently supervising doctoral research in emerging AI domains. She has successfully guided three Ph.D. scholars.

She is the investigator of a government-funded research project on medical image analytics and has two granted Indian patents. Her research emphasizes the integration of domain expertise with data-driven techniques to create scalable, efficient, and explainable AI models.

Her recent interests include exploring quantum-inspired learning methods to optimize AutoML processes and applying AI in healthcare, education, and societal development. She actively contributes to the research ecosystem through collaborations, reviews, and scholarly activities.

Areas Of Interest

Computational Intelligence
Quantum Machine Learning
Medical Image Analysis
Multimedia Data Analytics

Publications

A. Sahoo and S. Chandra, “Multi‐Objective Grey Wolf Optimizer for Improved Cervix Lesion Classification,” Applied Soft Computing, vol. 52, pp. 64–80, Jan. 2017, doi: 10.1016/j.asoc.2016.12.022.
A. Padha and A. Sahoo, “QCLR: Quantum‐LSTM Contrastive Learning Framework for Continuous Mental Health Monitoring,” Expert Systems with Applications, vol. 238, art. 121921, Nov. 2023, doi: 10.1016/j.eswa.2023.121921.
B. Bansal and A. Sahoo, “Multi‐omics Data Fusion Using Adaptive GTO‐guided Non‐negative Matrix Factorization for Cancer Subtype Discovery,” Computer Methods and Programs in Biomedicine, vol. 228, art. 107246, Jan. 2023, doi: 10.1016/j.cmpb.2022.107246.
A. Padha and A. Sahoo, “MAQML: A Meta‐approach to Quantum Machine Learning with Accentuated Sample Variations for Unobtrusive Mental Health Monitoring,” Quantum Machine Intelligence, vol. 5, no. 1, pp. 1–17, Apr. 2023, doi: 10.1007/s42484-023-00108-1.
A. Padha and A. Sahoo, “Quantum Deep Neural Networks for Time Series Analysis,” Quantum Information Processing, vol. 23, no. 6, art. 205, Jun. 2024, doi: 10.1007/s11128-024-04404‐Y.