IIT Delhi - Abu Dhabi

Research Areas

Underwater Acoustic Communication and Visible Light Communication Array Signal Processing and Sparse/Nested Array Design Direction of Arrival (DoA) Estimation and Beamforming GNSS Signal Design Medical Signal & Image Processing (ECG, EEG, Fundus, MRI, Ultrasound) AI & Deep Learning for Healthcare Quantum Machine Learning and Quantum Communication

Biosketch

Prof. Monika Aggrawal is a Professor at IIT Delhi. She received her Doctor of Philosophy (Ph.D.) in Electrical Engineering from IIT Delhi in 1999. Her research focuses on array signal processing and underwater communication systems, with strong contributions to sparse array design, high-resolution direction-of-arrival estimation, beamforming, and time-reversal techniques. She has also made impactful contributions in medical signal and image processing and quantum machine learning.

She has led and co-led funded research projects exceeding INR 25 Crores and has an extensive publication record in leading IEEE and Elsevier journals.

Leadership & Service

Associate Editor, IEEE Signal Processing Letters

Editor-in-Chief, IETE Journal of Research

Senior Editor, Sādhanā – Academy Proceedings in Engineering Sciences

Guest Editor, IEEE Journal of Selected Topics in Signal Processing

Chairperson, IEEE Signal Processing Society Delhi Section

Faculty Mentor, IEEE-OES, IEEE-WIE, IEEE-SP and MTS Student Branches (IIT Delhi)

Recent Publications
  • Kumar, R., Agrawal, M., & Bhadouria, V. S. (2025). Neural network-based equaliser for non-Gaussian underwater acoustic communication channels. International Journal of Communication Systems, 38(3), e5988.
  • Goel, K., Agrawal, M., & Kar, S. (2025). A novel planar sparse array design for two-dimensional direction-of-arrival estimation. Circuits, Systems, and Signal Processing, 44(2), 1214–1238. Springer.
  • Dhara, B., Agrawal, M., & Dutta Roy, S. (2025). Beamforming optimization via quantum algorithms. IET Quantum Communication, 6(1), e12120.
  • Dhara, B., Agrawal, M., & Roy, S. (2025). Exploring optimal and suboptimal beamforming solutions. In Proceedings of the 17th International Conference on Communications (COMSNETS 2025) (pp. 1091–1095). IEEE.
  • Chauhan, C., Tripathy, R. K., & Agrawal, M. (2025). Detection of bundle branch block from 12-lead ECG using machine learning techniques. IEEE Transactions on Human-Machine Systems.