Signal Processing Systems
Dept. of Microelectronics

dr. G. Joseph

Assistant Professor
Signal Processing Systems (SPS), Department of Microelectronics

Expertise: Compressive Sensing, Sparse Signal Processing, Linear Dynamical Systems, Sparse Control, Sensing, Communication

Themes: Distributed autonomous sensing systems, Signal processing for communication

Biography

Geethu Joseph received the B. Tech. degree in electronics and communication engineering from the National Institute of Technology, Calicut, India, in 2011, and the M. E. degree in signal processing and the Ph.D. degree in electrical communication engineering (ECE) from the Indian Institute of Science (IISc), Bangalore, in 2014 and 2019, respectively. She was a Postdoctoral Fellow with the Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA, from 2019 to 2021. She is currently an assistant professor at TU Delft. 

 

Dr. Joseph was awarded the 2022 IEEE SPS best PhD dissertation award and the 2020 SPCOM best doctoral dissertation award. She is also a recipient of the Prof. I. S. N. Murthy Medal in 2014 for being the best M. E. (signal processing) student in the ECE dept., IISc, and the Seshagiri Kaikini Medal for the best Ph.D. thesis of the ECE dept., at IISc for the year 2019-'20

Dr. Joseph holds 50+ peer-reviewed publications in the fields of signal processing, communications, and control theory. She is an associate editor of the IEEE Sensors Journal and an active reviewer for major journals and conferences in signal processing, communications, and control theory.  Her research interests include statistical signal processing, network control, and machine learning.

EE4740 Data compression: Entropy and sparsity perspectives

Data compression and its connections to information theory and compressed sensing

EE4C03 Statistical digital signal processing

A second course on digital signal processing: random signals, covariances, linear prediction, spectrum estimation, optimal filtering, Wiener and Kalman filters, LMS and RLS algorithm

Education history

EE2S31 Signal processing

(not running) Digital signal processing; stochastic processes

Atmospheric Turbulence Informed Machine Learning for Laser Satellite Communications

Physics-informed machine learning algorithms to formulate the optical link performance map

Signal processing for environment-aware radar

In future, cars will exploit multiple radars towards autonomous driving. Before this becomes a reality, several challenges will have to be solved.

  1. Noise-Resilient Unlimited Sampling and Recovery of Sparse Signals
    Geethu Joseph;
    In ICASSP,
    2025.

  2. On the Restricted Isometry Property of Kronecker-structured Matrices
    Yanbin He; Geethu Joseph;
    In ICASSP,
    2025.

  3. Kronecker-structured Sparse Vector Recovery with Application to IRS-MIMO Channel Estimation
    Yanbin He; Geethu Joseph;
    In ICASSP,
    2025.

  4. Situation-aware Space-time Waveform Design for Automotive MIMO Radars
    Edoardo Focante; Nitin Jonathan Myers; Geethu Joseph; Ashish Pandharipande;
    In ICASSP,
    2025.

  5. Convergence of Expectation-Maximization Algorithm with Mixed-Integer Optimization
    Geethu Joseph;
    IEEE Signal Processing Letters,
    2024.

  6. Anomaly Detection via Learning-Based Sequential Controlled Sensing
    Geethu Joseph; Chen Zhong; M. Cenk Gursoy; Senem Velipasalar; Pramod K. Varshney;
    IEEE Sensors,
    2024.

  7. Occupancy Grid Mapping for Automotive Driving Exploiting Clustered Sparsity
    Çağan Önen; Ashish Pandharipande; Geethu Joseph; Nitin Jonathan Myers;
    IEEE Sensors,
    2024.

  8. Bayesian Algorithms for Kronecker-structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation
    Yanbin He; Geethu Joseph;
    IEEE Transactions on Signal Processing,
    2024.

  9. Adaptive Beamforming for Situation-aware Automotive Radars Under Uncertain Side Information
    Edoardo Focante; Nitin Jonathan Myers; Geethu Joseph; Ashish Pandharipande;
    IEEE Transactions on Signal Processing,
    2024.

  10. Pointwise-Sparse Actuator Scheduling for Linear Systems with Controllability Guarantee
    Luca Ballotta; Geethu Joseph; Irawati Rahul Thete;
    IEEE Control Systems Letters,
    2024.

  11. Comprehensive MPSP for Fast Optimal Control: Algorithm Development and Convergence Analysis
    Prem Kumar; Geethu Joseph; Chandra R. Murthy; Radhakant Padhi;
    Transactions of the Indian National Academy of Engineering,
    2024.

  12. Sparse Actuator Control of Discrete-Time Linear Dynamical Systems
    Geethu Joseph;
    Now Publishers, Inc., , 2024. DOI: https://www.nowpublishers.com/article/Details/SYS-033

  13. Sparsity-Constrained Linear Dynamical Systems
    Geethu Joseph; Chandra R. Murthy;
    Springer Tracts in Electrical and Electronics Engineering, Springer, Singapore, , 2024. DOI: https://doi.org/10.1007/978-981-97-7090-8

  14. Situation-aware Adaptive Transmit Beamforming for Automotive Radars
    Edoardo Focante; Nitin Jonathan Myers; Geethu Joseph; Ashish Pandharipande;
    In ICASSP,
    2024.

  15. Sparse Millimeter Wave Channel Estimation From Partially Coherent Measurements
    Weijia Yi; Nitin Jonathan Myers; Geethu Joseph;
    In ICC,
    2024.

  16. Bayesian Learning-based Kalman Smoothing for Linear Dynamical Systems With Unknown Sparse Inputs
    Rupam Kalyan Chakraborty; Geethu Joseph; Chandra R. Murthy;
    In ICASSP,
    2024.

  17. Minimal Input Structural Modifications for Strongly Structural Controllability
    Geethu Joseph; Shana Moothedath; Jiabin Lin;
    In CDC,
    2024.

  18. Transmit Beamforming for Phased Array Radars Under Uncertain Occupancy Grid Map Information
    Edoardo Focante; Nitin Jonathan Myers; Geethu Joseph; Ashish Pandharipande;
    In IEEE Sensors,
    2024.

  19. Sparsity-Aware Occupancy Grid Mapping for Automotive Driving Using Radar-LiDAR Fusion
    Peiyuan Zhai; Geethu Joseph; Nitin Jonathan Myers; Çağan Önen; Ashish Pandharipande;
    In IEEE Sensors,
    2024.

  20. Transmit Beamforming for Phased Array Radars Under Uncertain Occupancy Grid Map Information
    Edoardo Focante; Nitin Jonathan Myers; Geethu Joseph; Ashish Pandharipande;
    In IEEE Sensors,
    2024.

  21. Poisson Networked Control Systems: Statistical Analysis and Online Learning for Channel Access
    Gourab Ghatak; Geethu Joseph; Chen Quan;
    In WiOpt workshop RAWNET,
    2024.

  22. Sparse Actuator Scheduling for Discrete-Time Linear Dynamical Systems
    Krishna Praveen V. S. Kondapi; Chandrasekhar Sriram; Geethu Joseph; Chandra R. Murthy;
    In Indian Control Conference,
    2024.

  23. Stabilizability of Linear Dynamical Systems Using Sparse Control Inputs
    Chandrasekhar Sriram; Geethu Joseph; Chandra R. Murthy;
    IEEE Transactions on Automatic Control,
    2023. DOI: 10.1109/TAC.2022.3217102

  24. Stabilizability of Linear Dynamical Systems Using Sparse Control Inputs
    Chandrasekhar Sriram; Geethu Joseph; Chandra R. Murthy;
    IEEE Transactions on Automatic Control,
    2023. DOI: 10.1109/TAC.2022.3217102

  25. Output Controllability of a Linear Dynamical System with Sparse Controls
    Geethu Joseph;
    IEEE Transactions on Control of Network Systems,
    2023. DOI: 10.1109/TCNS.2022.3188484

  26. Scalable and Decentralized Algorithms for Anomaly Detection via Learning-Based Controlled Sensing
    Geethu Joseph; Chen Zhong; M. Cenk Gursoy; Senem Velipasalar; Pramod K. Varshney;
    IEEE Transactions on Signal and Information Processing over Networks,
    2023.

  27. Occupancy Grid Mapping for Automotive Driving Exploiting Clustered Sparsity
    Çağan Önen; Ashish Pandharipande; Geethu Joseph; Nitin Jonathan Myers;
    IEEE Sensors Journal,
    2023.

  28. Structure-aware Sparse Bayesian Learning-based Channel Estimation for Intelligent Reflecting Surface-aided MIMO
    Yanbin He; Geethu Joseph;
    In ICASSP,
    2023.

  29. LiDAR-Based Occupancy Grid Map Estimation Exploiting Spatial Sparsity
    Çağan Önen; Ashish Pandharipande; Geethu Joseph; Nitin Jonathan Myers;
    In IEEE Sensors,
    2023.

  30. Output Controllability of a Linear Dynamical System with Sparse Controls
    Geethu Joseph;
    IEEE Transactions on Control of Network Systems,
    2022. DOI: 10.1109/TCNS.2022.3188484

  31. Sparsity-aware Bayesian inference and its applications
    Joseph, Geethu; Khanna, Saurabh; Murthy, Chandra R; Prasad, Ranjitha; Thoota, Sai Subramanyam;
    In Handbook of Statistics,
    Elsevier BV, 2022.

  32. State Estimation of Linear Systems With Sparse Inputs and Markov-modulated Missing Outputs
    Geethu Joseph; Pramod K. Varshney;
    In European Signal Processing Conference,
    2022.

  33. Near-field Focusing Using Phased Arrays With Dynamic Polarization Control
    Nitih Jonathan Myers; Yanki Aslan; Geethu Joseph;
    In European Signal Processing Conference,
    2022.

  34. Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers
    Saikiran Bulusu; Geethu Joseph; M. Cenk Gursoy; Pramod K. Varshney;
    In Neurips,
    2022. (S. Bulusu and G. Joseph have equal contribution).

BibTeX support

Last updated: 10 Feb 2025

Geethu Joseph

PhD students

MSc students

MSc project proposals