dr. G. Joseph

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

Expertise: Compressive Sensing, Statistical signal processing, Automotive sensing, Sparse Control, Communication

Themes: Autonomous sensor systems, XG - Next Generation Sensing and 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.

EE3S1 Signal Processing

Statistical and Digital Signal Processing

EE4740 Sparse signal processing

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. Sparse Millimeter Wave Channel Estimation Under Partially Coherent Phase Noise
    Quan, Chen; Yi, Weijia; Myers, Nitin Jonathan; Joseph, Geethu;
    IEEE Transactions on Wireless Communications,
    2026. DOI: 10.1109/TWC.2026.3684356
    document

  2. Energy-Efficient Sequential Estimation Via Sensor Ordering
    Quan, Chen; Joseph, Geethu; Myers, Nitin Jonathan;
    IEEE Transactions on Signal and Information Processing over Networks,
    pp. 1-13, 2026. DOI: 10.1109/TSIPN.2026.3685830
    document

  3. Camera-Aided Binary Prior Support-Informed Occupancy Grid Mapping
    Zhai, Peiyuan; Joseph, Geethu; Jonathan Myers, Nitin; Pandharipande, Ashish;
    IEEE Sensors Journal,
    Volume 26, Issue 3, pp. 4340-4348, 2026. DOI: 10.1109/JSEN.2025.3642255
    document

  4. Channel Access Strategies for Control–Communication Co-Designed Networks
    Ghatak, Gourab; Joseph, Geethu; Quan, Chen;
    IEEE Transactions on Control of Network Systems,
    Volume 13, Issue 1, pp. 117-129, 2026. DOI: 10.1109/TCNS.2025.3621024
    document

  5. Bayesian Algorithms for Kronecker-structured Sparse Vector Recovery With Application to IRS-MIMO Channel Estimation
    Yanbin He; Geethu Joseph;
    IEEE Transactions on Signal Processing,
    pp. 142-157, 2025. DOI: 10.1109/TSP.2024.3416543
    document

  6. Low-Resolution Compressed Sensing and Beyond for Communications and Sensing: Trends and Opportunities
    Geethu Joseph; et al.;
    Elsevier Signal Processing,
    2025.

  7. Efficient Off-Grid Bayesian Parameter Estimation for Kronecker-Structured Signals
    Yanbin He; G. Joseph;
    IEEE Transactions on Signal Processing,
    Volume 73, pp. 2616-2630, 2025. DOI: https://doi.org/10.1109/TSP.2025.3583895
    Abstract: ... This work studies the problem of jointly estimating unknown parameters from Kronecker-structured multidimensional signals, which arises in applications like intelligent reflecting surface (IRS)-aided channel estimation. Exploiting the Kronecker structure, we decompose the estimation problem into smaller, independent subproblems across each dimension. Each subproblem is posed as a sparse recovery problem using basis expansion and solved using a novel off-grid sparse Bayesian learning (SBL)-based algorithm. Additionally, we derive probabilistic error bounds for the decomposition, quantify its denoising effect, and provide convergence analysis for off-grid SBL. Our simulations show that applying the algorithm to IRS-aided channel estimation improves accuracy and runtime compared to state-of-the-art methods through the low-complexity and denoising benefits of the decomposition step and the high-resolution estimation capabilities of off-grid SBL.

    document

  8. Accelerated Pattern-Coupled Sparse Bayesian Learning for Automotive Occupancy Mapping
    Harraway, Frank; Zhai, Peiyuan; Joseph, Geethu; Pandharipande, Ashish;
    IEEE Sensors Journal,
    Volume 25, Issue 22, pp. 41801-41810, 2025. DOI: 10.1109/JSEN.2025.3617133
    document

  9. State and Sparse Input Estimation in Linear Dynamical Systems Using Low-Dimensional Measurements
    Chakraborty, Rupam Kalyan; Joseph, Geethu; Murthy, Chandra R.;
    IEEE Open Journal of Control Systems,
    Volume 4, pp. 581-596, 2025. DOI: 10.1109/OJCSYS.2025.3624615
    document

  10. Spatial Sparsity-Aware Radar-LiDAR Fusion for Occupancy Grid Mapping in Automotive Driving
    Zhai, Peiyuan; Joseph, Geethu; Myers, Nitin Jonathan; Önen, Çağan; Pandharipande, Ashish;
    IEEE Sensors Journal,
    Volume 25, Issue 17, pp. 33328-33338, 2025. DOI: 10.1109/JSEN.2025.3592023
    document

  11. Noise-Resilient Unlimited Sampling and Recovery of Sparse Signals
    Joseph, Geethu;
    In 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    pp. 1-5, 2025. DOI: 10.1109/ICASSP49660.2025.10888741
    document

  12. On the Restricted Isometry Property of Kronecker-structured Matrices
    He, Yanbin; Joseph, Geethu;
    In 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    pp. 1-5, 2025. DOI: 10.1109/ICASSP49660.2025.10888132

  13. Kronecker-structured Sparse Vector Recovery with Application to IRS-MIMO Channel Estimation
    He, Yanbin; Joseph, Geethu;
    In 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    pp. 1-5, 2025. DOI: 10.1109/ICASSP49660.2025.10890014
    document

  14. Situation-aware Space-time Waveform Design for Automotive MIMO Radars
    Focante, Edoardo; Myers, Nitin Jonathan; Joseph, Geethu; Pandharipande, Ashish;
    In 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    pp. 1-5, 2025. DOI: 10.1109/ICASSP49660.2025.10890749
    document

  15. An Energy-Efficient Ordered Transmission-based Sequential Estimation
    Quan, Chen; Joseph, Geethu; Myers, Nitin Jonathan;
    In 2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring),
    pp. 1-6, 2025. DOI: 10.1109/VTC2025-Spring65109.2025.11174545} url = {https://sp

  16. A Hierarchical View of Structured Sparsity in Kronecker Compressive Sensing
    Yanbin He; Geethu Joseph;
    In 2025 33rd European Signal Processing Conference (EUSIPCO),
    Sept. 2025. DOI: 10.23919/EUSIPCO63237.2025.11226345
    document

  17. Computationally-Efficient Sparsity-Aware Occupancy Grid Mapping for Automotive Driving
    Harraway, Frank; Zhai, Peiyuan; Pandharipande, Ashish; Joseph, Geethu;
    In 2025 IEEE SENSORS,
    pp. 1-4, 2025. DOI: 10.1109/SENSORS59705.2025.11331194
    document

  18. Adaptive Dithering for Improved Dynamic Range in Mixed-Resolution ADC Digital Radars
    Shaikh, Mohammed Aasim; Joseph, Geethu; Pandharipande, Ashish; Myers, Nitin Jonathan;
    In 2025 IEEE Radar Conference (RadarConf25),
    pp. 1242-1247, 2025. DOI: 10.1109/RadarConf2559087.2025.11205063
    document

  19. Non-Line-Of-Sight Localization in Automotive Radar Via Intelligent Reflecting Surfaces
    Chakraborty, Rupam Kalyan; Joseph, Geethu; Myers, Nitin Jonathan; Pandharipande, Ashish;
    In 2025 IEEE 26th International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC),
    pp. 1-5, 2025. DOI: 10.1109/SPAWC66079.2025.11143303
    document

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

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

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

  23. 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.

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

  25. 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.

  26. Sparse Actuator Control of Discrete-Time Linear Dynamical Systems
    Geethu Joseph;
    Now Publishers, Inc., , 2024. DOI: 10.1561/2600000033
    document

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

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

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

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

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

  32. 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.

  33. 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.

  34. 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.

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

  36. 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.

  37. 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

  38. 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

  39. 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

  40. 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.

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

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

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

  44. 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

  45. 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.

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

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

  48. 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).

  49. Sensorized nanoliter reactor chamber for DNA multiplication
    V.P. Iordanov; B.P. Iliev; V. Joseph; J. Bastemeijer; P.M. Sarro; I.T. Young; G. van DedemWK; M.J. Vellekoop;
    In D. Rocha; P.M. Sarro; M.J. Vellekoop (Ed.), Proceedings of IEEE Sensors, 2004,
    IEEE, Piscataway, pp. 229-232, 2004. niet eerder opgevoerd 50/50 EI/ECTM.

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Last updated: 9 Feb 2026