publications

Journal articles

1. IEEE Sensors Journal

   Accelerated Pattern-Coupled Sparse Bayesian Learning for Automotive Occupancy Mapping

   Frank Harraway, Peiyuan Zhai, Geethu Joseph, and 1 more author

   IEEE Sensors Journal, 2025

   DOI Bib

   @article{harraway2025accelerated,
     author = {Harraway, Frank and Zhai, Peiyuan and Joseph, Geethu and Pandharipande, Ashish},
     journal = {IEEE Sensors Journal},
     title = {Accelerated Pattern-Coupled Sparse Bayesian Learning for Automotive Occupancy Mapping},
     year = {2025},
     volume = {25},
     number = {22},
     pages = {41801--41810},
     keywords = {Sensors;Laser radar;Radar;Computational modeling;Vectors;Radar measurements;Bayes methods;Sparse matrices;Reflection;Octrees;Adaptive resolution;light detection and ranging (LiDAR) point clouds;nuScenes dataset;occupancy grid mapping (OGM);radar point clouds;RADIATE dataset;sparse Bayesian learning},
     doi = {10.1109/JSEN.2025.3617133}
   }

2. IEEE Sensors Journal

   

   Camera-Aided Binary Prior Support-Informed Occupancy Grid Mapping

   Peiyuan Zhai, Geethu Joseph, N. Jonathan Myers, and 1 more author

   IEEE Sensors Journal, Feb 2026

   DOI Bib

   @article{zhai2026camera,
     title = {Camera-Aided Binary Prior Support-Informed Occupancy Grid Mapping},
     author = {Zhai, Peiyuan and Joseph, Geethu and Myers, N. Jonathan and Pandharipande, Ashish},
     journal = {IEEE Sensors Journal},
     volume = {26},
     number = {3},
     pages = {4340--4348},
     year = {2026},
     month = feb,
     doi = {10.1109/JSEN.2025.3642255},
     publisher = {IEEE},
   }

3. IEEE Sensors Journal

   

   Spatial Sparsity-Aware Radar-LiDAR Fusion for Occupancy Grid Mapping in Automotive Driving

   Peiyuan Zhai, Geethu Joseph, N. J. Myers, and 2 more authors

   IEEE Sensors Journal, Sep 2025

   DOI Bib

   @article{zhai2025spatial,
     title = {Spatial Sparsity-Aware Radar-LiDAR Fusion for Occupancy Grid Mapping in Automotive Driving},
     author = {Zhai, Peiyuan and Joseph, Geethu and Myers, N. J. and Onen, Cemalcan and Pandharipande, Ashish},
     journal = {IEEE Sensors Journal},
     volume = {25},
     number = {17},
     pages = {33328--33338},
     year = {2025},
     month = sep,
     doi = {10.1109/JSEN.2025.3592023},
     publisher = {IEEE},
   }

Conference papers

1. IEEE SENSORS

   Computationally-Efficient Sparsity-Aware Occupancy Grid Mapping for Automotive Driving

   Frank Harraway, Peiyuan Zhai, Ashish Pandharipande, and 1 more author

   In 2025 IEEE SENSORS, 2025

   DOI Bib

   @inproceedings{harraway2025computationally,
     author = {Harraway, Frank and Zhai, Peiyuan and Pandharipande, Ashish and Joseph, Geethu},
     booktitle = {2025 IEEE SENSORS},
     title = {Computationally-Efficient Sparsity-Aware Occupancy Grid Mapping for Automotive Driving},
     year = {2025},
     pages = {1--4},
     keywords = {Point cloud compression;Laser radar;Runtime;Accuracy;Benchmark testing;Spatial databases;Real-time systems;Computational efficiency;Bayes methods;Automotive engineering;Occupancy grid mapping;LiDAR point clouds;sparse Bayesian learning;automotive driving},
     doi = {10.1109/SENSORS59705.2025.11331194}
   }

2. IEEE SENSORS

   Sparsity-aware occupancy grid mapping for automotive driving using radar-LiDAR fusion

   Peiyuan Zhai, Geethu Joseph, N. J. Myers, and 2 more authors

   In 2024 IEEE SENSORS, Oct 2024

   DOI Bib

   @inproceedings{zhai2024sparsity,
     title = {Sparsity-aware occupancy grid mapping for automotive driving using radar-LiDAR fusion},
     author = {Zhai, Peiyuan and Joseph, Geethu and Myers, N. J. and Onen, Cemalcan and Pandharipande, Ashish},
     booktitle = {2024 IEEE SENSORS},
     pages = {1--4},
     year = {2024},
     month = oct,
     doi = {10.1109/SENSORS60989.2024.10785054},
     organization = {IEEE},
   }

3. ICASSP

   

   Distributed Gaussian Process Hyperparameter Optimization for Multi-Agent Systems

   Peiyuan Zhai and R. T. Rajan

   In 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2023

   DOI Bib

   @inproceedings{zhai2023distributed,
     title = {Distributed Gaussian Process Hyperparameter Optimization for Multi-Agent Systems},
     author = {Zhai, Peiyuan and Rajan, R. T.},
     booktitle = {2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
     pages = {1--5},
     year = {2023},
     month = jun,
     doi = {10.1109/ICASSP49357.2023.10096267},
     organization = {IEEE},
   }

Degree dissertation

1. M.Sc. Thesis

   Distributed Gaussian Process for Multi-agent Systems

   Peiyuan Zhai

   Delft University of Technology, Jun 2022

   Advisor: R.T. Rajan, Signal Processing Systems Group

   Bib PDF

   @mastersthesis{zhai2022distributed,
     author = {Zhai, Peiyuan},
     title = {Distributed {G}aussian {P}rocess for {M}ulti-agent {S}ystems},
     school = {Delft University of Technology},
     year = {2022},
     month = jun,
     url = {https://repository.tudelft.nl/record/uuid:332d5ea4-9757-47da-8cb7-aaf95ba4e31d},
     note = {Advisor: R.T. Rajan, Signal Processing Systems Group},
     keywords = {Gaussian Process, Hyperparameter Optimization, Multi-Agent Systems, Distributed Signal Processing, Mixture of Experts}
   }