Computational Sensing

Utilizing computation to improve sensing capabilities.

Our research in the area of computational sensing focuses on signal acquisition and design, signal modeling and reconstruction algorithms, including inverse problems, as well as array signal processing techniques.

  • Researchers

  • Awards

    •  AWARD   2015 IEEE Signal Processing Society Best Paper Award
      Date: December 1, 2015
      Awarded to: Mark A. Davenport, Petros T. Boufounos, Michael B. Wakin and Richard G. Baraniuk
      MERL Contact: Petros Boufounos
      Research Area: Computational Sensing
      Brief
      • Petros Boufounos is a recipient of the 2015 IEEE Signal Processing Society Best Paper Award for the paper that he co-authored with Mark A. Davenport, Michael B. Wakin and Richard G. Baraniuk on "Signal Processing with Compressive Measurements" which was published in the April 2010 issue of IEEE Journal of Selected Topics in Signal Processing. The Best Paper Award honors the author(s) of a paper of exceptional merit dealing with a subject related to the Society's technical scope, and appearing in one of the Society's solely owned transactions or the Journal of Selected Topics in Signal Processing. Eligibility is based on a five-year window: for example, for the 2015 Award, the paper must have appeared in one of the Society's Transactions between January 1, 2010 and December 31, 2014.
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    •  AWARD   GRSS 2014 Symposium Prize Paper Award
      Date: May 1, 2014
      Awarded to: Dehong Liu and Petros T. Boufounos
      Awarded for: "Synthetic Aperture Imaging Using a Randomly Steered Spotlight"
      Awarded by: IEEE Geoscience and Remote Sensing Society (GRSS)
      MERL Contacts: Dehong Liu; Petros Boufounos
      Research Area: Computational Sensing
      Brief
      • Dehong Liu and Petros T. Boufounos are the recipients of the the IEEE Geoscience and Remote Sensing Society 2014 Symposium Prize Paper Award for their paper "Synthetic Aperture Imaging Using a Randomly Steered Spotlight," presented at IGARSS 2013 (TR2013-070).
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    •  AWARD   MMSP 2012 Top 10% Paper Award
      Date: September 1, 2012
      Awarded to: Mu Li, Shantanu Rane and Petros Boufounos
      Awarded for: "Quantized Embeddings of Scale-Invariant Image Features for Mobile Augmented Reality"
      Awarded by: IEEE International Workshop on Multimedia Signal Processing (MMSP)
      MERL Contact: Petros Boufounos
      Research Areas: Digital Video, Computational Sensing
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  • News & Events


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  • Research Highlights

  • Internships

    • SP1504: Coherent Imaging Systems

      MERL is seeking an intern to work on coherent optical imaging. The ideal candidate would be an experienced PhD student or post-graduate researcher working in coherent imaging. The candidate should have a detailed knowledge of optical interferometry and imaging with a focus on either optical coherence tomography, optical coherence microscopy or FMCW LIDAR. Strong programming skills in MATLAB are essential. Experience of working in an optical lab environment is a required. Duration is 3 to 6 months. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • SP1512: Mutual Interference Mitigation

      The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in mutual interference mitigation for automotive radar. Previous experience in waveform design, radar detection under interference, joint communication and sensing, interference mitigation, and deep learning for radar is highly preferred. Knowledge about automotive radar schemes (MIMO and waveform modulation, e.g., FMCW, PMCW, and OFDM) is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments using MERL in-house testbed, and prepare results for patents and publication. Senior Ph.D. students with research focuses on signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date.

    • SP1542: Research in Computational Sensing

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to assist in the development of computational methods for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, sensing of dynamical systems, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.


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  • Openings


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  • Recent Publications

    •  Ma, Y., Boufounos, P.T., Mansour, H., Aeron, S., "Multiview Sensing with Unknown Permutations: An Optimal Transport Approach", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-047 PDF
      • @inproceedings{Ma2021jun,
      • author = {Ma, Yanting and Boufounos, Petros T. and Mansour, Hassan and Aeron, Shuchin},
      • title = {Multiview Sensing with Unknown Permutations: An Optimal Transport Approach},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-047}
      • }
    •  Hyder, R., Mansour, H., Ma, Y., Boufounos, P.T., Wang, P., "A Consensus Equilibrium Solution for Deep Image Prior Powered by Red", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-046 PDF
      • @inproceedings{Hyder2021jun,
      • author = {Hyder, Rakib and Mansour, Hassan and Ma, Yanting and Boufounos, Petros T. and Wang, Perry},
      • title = {A Consensus Equilibrium Solution for Deep Image Prior Powered by Red},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-046}
      • }
    •  Yao, G., Wang, P., Berntorp, K., Mansour, H., Boufounos, P.T., Orlik, P.V., "Extended Object Tracking with Automotive Radar Using B-Spline Chained Ellipses Model", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-048 PDF
      • @inproceedings{Yao2021jun,
      • author = {Yao, Gang and Wang, Perry and Berntorp, Karl and Mansour, Hassan and Boufounos, Petros T. and Orlik, Philip V.},
      • title = {Extended Object Tracking with Automotive Radar Using B-Spline Chained Ellipses Model},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-048}
      • }
    •  Kadu, A., Mansour, H., Boufounos, P.T., "High-Contrast Reflection Tomography with Total-Variation Constraints", IEEE Transactions on Computational Imaging, March 2021.
      BibTeX TR2021-013 PDF
      • @article{Kadu2021mar,
      • author = {Kadu, Ajinkya and Mansour, Hassan and Boufounos, Petros T.},
      • title = {High-Contrast Reflection Tomography with Total-Variation Constraints},
      • journal = {IEEE Transactions on Computational Imaging},
      • year = 2021,
      • month = mar,
      • url = {https://www.merl.com/publications/TR2021-013}
      • }
    •  Xia, Y., Wang, P., Berntorp, K., Svensson, L., Granstrom, K., Mansour, H., Boufounos, P.T., Orlik, P.V., "Learning-based Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar", IEEE Journal of Selected Topics in Signal Processing, February 2021.
      BibTeX TR2021-006 PDF
      • @article{Xia2021feb,
      • author = {Xia, Yuxuan and Wang, Pu and Berntorp, Karl and Svensson, Lennart and Granstrom, Karl and Mansour, Hassan and Boufounos, Petros T. and Orlik, Philip V.},
      • title = {Learning-based Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar},
      • journal = {IEEE Journal of Selected Topics in Signal Processing},
      • year = 2021,
      • month = feb,
      • url = {https://www.merl.com/publications/TR2021-006}
      • }
    •  Li, S., Mansour, H., Wakin, M., "Recovery Analysis of Damped Spectrally Sparse Signals and Its Relation to MUSIC", Information and Inference: A Journal of the IMA, January 2021.
      BibTeX TR2021-008 PDF
      • @article{Li2021jan,
      • author = {Li, Shuang and Mansour, Hassan and Wakin, Michael},
      • title = {Recovery Analysis of Damped Spectrally Sparse Signals and Its Relation to MUSIC},
      • journal = {Information and Inference: A Journal of the IMA},
      • year = 2021,
      • month = jan,
      • url = {https://www.merl.com/publications/TR2021-008}
      • }
    •  Goukhshtein, M., Boufounos, P.T., Koike-Akino, T., Draper, S.C., "Distributed Coding of Quantized Random Projections", IEEE Transactions on Signal Processing, DOI: 10.1109/​TSP.2020.3029499, Vol. 68, pp. 5924-5939, December 2020.
      BibTeX TR2020-157 PDF
      • @article{Goukhshtein2020dec,
      • author = {Goukhshtein, Maxim and Boufounos, Petros T. and Koike-Akino, Toshiaki and Draper, Stark C.},
      • title = {Distributed Coding of Quantized Random Projections},
      • journal = {IEEE Transactions on Signal Processing},
      • year = 2020,
      • volume = 68,
      • pages = {5924--5939},
      • month = dec,
      • doi = {10.1109/TSP.2020.3029499},
      • issn = {1941-0476},
      • url = {https://www.merl.com/publications/TR2020-157}
      • }
    •  Yu, J., Wang, P., Koike-Akino, T., Wang, Y., Orlik, P.V., "Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/​GCWkshps50303.2020.9367535, December 2020.
      BibTeX TR2020-158 PDF
      • @inproceedings{Yu2020dec,
      • author = {Yu, Jianyuan and Wang, Pu and Koike-Akino, Toshiaki and Wang, Ye and Orlik, Philip V.},
      • title = {Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2020,
      • month = dec,
      • publisher = {IEEE},
      • doi = {10.1109/GCWkshps50303.2020.9367535},
      • isbn = {978-1-7281-7307-8},
      • url = {https://www.merl.com/publications/TR2020-158}
      • }
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  • Videos