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

    • SP1585: Three dimensional Imaging from Compton Camera

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that reconstruct a three dimensional distribution of a radioactive source when observed using a Compton camera. The project goal is to improve the performance and develop an uncertainty analysis of these algorithms. Ideal candidates should be Ph.D. students and have solid background and publication record in 3D Compton imaging. Experience in computational tomography, imaging inverse problems, and large-scale optimization is also preferred. 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.

    • SP1506: Learning-based Wireless Sensing

      The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in learning-based wireless sensing using communication signals (such as WiFi, Bluetooth, 5G) and other RF signals (such as FMCW). Previous experience in occupancy sensing, people counting, localization, device-free pose/gesture recognition, and skeleton tracking with deep learning is highly preferred. Familiarity with IEEE 802.11 (g/n/ac/ad/ay)standards 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 publication. Senior Ph.D. students with research focuses on wireless communications, machine learning, signal processing, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date. 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.


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  • Openings


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  • Recent Publications

    •  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), 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,
      • url = {https://www.merl.com/publications/TR2020-158}
      • }
    •  Wang, P., Koike-Akino, T., Orlik, P.V., Sertel, K., Yamashita, G., Tsujita, W., Tsutada, H., "Terahertz QR Positioning: Experimental Results", International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), November 2020.
      BibTeX TR2020-146 PDF
      • @inproceedings{Wang2020nov,
      • author = {Wang, Pu and Koike-Akino, Toshiaki and Orlik, Philip V. and Sertel, Kubilay and Yamashita, Genki and Tsujita, Wataru and Tsutada, Hiroyuki},
      • title = {Terahertz QR Positioning: Experimental Results},
      • booktitle = {International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)},
      • year = 2020,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2020-146}
      • }
    •  Yamashita, G., Tsujita, W., Tsutada, H., Ma, R., Wang, P., Orlik, P.V., "Evaluation of Position Error of Terahertz Polarimetric Encoder By Ray-Tracing Method", International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), November 2020.
      BibTeX TR2020-145 PDF
      • @inproceedings{Yamashita2020nov,
      • author = {Yamashita, Genki and Tsujita, Wataru and Tsutada, Hiroyuki and Ma, Rui and Wang, Pu and Orlik, Philip V.},
      • title = {Evaluation of Position Error of Terahertz Polarimetric Encoder By Ray-Tracing Method},
      • booktitle = {International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)},
      • year = 2020,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2020-145}
      • }
    •  Atalar, O., Millar, D.S., Wang, P., Koike-Akino, T., Kojima, K., Orlik, P.V., Parsons, K., "Spectrally sparse optical coherence tomography", Optics Express, DOI: 10.1364/OE.409539, Vol. 28, No. 25, pp. 37798-37810, October 2020.
      BibTeX TR2020-156 PDF
      • @article{Atalar2020oct,
      • author = {Atalar, Okan and Millar, David S. and Wang, Pu and Koike-Akino, Toshiaki and Kojima, Keisuke and Orlik, Philip V. and Parsons, Kieran},
      • title = {Spectrally sparse optical coherence tomography},
      • journal = {Optics Express},
      • year = 2020,
      • volume = 28,
      • number = 25,
      • pages = {37798--37810},
      • month = oct,
      • doi = {10.1364/OE.409539},
      • url = {https://www.merl.com/publications/TR2020-156}
      • }
    •  Xia, Y., Wang, P., Berntorp, K., Boufounos, P.T., Orlik, P.V., Svensson, L., Granstrom, K., "Extended Object Tracking with Automotive Radar Using Learned Structural Measurement Model", IEEE Radar Conference (RadarCon), September 2020.
      BibTeX TR2020-131 PDF
      • @inproceedings{Xia2020sep,
      • author = {Xia, Yuxuan and Wang, Pu and Berntorp, Karl and Boufounos, Petros T. and Orlik, Philip V. and Svensson, Lennart and Granstrom, Karl},
      • title = {Extended Object Tracking with Automotive Radar Using Learned Structural Measurement Model},
      • booktitle = {IEEE Radar Conference (RadarCon)},
      • year = 2020,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2020-131}
      • }
    •  Liu, D., Chen, S., Boufounos, P.T., "Graph-Based Array Signal Denoising for Perturbed Synthetic Aperture Radar", IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 2020, pp. 1881-1884.
      BibTeX TR2020-114 PDF Video
      • @inproceedings{Liu2020jul,
      • author = {Liu, Dehong and Chen, Siheng and Boufounos, Petros T.},
      • title = {Graph-Based Array Signal Denoising for Perturbed Synthetic Aperture Radar},
      • booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
      • year = 2020,
      • pages = {1881--1884},
      • month = jul,
      • isbn = {978-1-7281-6374-1},
      • url = {https://www.merl.com/publications/TR2020-114}
      • }
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  • Videos