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Yanting Ma

Yanting Ma
Yanting's Quick Links

  • Biography

    Yanting's research interests are mainly in algorithm design and analysis for inverse problems arising in computational sensing using statistical inference and optimization techniques. Additionally, she is generally interested in applied probability and convex analysis. Her PhD research focused on algorithmic and theoretical studies of approximate message passing, as well as provably convergent optimization algorithms for nonlinear diffractive imaging. Her postdoctoral work developed principled methods for dead time compensation for single-photon detectors based on Markov chain modeling.

  • Recent News & Events

    •  TALK   Prof. Pere Gilabert gave an invited talk at MERL on Machine Learning for Digital Predistortion Linearization of High Efficient Power Amplifier
      Date & Time: Tuesday, February 16, 2021; 11:00-12:00
      Speaker: Prof. Pere Gilabert, Universitat Politecnica de Catalunya, Barcelona, Spain
      MERL Host: Rui Ma
      Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
      Brief
      • Digital predistortion (DPD) linearization is the most common and spread solution to cope with power amplifiers (PA) inherent linearity versus efficiency trade-off. The use of new radio 5G spectrally efficient signals with high peak-to-average power ratios (PAPR) occupying wider bandwidths only aggravates such compromise. When considering wide bandwidth signals, carrier aggregation or multi-band configurations in high efficient transmitter architectures, such as Doherty PAs, load-modulated balanced amplifiers, envelope tracking PAs or outphasing transmitters, the number of parameters required in the DPD model to compensate for both nonlinearities and memory effects can be unacceptably high. This has a negative impact in the DPD model extraction/adaptation, because it increases the computational complexity and drives to over-fitting and uncertainty.
        This talk will discuss the use of machine learning techniques for DPD linearization. The use of artificial neural networks (ANNs) for adaptive DPD linearization and approaches to reduce the coefficients adaptation time will be discussed. In addition, an overview on several feature-extraction techniques used to reduce the number of parameters of the DPD linearization system as well as to ensure proper, well-conditioned estimation for related variables will be presented.
    •  
    •  NEWS   M. Benosman will give an invited talk at the Industrial and Applied Mathematics (SIAM) Student Chapter at Virginia Tech.
      Date: October 9, 2020
      MERL Contact: Mouhacine Benosman
      Research Area: Dynamical Systems
      Brief
      • M. Benosman will give an invited talk at the SIAM student chapter at Virginia Tech. to speak about several applications of mathematics to industrial problems.

        The Society for Industrial and Applied Mathematics (SIAM) Student Chapter at Virginia Tech will host a number of talks by mathematicians working in industry. The speakers will describe the path they followed to reach this point in their careers and also tell us more about their industry and how mathematics is used.
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  • MERL Publications

    •  Seidel, S.W., Murray-Bruce, J., Ma, Y., Yu, C., Freeman, W.T., Goyal, V.K., "Two-Dimensional Non-Line-of-Sight Scene Estimation from a Single Edge Occluder", IEEE Transactions on Computational Imaging, DOI: 10.1109/​TCI.2020.3037405, Vol. 7, pp. 58-72, December 2020.
      BibTeX
      • @article{Seidel2020dec,
      • author = {Seidel, Sheila, W. and Murray-Bruce, John and Ma, Yanting and Yu, Christopher and Freeman, William, T. and Goyal, Vivek K},
      • title = {Two-Dimensional Non-Line-of-Sight Scene Estimation from a Single Edge Occluder},
      • journal = {IEEE Transactions on Computational Imaging},
      • year = 2020,
      • volume = 7,
      • pages = {58--72},
      • month = dec,
      • doi = {10.1109/TCI.2020.3037405}
      • }
    •  Lin, C., Sels, D., Ma, Y., Wang, Y., "Stochastic optimal control formalism for an open quantum system", Physical Review, DOI: 10.1103/​PhysRevA.102.052605, Vol. 102, pp. 052605, December 2020.
      BibTeX TR2020-163 PDF
      • @article{Lin2020dec,
      • author = {Lin, Chungwei and Sels, Dries and Ma, Yanting and Wang, Yebin},
      • title = {Stochastic optimal control formalism for an open quantum system},
      • journal = {Physical Review},
      • year = 2020,
      • volume = 102,
      • pages = 052605,
      • month = dec,
      • doi = {10.1103/PhysRevA.102.052605},
      • url = {https://www.merl.com/publications/TR2020-163}
      • }
    •  Ma, Y., Boufounos, P.T., Mansour, H., Aeron, S., "Multiview Sensing with Unknown Permutations: An Optimal Transport Approach", arXiv, November 2020.
      BibTeX
      • @article{Ma2020nov,
      • author = {Ma, Yanting and Boufounos, Petros T. and Mansour, Hassan and Aeron, Shuchin},
      • title = {Multiview Sensing with Unknown Permutations: An Optimal Transport Approach},
      • journal = {arXiv},
      • year = 2020,
      • month = nov
      • }
    •  Yu, L., Liu, D., Mansour, H., Boufounos, P.T., Ma, Y., "Blind Multi-Spectral Image Pan-Sharpening", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/​ICASSP40776.2020.9053554, April 2020, pp. 1429-1433.
      BibTeX TR2020-047 PDF Video
      • @inproceedings{Yu2020apr,
      • author = {Yu, Lantao and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T. and Ma, Yanting},
      • title = {Blind Multi-Spectral Image Pan-Sharpening},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {1429--1433},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9053554},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-047}
      • }
    •  Ma, Y., Lodhi, M.A., Mansour, H., Boufounos, P.T., Liu, D., "Inverse Multiple Scattering With Phaseless Measurements", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/​ICASSP40776.2020.9053430, April 2020, pp. 1519-1523.
      BibTeX TR2020-041 PDF Video
      • @inproceedings{Ma2020apr,
      • author = {Ma, Yanting and Lodhi, Muhammad Asad and Mansour, Hassan and Boufounos, Petros T. and Liu, Dehong},
      • title = {Inverse Multiple Scattering With Phaseless Measurements},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2020,
      • pages = {1519--1523},
      • month = apr,
      • publisher = {IEEE},
      • doi = {10.1109/ICASSP40776.2020.9053430},
      • issn = {2379-190X},
      • isbn = {978-1-5090-6631-5},
      • url = {https://www.merl.com/publications/TR2020-041}
      • }
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  • Videos

  • MERL Issued Patents

    • Title: "Systems and Methods of Fusing Multi-angle View HD Images Based on Epipolar Geometry and Matrix Completion"
      Inventors: Liu, Dehong; Ma, Yanting; Mansour, Hassan; Kamilov, Ulugbek; Taguchi, Yuichi; Boufounos, Petros T.; Vetro, Anthony
      Patent No.: 10,212,410
      Issue Date: Feb 19, 2019
    See All Patents for MERL