Michael Bianco

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Postdoctoral Scholar
Marine Physical Laboratory
Scripps Institution of Oceanography
University of California San Diego (UCSD)

9500 Gilman Dr. MC 0238
La Jolla, CA 92037
E-mail: mbianco [@] ucsd [DOT] edu

My Google Scholar profile
My CV
GitHub

About me

I am a postdoctoral scholar performing research in signal processing and machine learning, with applications to acoustics and geoscience. I am affiliated with the UCSD Noiselab and am grateful to be funded by an Office of Naval Research postdoctoral fellowship.

I received my B.S. degree in Aeronautical and Astronautical Engineering from Purdue University in 2007 and my Ph.D. from the UCSD Scripps Institution of Oceanography in 2018. My dissertation work focused on the development of machine learning and sparse modeling-based methods for inverse problems in acoustics and geophysics. Prior to UCSD, I was an engineer at Rocketyne where I developed and analyzed rocket and jet engine systems. This work was part of the NASA Space Shuttle and Constellation programs.

Events

2020/04/27 - Gave course lecture on dictionary learning, autoencoders, and variational autoencoders in UCSD ECE228: Machine learning for physical applications [Slides]
2019/12/02 - Chaired technical session “Signal Processing in Acoustics: General topics in Signal Processing II”, and organized music event at the 178th Acoustical Society of America Meeting in San Diego
2019/11/13 - Gave seminar at Division of Geological and Planetary Sciences, Caltech
2019/11/12 - Gave seminar at Department of Earth Sciences, USC
2019/10/23 - Gave seminar at Center for Acoustics and Vibration at the PennState College of Engineering
2019/9/07 - Gave seminar at the Southern California Earthquake Center Community Velocity Model workshop
2019/07/24 - Attended the CIFAR/amii Deep Learning and Reinforcement Learning Summer School (DLRLSS) in Edmonton, AB
2019/05/14 - Presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) in Brighton, UK
2019/05/06 - Course lectures on K-means, expectation maximization (EM), Gaussian mixture models (GMMs), and dictionary learning in UCSD ECE228: Machine learning for physical applications [Slides1][Slides2]
2019/03/15 - Presenting at the LANL Machine Learning in Solid Earth Geoscience workshop in Santa Fe, NM, USA
2018/10/21 - Attending the UMN IMA Workshop: Recent advances in machine learning and computational methods for geoscience
2018/09/27 - Mike defended his PhD! Dissertation title: “Machine learning and sparse modeling for geophysical inverse problems”
2018/06/25 - Two UCSD SRIP interns, Ruixian Liu and Hao Zhang, joined the NoiseLab to work on machine learning in geoscience
2018/06/08 - Gave a seminar at the Berkeley Seismological Laboratory
2018/06/07 - Gave a seminar at the Scripps Intitution of Oceanography AOS seminar series
2018/05/17 - Gave an invited talk at the 2018 Seismological Society of America meeting in Miami, FL [Slides]
2018/05/09 - Gave a lecture on dictionary learning in the UCSD ECE course ECE228: Machine learning for physical applications [Slides]
2018/04/15 - Gave a poster at IEEE International Conference on Acoustics, Speech, and Signal Processing in Calgary, Canada
2018/02/20 - Gave a talk at the Machine Learning in Solid Earth Geoscience Workshop in Santa Fe, NM

Research

My research concerns the development of physics-based machine learning and signal processing theory, with applications in acoustics for geophysical inference problems. My research topics include:

  • Machine learning in signal processing

  • Acoustic and seismic tomography

  • Source localization

Selected publications

  1. M.J. Bianco, S. Gannot, and P. Gerstoft, "Semi-supervised source localization with deep generative modeling", submitted 2020. [arXiv]

  2. D. Snover, C.W. Johnson, M.J. Bianco, and P. Gerstoft, "Deep clustering to identify sources of urban seismic noise in Long Beach, CA", submitted to Seismological Research Letters, 2020.

  3. M.J. Bianco, P. Gerstoft, J. Traer, E. Ozanich, M.A. Roch, S. Gannot, and C.-A. Deledalle, "Machine learning in acoustics: a review", Journal of the Acoustical Society of America, 2019. [pdf][DOI: 10.1121/1.5133944]

  4. M.J. Bianco, P. Gerstoft, K.B. Olsen, F.-C. Lin, "High-resolution seismic tomography of Long Beach, CA using machine learning", Nature Scientific Reports, 2019. [pdf][DOI: 10.1038/s41598-019-50381-z]

  5. Q. Kong, D.T. Trugman, Z.E. Ross, M.J. Bianco, B. Meade, and P. Gerstoft, "Machine learning in seismology-Turning data into insights", Seismological Research Letters, 2018. [DOI: 10.1785/0220180259]

  6. M.J. Bianco and P. Gerstoft, "Travel time tomography with adaptive dictionaries", IEEE Transactions on Computational Imaging, 2018, [pdf][DOI: 10.1109/TCI.2018.2862644] [code]

  7. M. Wagner, M. Bianco, S. Nannuru, and P. Gerstoft, ‘‘Array Shape Calibration using Low Rank Projections," 52nd IEEE Asilomar Conf. on Signals, Systems, and Computers, 2018.

  8. P. Gerstoft, C.F. Mecklenbrauker, W. Seong, and M. Bianco, ‘‘Introduction to compressive sensing in acoustics," Journal of the Acoustical Society of America}, 143, pp. 3731–3736, 2018. [DOI: 10.1121/1.5043089]

  9. M. Bianco and P. Gerstoft, " Adaptive travel time tomography with local sparsity ", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018. [pdf]

  10. M. Bianco and P. Gerstoft, "Regularization of geophysical inversion using dictionary learning", ICASSP, 2017. [pdf]

  11. M. Bianco and P. Gerstoft, "Dictionary learning of sound speed profiles", Journal of the Acoustical Society of America, 141(3), pp. 1749-1758, 2017. [pdf]

  12. M. Bianco and P. Gerstoft, "Compressive acoustic sound speed profile estimation", Journal of the Acoustical Society of America, 139(3), pp. EL90-94, 2016. [pdf]

My CV can be downloaded here