Signal Processing
Acquisition and processing of information.
Our research in the area of signal processing encompasses a wide range of work in the areas of communications, sensing, estimation, localization, and speech and visual information processing. We explore novel approaches for signal acquisition and coding, methods to filter and recover signals in the presence of noise and other degrading factors, and techniques that infer meaning from the processed signals.
Quick Links
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Researchers
Toshiaki
Koike-Akino
Philip V.
Orlik
Kieran
Parsons
Pu
(Perry)
WangYe
Wang
Kyeong Jin
(K.J.)
KimKarl
Berntorp
Petros T.
Boufounos
Hassan
Mansour
Bingnan
Wang
Yebin
Wang
Stefano
Di Cairano
Jianlin
Guo
Dehong
Liu
Koon Hoo
Teo
Mouhacine
Benosman
Marcus
Greiff
Devesh K.
Jha
Chungwei
Lin
Hongbo
Sun
Jinyun
Zhang
Yanting
Ma
Marcel
Menner
Anthony
Vetro
Ankush
Chakrabarty
Tim K.
Marks
Rien
Quirynen
Avishai
Weiss
William S.
Yerazunis
Jose
Amaya
Matthew E.
Brand
Jonathan
Le Roux
Suhas
Lohit
Huifang
Sun
Jay
Thornton
Joshua
Rapp
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Awards
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AWARD Joshua Rapp wins Best Dissertation Award from the IEEE Signal Processing Society Date: December 20, 2021
Awarded to: Joshua Rapp
MERL Contact: Joshua Rapp
Research Areas: Computational Sensing, Signal ProcessingBrief- Joshua Rapp has won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society.
The award recognizes a PhD thesis completed on a signal processing subject within the past three years for its relevant work in signal processing while stimulating further research in the field.
Dr. Rapp completed his PhD at Boston University in 2020 with a thesis entitled "Probabilistic Modeling for Single-Photon Lidar." The dissertation tackles challenges of the acquisition and processing of 3D depth maps reconstructed from time-of-flight data captured one photon at a time.
The award will be presented at the 2022 IEEE International Conference on Image Processing (ICIP) in France.
- Joshua Rapp has won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society.
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AWARD Petros Boufounos Elevated to IEEE Fellow Date: January 1, 2022
Awarded to: Petros T. Boufounos
MERL Contact: Petros T. Boufounos
Research Areas: Computational Sensing, Signal ProcessingBrief- MERL’s Petros Boufounos has been elevated to IEEE Fellow, effective January 2022, for “contributions to compressed sensing.”
IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society. Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.
- MERL’s Petros Boufounos has been elevated to IEEE Fellow, effective January 2022, for “contributions to compressed sensing.”
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AWARD Toshiaki Koike-Akino elected Fellow of Optica Date: November 18, 2021
Awarded to: Toshiaki Koike-Akino
MERL Contact: Toshiaki Koike-Akino
Research Areas: Communications, Electronic and Photonic Devices, Signal ProcessingBrief- Toshiaki Koike-Akino's research activities in communications, error control coding and optical technologies at MERL have earned him election as a Fellow Member of Optica (formerly OSA), the foremost professional association in optics and photonics worldwide. Fellow membership in Optica is limited to no more than ten percent of the membership and is reserved for members who have served with distinction in the advancement of optics and photonics. Koike-Akino is one of 106 members from 24 countries in Optica’s 2022 Fellows Class, elected during the Board of Directors of Optica meeting held on 2nd of November, 2021.
“Congratulations to the 2022 Optica Fellows,” said 2021 President Connie Chang-Hasnain, University of California, Berkeley, USA. “These members exemplify what it means to be a leader in optics and photonics. Your election, by your peers, confirms the important contributions made within our field. Thank you for your dedication to Optica, and for advancing the science of light.”
Koike-Akino's elevation to Fellow is specifically “for outstanding and innovative contributions to R&D in enabling technologies for optical communications, including nonlinear equalizers, high-dimensional modulations, and FEC (Forward Error Correction),” said Meredith Smith, Director, Optica Awards and Honors Office. "Again, congratulations on joining this esteemed group of Optica members."
About Optica
Optica (formerly OSA) is dedicated to promoting the generation, application, archiving and dissemination of knowledge in optics and photonics worldwide. Founded in 1916, it is the leading organization for scientists, engineers, business professionals, students and others interested in the science of light. Optica’s renowned publications, meetings, online resources and in-person activities fuel discoveries, shape real-life applications and accelerate scientific, technical and educational achievement.
- Toshiaki Koike-Akino's research activities in communications, error control coding and optical technologies at MERL have earned him election as a Fellow Member of Optica (formerly OSA), the foremost professional association in optics and photonics worldwide. Fellow membership in Optica is limited to no more than ten percent of the membership and is reserved for members who have served with distinction in the advancement of optics and photonics. Koike-Akino is one of 106 members from 24 countries in Optica’s 2022 Fellows Class, elected during the Board of Directors of Optica meeting held on 2nd of November, 2021.
See All Awards for Signal Processing -
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News & Events
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NEWS MERL presenting 8 papers at ICASSP 2022 Date: May 22, 2022 - May 27, 2022
Where: Singapore
MERL Contacts: Anoop Cherian; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Tim K. Marks; Philip V. Orlik; Kuan-Chuan Peng; Pu (Perry) Wang; Gordon Wichern
Research Areas: Artificial Intelligence, Computer Vision, Signal Processing, Speech & AudioBrief- MERL researchers are presenting 8 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Singapore from May 22-27, 2022. A week of virtual presentations also took place earlier this month.
Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, and classification.
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
- MERL researchers are presenting 8 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Singapore from May 22-27, 2022. A week of virtual presentations also took place earlier this month.
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NEWS MERL Scientists Presenting 5 Papers at IEEE International Conference on Communications (ICC) 2022 Date: May 16, 2022 - May 20, 2022
Where: Seoul, Korea
MERL Contacts: Jianlin Guo; Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Philip V. Orlik; Kieran Parsons; Pu (Perry) Wang; Ye Wang
Research Areas: Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Machine Learning, Signal ProcessingBrief- MERL Connectivity & Information Processing Team scientists remotely presented 5 papers at the IEEE International Conference on Communications (ICC) 2022, held in Seoul Korea on May 16-20, 2022. Topics presented include recent advancements in communications technologies, deep learning methods, and quantum machine learning (QML). Presentation videos are also found on our YouTube channel. In addition, K. J. Kim organized "Industrial Private 5G-and-beyond Wireless Networks Workshop" at the conference.
IEEE ICC is one of two IEEE Communications Society’s flagship conferences (ICC and Globecom). Each year, close to 2,000 attendees from over 70 countries attend IEEE ICC to take advantage of a program which consists of exciting keynote session, robust technical paper sessions, innovative tutorials and workshops, and engaging industry sessions. This 5-day event is known for bringing together audiences from both industry and academia to learn about the latest research and innovations in communications and networking technology, share ideas and best practices, and collaborate on future projects.
- MERL Connectivity & Information Processing Team scientists remotely presented 5 papers at the IEEE International Conference on Communications (ICC) 2022, held in Seoul Korea on May 16-20, 2022. Topics presented include recent advancements in communications technologies, deep learning methods, and quantum machine learning (QML). Presentation videos are also found on our YouTube channel. In addition, K. J. Kim organized "Industrial Private 5G-and-beyond Wireless Networks Workshop" at the conference.
See All News & Events for Signal Processing -
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Research Highlights
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Internships
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ST1750: THz (Terahertz) Sensing
The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in THz (Terahertz) sensing. Expertise in statistical inference, unsupervised anomaly detection, and deep learning (spatial-temporal representation learning) is required. Previous hands-on experience in THz data analysis is a plus. Familiarity with python and deep learning libraries is a must. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments with collaborators, and prepare results for patents and publication. The expected duration of the internship is 3 months with a flexible start date.
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ST1762: Computational Sensing Technologies
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, deep learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/THz imaging, joint communications and sensing, multimodal sensor fusion, object or human tracking, 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.
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ST1763: Technologies for Multimodal Tracking and Imaging
MERL is seeking a motivated intern to assist in developing hardware and algorithms for multimodal imaging applications. The project involves integration of radar, camera, and depth sensors in a variety of sensing scenarios. The ideal candidate should have experience with FMCW radar and/or depth sensing, and be fluent in Python and scripting methods. Familiarity with optical tracking of humans and experience with hardware prototyping is desired. Good knowledge of computational imaging and/or radar imaging methods is a plus.
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Openings
See All Openings at MERL -
Recent Publications
- "AutoVAE: Mismatched Variational Autoencoder with Irregular Posterior Prior Pairing", IEEE International Symposium on Information Theory (ISIT), July 2022.BibTeX TR2022-071 PDF Video Presentation
- @inproceedings{Koike-Akino2022jul,
- author = {Koike-Akino, Toshiaki and Wang, Ye},
- title = {AutoVAE: Mismatched Variational Autoencoder with Irregular Posterior Prior Pairing},
- booktitle = {IEEE International Symposium on Information Theory (ISIT)},
- year = 2022,
- month = jul,
- url = {https://www.merl.com/publications/TR2022-071}
- }
, - "Location and Driver-Specific Vehicle Adaptation Using Crowdsourced Data", European Control Conference (ECC), DOI: 10.23919/ECC55457.2022.9838135, July 2022, pp. 769-774.BibTeX TR2022-095 PDF
- @inproceedings{Menner2022jul,
- author = {Menner, Marcel and Ma, Ziyi and Berntorp, Karl and Di Cairano, Stefano},
- title = {Location and Driver-Specific Vehicle Adaptation Using Crowdsourced Data},
- booktitle = {European Control Conference (ECC)},
- year = 2022,
- pages = {769--774},
- month = jul,
- doi = {10.23919/ECC55457.2022.9838135},
- url = {https://www.merl.com/publications/TR2022-095}
- }
, - "Bayesian Sensor Fusion of GNSS and Camera With Outlier Adaptation for Vehicle Positioning", International Conference on Information Fusion (FUSION), July 2022.BibTeX TR2022-093 PDF
- @inproceedings{Berntorp2022jul,
- author = {Berntorp, Karl and Greiff, Marcus and Di Cairano, Stefano},
- title = {Bayesian Sensor Fusion of GNSS and Camera With Outlier Adaptation for Vehicle Positioning},
- booktitle = {International Conference on Information Fusion (FUSION)},
- year = 2022,
- month = jul,
- url = {https://www.merl.com/publications/TR2022-093}
- }
, - "Dynamic Clustering for GNSS Positioning with Multiple Receivers", International Conference on Information Fusion (FUSION), July 2022.BibTeX TR2022-094 PDF
- @inproceedings{Greiff2022jul,
- author = {Greiff, Marcus and Di Cairano, Stefano and Berntorp, Karl},
- title = {Dynamic Clustering for GNSS Positioning with Multiple Receivers},
- booktitle = {International Conference on Information Fusion (FUSION)},
- year = 2022,
- month = jul,
- url = {https://www.merl.com/publications/TR2022-094}
- }
, - "DNN-assisted phase distance tuned PSK modulation for PAM4-to-QPSK format conversion gateway node", Optics Express, DOI: 10.1364/OE.449812, Vol. 30, No. 7, pp. 10866-10876, June 2022.BibTeX TR2022-091 PDF
- @article{Kodama2022jun,
- author = {Kodama, Takahiro and Koike-Akino, Toshiaki and Millar, David S. and Kojima, Keisuke and Parsons, Kieran},
- title = {DNN-assisted phase distance tuned PSK modulation for PAM4-to-QPSK format conversion gateway node},
- journal = {Optics Express},
- year = 2022,
- volume = 30,
- number = 7,
- pages = {10866--10876},
- month = jun,
- doi = {10.1364/OE.449812},
- url = {https://www.merl.com/publications/TR2022-091}
- }
, - "Spatial-Domain Mutual Interference Mitigation for Slow-Time MIMO-FMCW Automotive Radar", IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), June 2022.BibTeX TR2022-067 PDF
- @inproceedings{Jin2022jun,
- author = {Jin, Sian and Pu, Wang and Boufounos, Petros T. and Orlik, Philip V. and Takahashi, Ryuhei and Roy, Sumit},
- title = {Spatial-Domain Mutual Interference Mitigation for Slow-Time MIMO-FMCW Automotive Radar},
- booktitle = {IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)},
- year = 2022,
- month = jun,
- url = {https://www.merl.com/publications/TR2022-067}
- }
, - "AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communications", IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), June 2022.BibTeX TR2022-068 PDF Video Presentation
- @inproceedings{Koike-Akino2022jun,
- author = {Koike-Akino, Toshiaki and Wang, Pu and Wang, Ye},
- title = {AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communications},
- booktitle = {IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)},
- year = 2022,
- month = jun,
- url = {https://www.merl.com/publications/TR2022-068}
- }
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- "AutoVAE: Mismatched Variational Autoencoder with Irregular Posterior Prior Pairing", IEEE International Symposium on Information Theory (ISIT), July 2022.
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Videos
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Toshiaki Koike-Akino Gives Seminar Talk at IEEE Boston Photonics
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[MERL Seminar Series 2021] Deep probabilistic regression
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[MERL Seminar Series 2021] Reconfigurable Intelligent Surfaces for Wireless Communications
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Application of Deep Learning for Nanophotonic Device Design (Invited)
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Multiview Sensing with Unknown Permutations: An Optimal Transport Approach
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Imaging for inverse scattering in Reflection Tomography
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All Digital Transmitter
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Machine Learning Power Amplifier
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Polar Coding with Chemical Reaction Networks for Molecular Communications
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EMI reduction in PWM inverters using adaptive frequency modulated carriers
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Through-the-Wall Imaging
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Software Downloads