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)
Wang
Ye
Wang
Petros T.
Boufounos
Hassan
Mansour
Stefano
Di Cairano
Dehong
Liu
Bingnan
Wang
Jianlin
Guo
Yebin
Wang
Wataru
Tsujita
Joshua
Rapp
Yanting
Ma
Matthew
Brand
Devesh K.
Jha
Chungwei
Lin
Hongbo
Sun
Jinyun
Zhang
Ankush
Chakrabarty
Anthony
Vetro
Avishai
Weiss
Wael H.
Ali
Abraham
Goldsmith
Jonathan
Le Roux
Suhas
Lohit
Tim K.
Marks
William S.
Yerazunis
Anoop
Cherian
Radu
Corcodel
Vedang M.
Deshpande
Chiori
Hori
Pedro
Miraldo
Saviz
Mowlavi
Huifang
Sun
Abraham P.
Vinod
Kenji
Inomata
Jing
Liu
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Awards
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AWARD Best paper award at PHMAP 2023 Date: September 14, 2023
Awarded to: Dehong Liu, Anantaram Varatharajan, and Abraham Goldsmith
MERL Contacts: Abraham Goldsmith; Dehong Liu
Research Areas: Electric Systems, Signal ProcessingBrief- MERL researchers Dehong Liu, Anantaram Varatharajan, and Abraham Goldsmith were awarded one of three best paper awards at Asia Pacific Conference of the Prognostics and Health Management Society 2023 (PHMAP23) held in Tokyo from September 11th to 14th, 2023, for their co-authored paper titled 'Extracting Broken-Rotor-Bar Fault Signature of Varying-Speed Induction Motors.'
PHMAP is a biennial international conference specialized in prognostics and health management. PHMAP23 attracted more than 300 attendees from worldwide and published more than 160 regular papers from academia and industry including aerospace, production, civil engineering, electronics, and so on.
- MERL researchers Dehong Liu, Anantaram Varatharajan, and Abraham Goldsmith were awarded one of three best paper awards at Asia Pacific Conference of the Prognostics and Health Management Society 2023 (PHMAP23) held in Tokyo from September 11th to 14th, 2023, for their co-authored paper titled 'Extracting Broken-Rotor-Bar Fault Signature of Varying-Speed Induction Motors.'
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AWARD MERL’s Paper on Wi-Fi Sensing Earns Top 3% Paper Recognition at ICASSP 2023, Selected as a Best Student Paper Award Finalist Date: June 9, 2023
Awarded to: Cristian J. Vaca-Rubio, Pu Wang, Toshiaki Koike-Akino, Ye Wang, Petros Boufounos and Petar Popovski
MERL Contacts: Petros T. Boufounos; Toshiaki Koike-Akino; Pu (Perry) Wang; Ye Wang
Research Areas: Artificial Intelligence, Communications, Computational Sensing, Dynamical Systems, Machine Learning, Signal ProcessingBrief- A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.
Performed during Cristian’s stay at MERL first as a visiting Marie Skłodowska-Curie Fellow and then as a full-time intern in 2022, this work capitalizes on standards-compliant Wi-Fi signals to perform indoor localization and sensing. The paper uses a neural dynamic learning framework to address technical issues such as low sampling rate and irregular sampling intervals.
ICASSP, a flagship conference of the IEEE Signal Processing Society (SPS), was hosted on the Greek island of Rhodes from June 04 to June 10, 2023. ICASSP 2023 marked the largest ICASSP in history, boasting over 4000 participants and 6128 submitted papers, out of which 2709 were accepted.
- A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.
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AWARD Best Paper Award of 2022 IPSJ Transactions on Consumer Devices & Systems Date: March 27, 2023
Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
MERL Contacts: Jianlin Guo; Philip V. Orlik; Kieran Parsons
Research Areas: Communications, Signal ProcessingBrief- MELCO/MERL research paper “IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1GHz Frequency Bands” has won the Best Paper Award of the 2022 IPSJ Transactions on Consumer Devices and Systems. The Information Processing Society of Japan (IPSJ) award was established in 1970 and is conferred on the authors of particularly excellent papers, which are published in the IPSJ journals and transactions. Our paper was published by the IPSJ Transaction on Consumer Device and System Vol. 29 in 2021 and authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
See All Awards for Signal Processing -
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News & Events
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NEWS Jianlin Guo delivered a Keynote in IEEE ICC 2025 Workshop Date: June 8, 2025 - June 12, 2025
MERL Contacts: Jianlin Guo; Kieran Parsons
Research Areas: Communications, Signal ProcessingBrief- Jianlin Guo delivered a keynote titled "Multipath Transport in Industrial Private Wireless IoT Networks" in the IEEE International Conference on Communications (ICC) 2025 Workshop on "Industrial Private Beyond-5G Wireless Networks", held in Montreal, Canada from June 8-12. Jianlin also presented two conference papers, two workshop papers, and chaired two technical sessions. The ICC is one of two IEEE Communications Society’s flagship conferences.
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NEWS Toshiaki Koike-Akino to give a tutorial talk at ISIT 2025 Quantum Hackathon Date: June 22, 2025
Where: IEEE International Symposium on Information Theory (ISIT)
MERL Contact: Toshiaki Koike-Akino
Research Areas: Artificial Intelligence, Communications, Data Analytics, Machine Learning, Optimization, Signal Processing, Human-Computer Interaction, Information SecurityBrief- Toshiaki Koike-Akino is invited to present a tutorial talk at IEEE ISIT 2025 Quantum Hackathon, to be held at Ann Arbor, Michigan, USA. The talk, entitled "Emerging Quantum AI Technology", will discuss the recent trends, challenges, and applications of quantum artificial intelligence (QAI) technologies.
The ISIT 2025 Quantum Hackathon invites participants to explore the intersection of quantum computing and information theory. Participants will work with quantum simulators, available quantum hardware, and state-of-the-art development kits to create innovative solutions that connect quantum advancements with challenges in communication and signal processing.
The IEEE International Symposium on Information Theory (ISIT) is the flagship conference of the IEEE Information Theory Society. The symposium centers around the presentation in all of the areas of information theory, including source and channel coding, communication theory and systems, cryptography and security, detection and estimation, networks, pattern recognition and learning, statistics, stochastic processes and complexity, and signal processing.
- Toshiaki Koike-Akino is invited to present a tutorial talk at IEEE ISIT 2025 Quantum Hackathon, to be held at Ann Arbor, Michigan, USA. The talk, entitled "Emerging Quantum AI Technology", will discuss the recent trends, challenges, and applications of quantum artificial intelligence (QAI) technologies.
See All News & Events for Signal Processing -
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Research Highlights
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Internships
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CI0082: Internship - Quantum AI
MERL is excited to announce an internship opportunity in the field of Quantum Machine Learning (QML) and Quantum AI (QAI). We are seeking a highly motivated and talented individual to join our research team. This is an exciting opportunity to make a real impact in the field of quantum computing and AI, with the aim of publishing at leading research venues.
Responsibilities:
- Conduct cutting-edge research in quantum machine learning.
- Collaborate with a team of experts in quantum computing, deep learning, and signal processing.
- Develop and implement algorithms using PyTorch and PennyLane.
- Publish research results at leading research venues.
Qualifications:
- Currently pursuing a PhD or a post-graduate researcher in a relevant field.
- Strong background and solid publication records in quantum computing, deep learning, and signal processing.
- Proficient programming skills in PyTorch and PennyLane are highly desirable.
What We Offer:
- An opportunity to work on groundbreaking research in a leading research lab.
- Collaboration with a team of experienced researchers.
- A stimulating and supportive work environment.
If you are passionate about quantum machine learning and meet the above qualifications, we encourage you to apply. Please submit your resume and a brief cover letter detailing your research experience and interests. Join us at MERL and contribute to the future of quantum machine learning!
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EA0151: Internship - Physics-informed machine learning
MERL is looking for a self-motivated intern to work on physics-informed machine learning with application to electric machine condition monitoring and predictive maintenance. The ideal candidate would be a Ph.D. student in electrical engineering or computer science with solid research background in electric machines, signal processing, and machine learning. Proficiency in Python and Matlab is required. The intern is expected to collaborate with MERL researchers to build machine learning model for multi-modal data analysis, prepare technical reports, and draft manuscripts for scientific publications. The total duration is anticipated to be 3-6 months. The start date is flexible. This internship requires work that can only be done at MERL.
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ST0096: Internship - 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.
Required Specific Experience
- Experience with Python and Python Deep Learning Frameworks.
- Experience with FMCW radar and/or Depth Sensors.
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Openings
See All Openings at MERL -
Recent Publications
- , "Policy Optimization for PDE Control with a Warm Start", American Control Conference (ACC), July 2025.BibTeX TR2025-105 PDF
- @inproceedings{Zhang2025jul,
- author = {Zhang, Xiangyuan and Mowlavi, Saviz and Benosman, Mouhacine and Basar, Tamer},
- title = {{Policy Optimization for PDE Control with a Warm Start}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-105}
- }
- , "GNSS-RTK Factor Graph Optimization with Adaptive Ambiguity Noise", American Control Conference (ACC), July 2025.BibTeX TR2025-102 PDF
- @inproceedings{Hu2025jul,
- author = {Hu, Yingjie and {Di Cairano}, Stefano and Berntorp, Karl},
- title = {{GNSS-RTK Factor Graph Optimization with Adaptive Ambiguity Noise}},
- booktitle = {American Control Conference (ACC)},
- year = 2025,
- month = jul,
- url = {https://www.merl.com/publications/TR2025-102}
- }
- , "Machine Learning-Powered Radio Frequency Sensing: A Review", IEEE Sensors Journal, June 2025.BibTeX TR2025-099 PDF
- @article{Santra2025jun,
- author = {Santra, Avik and Wang, Pu and Shaker, George and Mysore, Bhavani Shankar and Dolmans, Guido and Chen, Yan and Shariati, Negin and Pandharipande, Ashish},
- title = {{Machine Learning-Powered Radio Frequency Sensing: A Review}},
- journal = {IEEE Sensors Journal},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-099}
- }
- , "Deep Generalized Canonical Correlation Analysis for Motor Fault Diagnosis", 2025 IEEE Industry Applications Society Annual Meeting (IAS), June 2025.BibTeX TR2025-085 PDF
- @inproceedings{Guo2025jun2,
- author = {Guo, Peikun and Liu, Dehong and Wang, Bingnan and Wang, Yebin and Inoue, Hiroshi and Kanemaru, Makoto},
- title = {{Deep Generalized Canonical Correlation Analysis for Motor Fault Diagnosis}},
- booktitle = {2025 IEEE Industry Applications Society Annual Meeting (IAS)},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-085}
- }
- , "IEEE 802.11bf Multistatic Sensing with Unsynchronized Receivers", IEEE Statistical Signal Processing Workshop (SSP), June 2025.BibTeX TR2025-080 PDF
- @inproceedings{Abdallah2025jun,
- author = {Abdallah, Ayah and Zhou, Shengli and Wang, Pu},
- title = {{IEEE 802.11bf Multistatic Sensing with Unsynchronized Receivers}},
- booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-080}
- }
- , "Indoor Airflow Imaging Using Physics-Informed Background-Oriented Schlieren Tomography", International Symposium on Computational Sensing (ISCS), June 2025.BibTeX TR2025-071 PDF
- @inproceedings{Teh2025jun,
- author = {Teh, Arjun and Ali, Wael H. and Rapp, Joshua and Mansour, Hassan},
- title = {{Indoor Airflow Imaging Using Physics-Informed Background-Oriented Schlieren Tomography}},
- booktitle = {International Symposium on Computational Sensing (ISCS)},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-071}
- }
- , "Pulse Design of Baseband Flux Control for Adiabatic Controlled-Phase Gates in Superconducting Circuits", Physical Review Applied, June 2025.BibTeX TR2025-070 PDF
- @article{Ding2025jun,
- author = {Ding, Qi and Oppenheim, Alan V. and Boufounos, Petros T. and Gustavsson, Simon and Grover, Jeffrey A. and Baran, Thomas A. and Oliver, William D.},
- title = {{Pulse Design of Baseband Flux Control for Adiabatic Controlled-Phase Gates in Superconducting Circuits}},
- journal = {Physical Review Applied},
- year = 2025,
- month = jun,
- url = {https://www.merl.com/publications/TR2025-070}
- }
- , "Rateless Deep Joint Source Channel Coding for 3D Point Cloud", IEEE Access, DOI: 10.1109/ACCESS.2025.3546514, Vol. 13, pp. 39585-39599, June 2025.BibTeX TR2025-069 PDF
- @article{Fujihashi2025jun,
- author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi},
- title = {{Rateless Deep Joint Source Channel Coding for 3D Point Cloud}},
- journal = {IEEE Access},
- year = 2025,
- volume = 13,
- pages = {39585--39599},
- month = jun,
- doi = {10.1109/ACCESS.2025.3546514},
- issn = {2169-3536},
- url = {https://www.merl.com/publications/TR2025-069}
- }
- , "Policy Optimization for PDE Control with a Warm Start", American Control Conference (ACC), July 2025.
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Videos
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Software & Data Downloads
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Learned Born Operator for Reflection Tomographic Imaging -
Stabilizing Subject Transfer in EEG Classification with Divergence Estimation -
Radar dEtection TRansformer -
Millimeter-wave Multi-View Radar Dataset -
Nonparametric Score Estimators -
Convergent Inverse Scattering using Optimization and Regularization -
One-Bit CRB
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