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
Jianlin
Guo
Dehong
Liu
Bingnan
Wang
Yebin
Wang
Wataru
Tsujita
Yanting
Ma
Joshua
Rapp
Matthew
Brand
Devesh K.
Jha
Chungwei
Lin
Hongbo
Sun
Jinyun
Zhang
Ankush
Chakrabarty
Anthony
Vetro
Avishai
Weiss
Abraham
Goldsmith
Jonathan
Le Roux
Suhas
Lohit
Tim K.
Marks
William S.
Yerazunis
Jose
Amaya
Anoop
Cherian
Radu
Corcodel
Vedang M.
Deshpande
Chiori
Hori
Sameer
Khurana
Pedro
Miraldo
Huifang
Sun
Abraham P.
Vinod
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 2024 Workshop Date: June 13, 2024
Where: IEEE International Conference on Communications (ICC)
MERL Contacts: Jianlin Guo; Philip V. Orlik; Kieran Parsons; Pu (Perry) Wang
Research Areas: Communications, Machine Learning, Signal ProcessingBrief- Jianlin Guo delivered a keynote titled "Private IoT Networks" in the IEEE International Conference on Communications (ICC) 2024 Workshop "Industrial Private 5G-and-Beyond Wireless Networks", held in Denver, Colorado from June 9-13. The ICC is one of two IEEE Communications Society’s flagship conferences.
Abstract: With the advent of private 5G-and-Beyond communication technologies, private IoT networks have been emerging. In private IoT networks, network owners have full control on the network resource management. However, to fully realize private IoT networks, the upper layer technologies need to be developed as well. This keynote presents machine learning based anomaly detection in manufacturing systems, innovative multipath TCP technologies over heterogeneous wireless IoT networks, novel channel resource scheduling in private 5G networks and efficient wireless coexistence of the heterogeneous wireless systems.
- Jianlin Guo delivered a keynote titled "Private IoT Networks" in the IEEE International Conference on Communications (ICC) 2024 Workshop "Industrial Private 5G-and-Beyond Wireless Networks", held in Denver, Colorado from June 9-13. The ICC is one of two IEEE Communications Society’s flagship conferences.
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TALK [MERL Seminar Series 2024] Fadel Adib presents talk titled Decoding Hidden Worlds: Unprecedented Sensing and Connectivity for Climate, Robotics, & Smart Environments Date & Time: Wednesday, April 3, 2024; 12:00 PM
Speaker: Fadel Adib, MIT & Cartesian
MERL Host: Wael Hajj Ali
Research Areas: Computational Sensing, Dynamical Systems, Signal ProcessingAbstract
This talk will cover a new generation of technologies that can sense, connect, and perceive the physical world in unprecedented ways. These technologies can uncover hidden worlds around us, promising transformative impact on areas spanning climate change monitoring, ocean mapping, healthcare, food security, supply chain, and even extraterrestrial exploration.
The talk will cover four core technologies invented by Prof. Adib and his team. The first is an ocean internet-of-things (IoT) that uses battery-free sensors for climate change monitoring, marine life discovery, and seafood production (aquaculture). The second is a new perception technology that enables robots to sense and manipulate hidden objects. The third is a new augmented reality headset with ``X-ray vision”, which extends human perception beyond line-of-sight. The fourth is a wireless sensing technology that can “see through walls” and monitor people’s vital signs (including their breathing, heart rate, and emotions), enabling smart environments that sense humans requiring any contact with the human body.
The talk will touch on the journey of these technologies from their inception at MIT to international collaborations and startups that are translating them to real-world impact in areas spanning healthcare, climate change, and supply chain.
See All News & Events for Signal Processing -
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Research Highlights
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Internships
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EA0070: Internship - Multi-modal sensor fusion
MERL is looking for a self-motivated intern to work on multi-modal sensor fusion for health condition monitoring and predictive maintenance of motor drive systems. The ideal candidate would be a Ph.D. candidate in electrical engineering or computer science with solid research background in signal processing and machine learning. Experience in motor drive system is a plus. The intern is expected to collaborate with MERL researchers to collect data, explore multi-modal data relationship, and prepare manuscripts for publications. The total duration is anticipated to be 3 months and the start date is flexible.
Required Specific Experience
- Experience with multi-modal sensor fusion.
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ST0081: Internship - Background Oriented Schlieren Tomography
The Computational Sensing team at MERL is seeking motivated and qualified individuals to develop algorithms that can perform background oriented schlieren (BOS) tomography. The project goal is to utilize both analytical and learning-based architectures to enable the reconstruction of 3D air flows in an indoor setting from BOS measurements coupled with physics informed machine learning. 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, large-scale optimization, differentiable scene rendering, learning-based modeling for imaging, and physics informed neural networks. Preferred skills include experience with schlieren tomography, inverse rendering, neural scene representation, and computational imaging hardware. 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.
Required Specific Experience
- Experience with differentiable/physics-based rendering.
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ST0068: Internship - Single-Photon Lidar Algorithms
The Computational Sensing Team at MERL is seeking an intern to work on estimation algorithms for single-photon lidar. The ideal candidate would be a PhD student with a strong background in statistical modeling, estimation theory, computational imaging, or inverse problems. The intern will collaborate with MERL researchers to design new lidar reconstruction algorithms, conduct simulations, and prepare results for publication. A detailed knowledge of single-photon detection, lidar, and Poisson processes is preferred. Hands-on optics experience is beneficial but not required. Strong programming skills in Python or MATLAB are essential. The duration is anticipated to be at least 3 months with a flexible start date.
See All Internships for Signal Processing -
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Recent Publications
- , "RETR: Multi-View Radar Detection Transformer for Indoor Perception", Advances in Neural Information Processing Systems (NeurIPS), November 2024.BibTeX TR2024-159 PDF
- @inproceedings{Yataka2024nov3,
- author = {Yataka, Ryoma and Cardace, Adriano and Wang, Pu and Boufounos, Petros T. and Takahashi, Ryuhei}},
- title = {RETR: Multi-View Radar Detection Transformer for Indoor Perception},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2024,
- month = nov,
- url = {https://www.merl.com/publications/TR2024-159}
- }
- , "Single-pixel imaging of spatio-temporal flows using differentiable latent dynamics", IEEE Transactions on Computational Imaging, October 2024.BibTeX TR2024-151 PDF
- @article{Sholokhov2024oct,
- author = {{Sholokhov, Aleksei and Nabi, Saleh and Rapp, Joshua and Brunton, Steven and Kutz, Nathan and Boufounos, Petros T. and Mansour, Hassan}},
- title = {Single-pixel imaging of spatio-temporal flows using differentiable latent dynamics},
- journal = {IEEE Transactions on Computational Imaging},
- year = 2024,
- month = oct,
- url = {https://www.merl.com/publications/TR2024-151}
- }
- , "Autonomous Horizon-Based Optical Navigation on Near-Planar Cislunar Libration Point Orbits", 4th Space Imaging Workshop, October 2024.BibTeX TR2024-139 PDF
- @inproceedings{Shimane2024oct,
- author = {Shimane, Yuri and Ho, Koki and Weiss, Avishai}},
- title = {Autonomous Horizon-Based Optical Navigation on Near-Planar Cislunar Libration Point Orbits},
- booktitle = {4th Space Imaging Workshop},
- year = 2024,
- month = oct,
- url = {https://www.merl.com/publications/TR2024-139}
- }
- , "Remaining Useful Life Estimation of Used Li-Ion Cells with Deep Learning Algorithms without First Life Information", IEEE Access, October 2024.BibTeX TR2024-155 PDF
- @article{Sanz-Gorrachategui2024oct,
- author = {Sanz-Gorrachategui, Ivan and Wang, Ye and Guillen-Asenio, Alejandro and Bono-Nuez, Antonio and Martín-del-Brío, Bonifacio and Orlik, Philip V. and Pastor-Flores, Pablo}},
- title = {Remaining Useful Life Estimation of Used Li-Ion Cells with Deep Learning Algorithms without First Life Information},
- journal = {IEEE Access},
- year = 2024,
- month = oct,
- url = {https://www.merl.com/publications/TR2024-155}
- }
- , "Spatial-Domain Mutual Interference Mitigation for MIMO-FMCW Automotive Radar", IEEE Transactions on Vehicular Technology, DOI: 10.1109/TVT.2024.3467917, September 2024.BibTeX TR2024-148 PDF
- @article{Jin2024sep,
- author = {Jin, Sian and Wang, Pu and Boufounos, Petros T. and Orlik, Philip V. and Takahashi, Ryuhei and Roy, Sumit}},
- title = {Spatial-Domain Mutual Interference Mitigation for MIMO-FMCW Automotive Radar},
- journal = {IEEE Transactions on Vehicular Technology},
- year = 2024,
- month = sep,
- doi = {10.1109/TVT.2024.3467917},
- issn = {1939-9359},
- url = {https://www.merl.com/publications/TR2024-148}
- }
- , "From Convexity to Strong Convexity and Beyond: Bridging The Gap In Convergence Rates", IEEE Conference on Decision and Control (CDC), September 2024.BibTeX TR2024-131 PDF
- @inproceedings{Romero2024sep,
- author = {Romero, Orlando and Benosman, Mouhacine and Pappas, George}},
- title = {From Convexity to Strong Convexity and Beyond: Bridging The Gap In Convergence Rates},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2024,
- month = sep,
- url = {https://www.merl.com/publications/TR2024-131}
- }
- , "ROBUST SLOT HARMONIC EXTRACTION IN VARYING SPEED OPERATIONS", 26TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES ICEM 2024, DOI: 10.1109/ICEM60801.2024.10700540, September 2024.BibTeX TR2024-119 PDF
- @inproceedings{Liu2024sep,
- author = {Liu, Dehong and Shinya, Tsurutashin}},
- title = {ROBUST SLOT HARMONIC EXTRACTION IN VARYING SPEED OPERATIONS},
- booktitle = {26TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES ICEM 2024},
- year = 2024,
- month = sep,
- publisher = {IEEE},
- doi = {10.1109/ICEM60801.2024.10700540},
- issn = {2473-2087},
- isbn = {979-8-3503-7060-7},
- url = {https://www.merl.com/publications/TR2024-119}
- }
- , "MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception", European Conference on Computer Vision (ECCV), DOI: 10.1007/978-3-031-72986-7_18, September 2024, pp. 306–322.BibTeX TR2024-117 PDF Data
- @inproceedings{Rahman2024sep,
- author = {Rahman, Mahbub and Yataka, Ryoma and Kato, Sorachi and Wang, Pu and Li, Peizhao and Cardace, Adriano and Boufounos, Petros T.}},
- title = {MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception},
- booktitle = {European Conference on Computer Vision (ECCV)},
- year = 2024,
- pages = {306–322},
- month = sep,
- publisher = {Springer},
- doi = {10.1007/978-3-031-72986-7_18},
- url = {https://www.merl.com/publications/TR2024-117}
- }
- , "RETR: Multi-View Radar Detection Transformer for Indoor Perception", Advances in Neural Information Processing Systems (NeurIPS), November 2024.
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