News & Events

1,237 News items, Awards, Events and Talks related to MERL and its staff.


  •  AWARD   Best Student Paper Award at IEEE ICASSP 2018
    Date: April 17, 2018
    Awarded to: Zhong-Qiu Wang
    MERL Contact: Jonathan Le Roux
    Research Areas: Speech & Audio, Artificial Intelligence
    Brief
    • Former MERL intern Zhong-Qiu Wang (Ph.D. Candidate at Ohio State University) has received a Best Student Paper Award at the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018) for the paper "Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation" by Zhong-Qiu Wang, Jonathan Le Roux, and John Hershey. The paper presents work performed during Zhong-Qiu's internship at MERL in the summer 2017, extending MERL's pioneering Deep Clustering framework for speech separation to a multi-channel setup. The award was received on behalf on Zhong-Qiu by MERL researcher and co-author Jonathan Le Roux during the conference, held in Calgary April 15-20.
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  •  NEWS   MERL presenting 9 papers at ICASSP 2018
    Date: April 15, 2018 - April 20, 2018
    Where: Calgary, AB
    MERL Contacts: Petros Boufounos; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip Orlik; Pu (Perry) Wang
    Research Areas: Computational Sensing, Digital Video, Speech & Audio, Artificial Intelligence, Signal Processing
    Brief
    • MERL researchers are presenting 9 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Calgary from April 15-20, 2018. Topics to be presented include recent advances in speech recognition, audio processing, and computational sensing. MERL is also a sponsor of the conference.

      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.
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  •  NEWS   LOBPCG method of Andrew Knyazev used on the K computer in Japan for superconductivity research
    Date: March 20, 2018
    Where: Asian Conference on Supercomputing Frontiers
    MERL Contact: Joseph Katz
    Research Areas: Control, Optimization
    Brief
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  •  NEWS   Andrew Knyazev (MERL) presents at WPI SIAM Industry Speaker Series about his career path
    Date: April 19, 2018
    Where: Room 202 Stratton Hall Worcester Polytechnic Institute
    MERL Contact: Joseph Katz
    Brief
    • Andrew Knyazev, Distinguished Research Scientist of MERL, has accepted an invitation to speak at the Worcester Polytechnic Institute (WPI) chapter of the Society for Industrial and Applied Mathematics (SIAM) located in Worcester, MA, at a series of industry speakers about different career paths for applied mathematicians.

      Andrew Knyazev studied at the Department of Computational Mathematics and Cybernetics of the Moscow State University in 1976-1981. He obtained PhD Degree in Numerical Mathematics at the Russian Academy of Sciences (RAS) in 1985. Knyazev worked at the Kurchatov Institute in 1981-1983 and at the Institute of Numerical Mathematics RAS in 1983-1992, where he collaborated with Academician Bakhvalov (Erdos number 3 via Kantorovich) on numerical methods for homogenization. In 1993-1994, Knyazev held a visiting position at the Courant Institute of Mathematical Sciences of New York University. From 1994 and until retirement in 2014, he was a Professor of Mathematics at the University of Colorado Denver (CU Denver), supported by many grants from the National Science Foundation and the United States Department of Energy. He was awarded the title of CU Denver Professor Emeritus and named the SIAM Fellow in 2016. During his 30 years in the academy, Knyazev supervised 7 PhD students. He is best known for his Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) eigenvalue solver. In 2012, Knyazev starts his industrial research career joining Mitsubishi Electric Research Laboratories (MERL) in Cambridge, MA, where he invents and develops algorithms for control, machine learning, data sciences, computer vision, coding, communications, material sciences, and signal processing, having 11 US patent applications filed (6 issued, 5 pending) and over 20 papers published.
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  •  NEWS   Mouhacine Benosman joins the Editorial Board of the International Journal of Adaptive Control and Signal Processing
    Date: March 19, 2018
    MERL Contact: Mouhacine Benosman
    Brief
    • MERL researcher Mouhacine Benosman has been appointed as a member of the Editorial Board of the International Journal of Adaptive Control and Signal Processing.

      The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.
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  •  NEWS   Andrew Knyazev (MERL) presents at the Schlumberger-Tufts U. Computational and Applied Math Seminar
    Date: April 10, 2018
    Research Areas: Machine Learning, Signal Processing
    Brief
    • Andrew Knyazev, Distinguished Research Scientist of MERL, has accepted an invitation to speak about his work on Big Data and spectral graph partitioning at the Schlumberger-Tufts U. Computational and Applied Math Seminar. A primary focus of this seminar series is on mathematical and computational aspects of remote sensing. A partial list of the topics of interest includes: numerical solution of large scale PDEs (a.k.a. forward problems); theory and numerical methods of inverse and ill-posed problems; imaging; related problems in numerical linear algebra, approximation theory, optimization and model reduction. The seminar meets on average once a month, the location alternates between Schlumberger's office in Cambridge, MA and the Tufts Medford Campus.

      Abstract: Data clustering via spectral graph partitioning requires constructing the graph Laplacian and solving the corresponding eigenvalue problem. We consider and motivate using negative edge weights in the graph Laplacian. Preconditioned iterative solvers for the Laplacian eigenvalue problem are discussed and preliminary numerical results are presented.
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  •  AWARD   Best Student Paper Award at the International Conference on Data Mining
    Date: November 30, 2017
    Awarded to: Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn Keogh
    MERL Contact: Daniel Nikovski
    Research Areas: Data Analytics
    Brief
    • Yan Zhu, a former MERL intern from the University of California at Riverside has won the Best Student Paper Award at the International Conference on Data Mining in 2017, for her work on time series chains, a novel primitive for time series analysis. The work was done in collaboration with Makoto Imamura, formerly at Information Technology Center/AI Department, and currently a professor at Tokai University in Tokyo, Japan, Daniel Nikovski from MERL, and Yan's advisor, Prof. Eamonn Keogh from UC Riverside, whose lab has had a long and fruitful collaboration with MERL and Mitsubishi Electric.
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  •  NEWS   MERL researchers will present 6 papers at OFC2018 optical communications conference
    Date: March 11, 2018 - March 15, 2018
    Where: Optical Fiber Communication Conference and Exhibition (OFC)
    MERL Contacts: Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons
    Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
    Brief
    • Six papers from the Optical Comms team will be presented at OFC2018 to be held in San Diego from 11-15 March 2018. The papers relate to high performance modulation formats, error correction coding and optimized pulse shape filtering for coherent optical links, and optical devices.
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  •  TALK   Theory and Applications of Sparse Model-Based Recurrent Neural Networks
    Date & Time: Tuesday, March 6, 2018; 12:00 PM
    Speaker: Scott Wisdom, Affectiva
    MERL Host: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • Recurrent neural networks (RNNs) are effective, data-driven models for sequential data, such as audio and speech signals. However, like many deep networks, RNNs are essentially black boxes; though they are effective, their weights and architecture are not directly interpretable by practitioners. A major component of my dissertation research is explaining the success of RNNs and constructing new RNN architectures through the process of "deep unfolding," which can construct and explain deep network architectures using an equivalence to inference in statistical models. Deep unfolding yields principled initializations for training deep networks, provides insight into their effectiveness, and assists with interpretation of what these networks learn.

      In particular, I will show how RNNs with rectified linear units and residual connections are a particular deep unfolding of a sequential version of the iterative shrinkage-thresholding algorithm (ISTA), a simple and classic algorithm for solving L1-regularized least-squares. This equivalence allows interpretation of state-of-the-art unitary RNNs (uRNNs) as an unfolded sparse coding algorithm. I will also describe a new type of RNN architecture called deep recurrent nonnegative matrix factorization (DR-NMF). DR-NMF is an unfolding of a sparse NMF model of nonnegative spectrograms for audio source separation. Both of these networks outperform conventional LSTM networks while also providing interpretability for practitioners.
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  •  NEWS   MERL presents two invited papers at SPIE Photonics West 2018
    Date: January 31, 2018
    Where: SPIE Photonics West
    MERL Contacts: Keisuke Kojima; Bingnan Wang
    Research Areas: Communications, Electronic and Photonic Devices, Signal Processing, Applied Physics
    Brief
    • MERL presents two invited papers at SPIE Photonics West 2018, to be held in San Francisco from Jan 27 to February 1. MERL researchers Bingnan Wang and Keisuke Kojima will give an talk on "Metamaterial absorber for THz polarimetric sensing" and "System and device technologies for coherent optical communications", respectively.
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  •  NEWS   MERL Researchers Demonstrate New Model-Based AI Learning Technology for Equipment Control
    Date: February 14, 2018
    Where: Tokyo, Japan
    MERL Contacts: Devesh Jha; Daniel Nikovski; Diego Romeres; William Yerazunis; Jeroen van Baar; Alan Sullivan
    Research Areas: Optimization, Computer Vision, Artificial Intelligence, Data Analytics, Robotics
    Brief
    • New technology for model-based AI learning for equipment control was demonstrated by MERL researchers at a recent press release event in Tokyo. The AI learning method constructs predictive models of the equipment through repeated trial and error, and then learns control rules based on these models. The new technology is expected to significantly reduce the cost and time needed to develop control programs in the future. Please see the link below for the full text of the Mitsubishi Electric press release.
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  •  NEWS   MERL Researchers Demonstrate Intelligent Wireless Communication Technology Supported with AI
    Date: February 14, 2018
    Where: Tokyo, Japan
    MERL Contacts: Mouhacine Benosman; Rui Ma; Yukimasa (Yuki) Nagai; Philip Orlik; Koon Hoo Teo
    Research Areas: Communications, Electronic and Photonic Devices, Signal Processing, Electric Systems
    Brief
    • MERL machine learning power amplifier and all-digital transmitter technologies that enable future intelligent wireless communications were reported at a recent press release event in Tokyo. Please see the link below for the full Mitsubishi Electric press release text.
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  •  NEWS   MERL's speech research featured in NPR's All Things Considered
    Date: February 5, 2018
    Where: National Public Radio (NPR)
    MERL Contact: Jonathan Le Roux
    Research Areas: Speech & Audio, Artificial Intelligence
    Brief
    • MERL's speech separation technology was featured in NPR's All Things Considered, as part of an episode of All Tech Considered on artificial intelligence, "Can Computers Learn Like Humans?". An example separating the overlapped speech of two of the show's hosts was played on the air.
      The technology is based on a proprietary deep learning method called Deep Clustering. It is the world's first technology that separates in real time the simultaneous speech of multiple unknown speakers recorded with a single microphone. It is a key step towards building machines that can interact in noisy environments, in the same way that humans can have meaningful conversations in the presence of many other conversations.
      A live demonstration was featured in Mitsubishi Electric Corporation's Annual R&D Open House last year, and was also covered in international media at the time.

      (Photo credit: Sam Rowe for NPR)

      Link:
      "Can Computers Learn Like Humans?" (NPR, All Things Considered)
      MERL Deep Clustering Demo
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  •  TALK   Advances in Accelerated Computing
    Date & Time: Friday, February 2, 2018; 12:00
    Speaker: Dr. David Kaeli, Northeastern University
    MERL Host: Abraham Goldsmith
    Research Areas: Control, Optimization, Machine Learning, Speech & Audio
    Brief
    • GPU computing is alive and well! The GPU has allowed researchers to overcome a number of computational barriers in important problem domains. But still, there remain challenges to use a GPU to target more general purpose applications. GPUs achieve impressive speedups when compared to CPUs, since GPUs have a large number of compute cores and high memory bandwidth. Recent GPU performance is approaching 10 teraflops of single precision performance on a single device. In this talk we will discuss current trends with GPUs, including some advanced features that allow them exploit multi-context grains of parallelism. Further, we consider how GPUs can be treated as cloud-based resources, enabling a GPU-enabled server to deliver HPC cloud services by leveraging virtualization and collaborative filtering. Finally, we argue for for new heterogeneous workloads and discuss the role of the Heterogeneous Systems Architecture (HSA), a standard that further supports integration of the CPU and GPU into a common framework. We present a new class of benchmarks specifically tailored to evaluate the benefits of features supported in the new HSA programming model.
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  •  NEWS   Scott A. Bortoff named Associate Editor, IEEE Control Systems Magazine
    Date: February 1, 2018
    MERL Contact: Scott Bortoff
    Research Area: Control
    Brief
    • Scott A. Bortoff has been selected by the IEEE Control System Society Board of Governors to serve as an Associate Editor of the IEEE Control Systems Magazine, effective January 1, 2018.
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  •  NEWS   Chiori Hori elected to IEEE Technical Committee on Speech and Language Processing
    Date: January 31, 2018
    MERL Contact: Chiori Hori
    Research Area: Speech & Audio
    Brief
    • Chiori Hori has been elected to serve on the Speech and Language Processing Technical Committee (SLTC) of the IEEE Signal Processing Society for a 3-year term.

      The SLTC promotes and influences all the technical areas of speech and language processing such as speech recognition, speech synthesis, spoken language understanding, speech to speech translation, spoken dialog management, speech indexing, information extraction from audio, and speaker and language recognition.
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  •  NEWS   Andrew Knyazev (MERL) invited to 2018 MathWorks Research Summit
    Date: June 2, 2018 - June 4, 2018
    Where: Newton, Massachusetts (USA)
    Research Areas: Control, Computer Vision, Dynamical Systems, Machine Learning, Data Analytics
    Brief
    • Dr. Andrew Knyazev of MERL has accepted an invitation to participate at the 2018 MathWorks Research Summit. The objective of the Research Summit is to provide a forum for leading researchers in academia and industry to explore the latest research and technology results and directions in computation and its use in technology, engineering, and science. The event aims to foster discussion among scientists, engineers, and research faculty about challenges and research opportunities for the respective communities with a particular interest in exploring cross-disciplinary research avenues.
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  •  NEWS   Anthony Vetro appointed to IEEE Signal Processing Society Conference Board
    Date: January 1, 2018
    MERL Contact: Anthony Vetro
    Brief
    • Anthony Vetro has been appointed to the Conference Board of the IEEE Signal Processing Society. His term is two years and expires in December 2019. He will also serve as a member of the Conference Board Executive Subcommittee.
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  •  NEWS   MERL presents 3 papers at ASRU 2017, John Hershey serves as general chair
    Date: December 16, 2017 - December 20, 2017
    Where: Okinawa, Japan
    MERL Contacts: Chiori Hori; Takaaki Hori; Jonathan Le Roux
    Research Areas: Speech & Audio, Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • MERL presented three papers at the 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), which was held in Okinawa, Japan from December 16-20, 2017. ASRU is the premier speech workshop, bringing together researchers from academia and industry in an intimate and collegial setting. More than 270 people attended the event this year, a record number. MERL's Speech and Audio Team was a key part of the organization of the workshop, with John Hershey serving as General Chair, Chiori Hori as Sponsorship Chair, and Jonathan Le Roux as Demonstration Chair. Two of the papers by MERL were selected among the 10 finalists for the best paper award. Mitsubishi Electric and MERL were also Platinum sponsors of the conference, with MERL awarding the MERL Best Student Paper Award.
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  •  NEWS   MERL among top Massachusetts organizations in patent activity
    Date: November 27, 2017
    MERL Contact: Richard (Dick) Waters
    Brief
    • A recent report by JLL finds that MERL is among the top 10 organizations in Massachusetts in terms of patent filings in 2010-2015. This is especially notable since MERL is by far the smallest organization in that group.
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