News & Events

1,182 News items, Awards, Events and Talks related to MERL and its staff.




  •  NEWS   MERL researchers will present 5 papers at ICC2017 wireless communications conference
    Date: May 21, 2017 - May 25, 2017
    Where: IEEE International Conference on Communications (ICC)
    MERL Contacts: Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Philip V. Orlik; Milutin Pajovic; Pu (Perry) Wang; Ye Wang
    Research Areas: Electronics & Communications, Wireless Communications & Signal Processing
    Brief
    • Five papers from the Wireless Comms team will be presented at ICC2017 to be held in Paris from 21-25 May 2017. The papers relate to channel estimation and adaptive transmission for mmWave, noncoherent MIMO, error correction coding, and video transmission.
  •  
  •  EVENT   Society for Industrial and Applied Mathematics panel for students on careers in industry
    Date & Time: Monday, July 10, 2017; 6:15 PM - 7:15 PM
    Speaker: Andrew Knyazev and other panelists, MERL
    MERL Contacts: Joseph Katz; Andrew Knyazev
    Location: David Lawrence Convention Center, Pittsburgh PA
    Research Areas: Electronics & Communications, Multimedia, Data Analytics, Computer Vision, Mechatronics, Algorithms, Advanced Control Systems, Computational Geometry, Computational Photography, Computational Sensing, Decision Optimization, Digital Video, Dynamical Systems, Information Security, Machine Learning, Optical Communications & Devices, Power & RF, Predictive Modeling, Speech & Audio, Wireless Communications & Signal Processing
    Brief
    • Andrew Knyazev accepted an invitation to represent MERL at the panel on Student Careers in Business, Industry and Government at the annual meeting of the Society for Industrial and Applied Mathematics (SIAM).

      The format consists of a five minute introduction by each of the panelists covering their background and an overview of the mathematical and computational challenges at their organization. The introductions will be followed by questions from the students.
  •  
  •  NEWS   MERL Researcher Tim Marks presents an invited talk at MIT Lincoln Laboratory
    Date: April 27, 2017
    Where: Lincoln Laboratory, Massachusetts Institute of Technology
    MERL Contact: Tim K. Marks
    Research Areas: Computer Vision, Machine Learning
    Brief
    • MERL researcher Tim K. Marks presented an invited talk as part of the MIT Lincoln Laboratory CORE Seminar Series on Biometrics. The talk was entitled "Robust Real-Time 2D Face Alignment and 3D Head Pose Estimation."

      Abstract: Head pose estimation and facial landmark localization are key technologies, with widespread application areas including biometrics and human-computer interfaces. This talk describes two different robust real-time face-processing methods, each using a different modality of input image. The first part of the talk describes our system for 3D head pose estimation and facial landmark localization using a commodity depth sensor. The method is based on a novel 3D Triangular Surface Patch (TSP) descriptor, which is viewpoint-invariant as well as robust to noise and to variations in the data resolution. This descriptor, combined with fast nearest-neighbor lookup and a joint voting scheme, enable our system to handle arbitrary head pose and significant occlusions. The second part of the talk describes our method for face alignment, which is the localization of a set of facial landmark points in a 2D image or video of a face. Face alignment is particularly challenging when there are large variations in pose (in-plane and out-of-plane rotations) and facial expression. To address this issue, we propose a cascade in which each stage consists of a Mixture of Invariant eXperts (MIX), where each expert learns a regression model that is specialized to a different subset of the joint space of pose and expressions. We also present a method to include deformation constraints within the discriminative alignment framework, which makes the algorithm more robust. Both our 3D head pose and 2D face alignment methods outperform the previous results on standard datasets. If permitted, I plan to end the talk with a live demonstration.
  •  
  •  NEWS   MERL researcher Tim Marks presents invited talk at University of Utah
    Date: April 10, 2017
    Where: University of Utah School of Computing
    MERL Contact: Tim K. Marks
    Research Areas: Computer Vision, Machine Learning
    Brief
    • MERL researcher Tim K. Marks presented an invited talk at the University of Utah School of Computing, entitled "Action Detection from Video and Robust Real-Time 2D Face Alignment."

      Abstract: The first part of the talk describes our multi-stream bi-directional recurrent neural network for action detection from video. In addition to a two-stream convolutional neural network (CNN) on full-frame appearance (images) and motion (optical flow), our system trains two additional streams on appearance and motion that have been cropped to a bounding box from a person tracker. To model long-term temporal dynamics within and between actions, the multi-stream CNN is followed by a bi-directional Long Short-Term Memory (LSTM) layer. Our method outperforms the previous state of the art on two action detection datasets: the MPII Cooking 2 Dataset, and a new MERL Shopping Dataset that we have made available to the community. The second part of the talk describes our method for face alignment, which is the localization of a set of facial landmark points in a 2D image or video of a face. Face alignment is particularly challenging when there are large variations in pose (in-plane and out-of-plane rotations) and facial expression. To address this issue, we propose a cascade in which each stage consists of a Mixture of Invariant eXperts (MIX), where each expert learns a regression model that is specialized to a different subset of the joint space of pose and expressions. We also present a method to include deformation constraints within the discriminative alignment framework, which makes the algorithm more robust. Our face alignment system outperforms the previous results on standard datasets. The talk will end with a live demo of our face alignment system.
  •  
  •  EVENT   MERL to participate in Xconomy Forum on AI & Robotics
    Date & Time: Tuesday, March 28, 2017; 1:30 - 5:30PM
    MERL Contacts: John R. Hershey; Joseph Katz; Daniel N. Nikovski; Alan Sullivan; Jay E. Thornton; Anthony Vetro; Richard C. (Dick) Waters; Jinyun Zhang
    Location: Google (355 Main St., 5th Floor, Cambridge MA)
    Research Areas: Multimedia, Data Analytics, Computer Vision, Mechatronics
    Brief
    • How will AI and robotics reshape the economy and create new opportunities (and challenges) across industries? Who are the hottest companies that will compete with the likes of Google, Amazon, and Uber to create the future? And what are New England innovators doing to strengthen the local cluster and help lead the national discussion?

      MERL will be participating in Xconomy's third annual conference on AI and robotics in Boston to address these questions. MERL President & CEO, Dick Waters, will be on a panel discussing the status and future of self-driving vehicles. Lab members will also be on hand demonstrate and discuss recent advances AI and robotics technology.

      The agenda and registration for the event can be found online: https://xconomyforum85.eventbrite.com
  •  
  •  NEWS   MERL researchers will present 5 papers at OFC2017 optical communications conference
    Date: March 19, 2017 - March 23, 2017
    Where: Optical Fiber Communication Conference and Exhibition (OFC)
    MERL Contacts: Toshiaki Koike-Akino; Keisuke Kojima; David S. Millar; Milutin Pajovic; Kieran Parsons
    Research Areas: Electronics & Communications, Optical Communications & Devices, Signal Processing
    Brief
    • Five papers from the Optical Comms team will be presented at OFC2017 to be held in Los Angeles from 19-23 March 2017. The papers relate to 1Tb/s optical transmission, high performance modulation formats and error correction coding for coherent optical links and precoding for plastic optical fiber links.
  •  
  •  EVENT   MERL hosts Boston Imaging and Vision Meetup
    Date & Time: Tuesday, January 17, 2017; 6:00 pm
    Speaker: Tim Marks, Esra Cansizoglu and Carl Vondrick, MERL and MIT
    MERL Contact: Alan Sullivan
    Location: 201 Broadway, Cambridge, MA
    Research Areas: Computer Vision, Computational Photography
    Brief
    • MERL was pleased to host the Boston Imaging and Vision Meetup held on January 17. The meetup is an informal gathering of people interested in the field of computer imaging and vision. According to the group's website "the meetup provides an opportunity for the image processing/computer vision community to network, socialize and learn". The event held at MERL featured three speakers, Tim Marks and Esra Cansizoglu from MERL, as well as Carl Vondrick, an MIT CS graduate student in the group of Prof. Antonio Torralba. Roughly 70 people attended to eat pizza, hear the speakers and network.
  •  
  •  TALK   Generative Model-Based Text-to-Speech Synthesis
    Date & Time: Wednesday, February 1, 2017; 12:00-13:00
    Speaker: Dr. Heiga ZEN, Google
    MERL Host: Chiori Hori
    Research Areas: Multimedia, Speech & Audio
    Brief
    • Recent progress in generative modeling has improved the naturalness of synthesized speech significantly. In this talk I will summarize these generative model-based approaches for speech synthesis such as WaveNet, a deep generative model of raw audio waveforms. We show that WaveNets are able to generate speech which mimics any human voice and which sounds more natural than the best existing Text-to-Speech systems.
      See https://deepmind.com/blog/wavenet-generative-model-raw-audio/ for further details.
  •  
  •  NEWS   MERL to present 10 papers at ICASSP 2017
    Date: March 5, 2017 - March 9, 2017
    Where: New Orleans
    MERL Contacts: Petros T. Boufounos; Chen Feng; John R. Hershey; Takaaki Hori; Ulugbek Kamilov; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Dong Tian; Anthony Vetro; Ye Wang; Shinji Watanabe
    Research Areas: Multimedia, Computer Vision, Computational Geometry, Computational Sensing, Digital Video, Information Security, Speech & Audio
    Brief
    • MERL researchers will presented 10 papers at the upcoming IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), to be held in New Orleans from March 5-9, 2017. Topics to be presented include recent advances in speech recognition and audio processing; graph signal processing; computational imaging; and privacy-preserving data analysis.

      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.
  •  
  •  NEWS   MERL's Power Amplifier Technologies featured in Mitsubishi Electric Corporation press release
    Date: January 12, 2017
    Where: Tokyo, Japan
    MERL Contact: Rui Ma
    Research Areas: Electronics & Communications, Power & RF, Wireless Communications & Signal Processing, RF, Signal Processing, Wireless Communications
    Brief
    • Mitsubishi Electric Corporation and Mitsubishi Electric Research Laboratories (MERL) announced today the development of an ultra-wideband gallium nitride (GaN) Doherty power amplifier for next generation base stations that is compatible with a world-leading range (company estimate) of frequency bands above 3GHz to cover an operating bandwidth of 600MHz. The technology is expected to help reduce the size and energy consumption of next generation wireless base stations.

      Please see the link below for the full Mitsubishi Electric press release text.
  •  
  •  AWARD   APSIPA recognizes Anthony Vetro as a 2016 Industrial Distinguished Leader
    Date: October 15, 2016
    Awarded to: Anthony Vetro
    MERL Contact: Anthony Vetro
    Research Area: Multimedia
    Brief
    • Anthony Vetro was recognized by APSIPA (Asia-Pacific Signal and Information Processing Association) as a 2016 Industrial Distinguished Leader. This distinction is reserved for selected APSIPA members with extraordinary accomplishments in any of the fields related to APSIPA scope. A list of past recipients can be found online: http://www.apsipa.org/industrial.htm.
  •  
  •  TALK   High-Dimensional Analysis of Stochastic Optimization Algorithms for Estimation and Learning
    Date & Time: Tuesday, December 13, 2016; Noon
    Speaker: Yue M. Lu, John A. Paulson School of Engineering and Applied Sciences, Harvard University
    MERL Host: Petros T. Boufounos
    Research Areas: Multimedia, Computational Sensing, Machine Learning
    Brief
    • In this talk, we will present a framework for analyzing, in the high-dimensional limit, the exact dynamics of several stochastic optimization algorithms that arise in signal and information processing. For concreteness, we consider two prototypical problems: sparse principal component analysis and regularized linear regression (e.g. LASSO). For each case, we show that the time-varying estimates given by the algorithms will converge weakly to a deterministic "limiting process" in the high-dimensional limit. Moreover, this limiting process can be characterized as the unique solution of a nonlinear PDE, and it provides exact information regarding the asymptotic performance of the algorithms. For example, performance metrics such as the MSE, the cosine similarity and the misclassification rate in sparse support recovery can all be obtained by examining the deterministic limiting process. A steady-state analysis of the nonlinear PDE also reveals interesting phase transition phenomena related to the performance of the algorithms. Although our analysis is asymptotic in nature, numerical simulations show that the theoretical predictions are accurate for moderate signal dimensions.
  •  
  •  TALK   Reduced basis methods and their application in data science and uncertainty quantification
    Date & Time: Monday, December 12, 2016; 12:00 PM
    Speaker: Yanlai Chen, Department of Mathematics at the University of Massachusetts Dartmouth
    MERL Host: Andrew Knyazev
    Research Areas: Algorithms, Advanced Control Systems, Dynamical Systems
    Brief
    • Models of reduced computational complexity is indispensable in scenarios where a large number of numerical solutions to a parametrized problem are desired in a fast/real-time fashion. These include simulation-based design, parameter optimization, optimal control, multi-model/scale analysis, uncertainty quantification. Thanks to an offline-online procedure and the recognition that the parameter-induced solution manifolds can be well approximated by finite-dimensional spaces, reduced basis method (RBM) and reduced collocation method (RCM) can improve efficiency by several orders of magnitudes. The accuracy of the RBM solution is maintained through a rigorous a posteriori error estimator whose efficient development is critical and involves fast eigensolves.

      In this talk, I will give a brief introduction of the RBM/RCM, and explain how they can be used for data compression, face recognition, and significantly delaying the curse of dimensionality for uncertainty quantification.
  •  
  •  TALK   Collaborative dictionary learning from big, distributed data
    Date & Time: Friday, December 2, 2016; 11:00 AM
    Speaker: Prof. Waheed Bajwa, Rutgers University
    MERL Host: Petros T. Boufounos
    Research Areas: Multimedia, Computational Sensing
    Brief
    • While distributed information processing has a rich history, relatively less attention has been paid to the problem of collaborative learning of nonlinear geometric structures underlying data distributed across sites that are connected to each other in an arbitrary topology. In this talk, we discuss this problem in the context of collaborative dictionary learning from big, distributed data. It is assumed that a number of geographically-distributed, interconnected sites have massive local data and they are interested in collaboratively learning a low-dimensional geometric structure underlying these data. In contrast to some of the previous works on subspace-based data representations, we focus on the geometric structure of a union of subspaces (UoS). In this regard, we propose a distributed algorithm, termed cloud K-SVD, for collaborative learning of a UoS structure underlying distributed data of interest. The goal of cloud K-SVD is to learn an overcomplete dictionary at each individual site such that every sample in the distributed data can be represented through a small number of atoms of the learned dictionary. Cloud K-SVD accomplishes this goal without requiring communication of individual data samples between different sites. In this talk, we also theoretically characterize deviations of the dictionaries learned at individual sites by cloud K-SVD from a centralized solution. Finally, we numerically illustrate the efficacy of cloud K-SVD in the context of supervised training of nonlinear classsifiers from distributed, labaled training data.
  •  
  •  EVENT   MERL organizes Workshop on End-to-End Speech and Audio Processing at NIPS 2016
    Date: Saturday, December 10, 2016
    MERL Contact: John R. Hershey
    Location: Centre Convencions Internacional Barcelona, Barcelona SPAIN
    Research Areas: Multimedia, Machine Learning, Speech & Audio
    Brief
    • MERL researcher John Hershey, is organizing a Workshop on End-to-End Speech and Audio Processing, on behalf of MERL's Speech and Audio team, and in collaboration with Philemon Brakel of the University of Montreal. The workshop focuses on recent advances to end-to-end deep learning methods to address alignment and structured prediction problems that naturally arise in speech and audio processing. The all day workshop takes place on Saturday, December 10th at NIPS 2016, in Barcelona, Spain.
  •  
  •  EVENT   John Hershey to present tutorial at the 2016 IEEE SLT Workshop
    Date: Tuesday, December 13, 2016
    Speaker: John Hershey, MERL
    MERL Contacts: John R. Hershey; Jonathan Le Roux; Shinji Watanabe
    Location: 2016 IEEE Spoken Language Technology Workshop, San Diego, California
    Research Areas: Multimedia, Machine Learning, Speech & Audio
    Brief
    • MERL researcher John Hershey presents an invited tutorial at the 2016 IEEE Workshop on Spoken Language Technology, in San Diego, California. The topic, "developing novel deep neural network architectures from probabilistic models" stems from MERL work with collaborators Jonathan Le Roux and Shinji Watanabe, on a principled framework that seeks to improve our understanding of deep neural networks, and draws inspiration for new types of deep network from the arsenal of principles and tools developed over the years for conventional probabilistic models. The tutorial covers a range of parallel ideas in the literature that have formed a recent trend, as well as their application to speech and language.
  •  
  •  EVENT   2016 IEEE Workshop on Spoken Language Technology: Sponsored by MERL
    Date: Tuesday, December 13, 2016 - Friday, December 16, 2016
    MERL Contact: John R. Hershey
    Location: San Diego, California
    Research Areas: Multimedia, Speech & Audio
    Brief
    • The IEEE Workshop on Spoken Language Technology is a premier international showcase for advances in spoken language technology. The theme for 2016 is "machine learning: from signal to concepts," which reflects the current excitement about end-to-end learning in speech and language processing. This year, MERL is showing its support for SLT as one of its top sponsors, along with Amazon and Microsoft.
  •  
  •  EVENT   MERL Open House
    Date & Time: Thursday, December 8, 2016; 4:00-7:00pm
    MERL Contacts: Elizabeth Phillips; Anthony Vetro
    Location: 201 Broadway, 8th Floor, Cambridge, MA
    Research Areas: Electronics & Communications, Multimedia, Data Analytics, Computer Vision, Mechatronics, Algorithms, Business Innovation
    Brief
    • Snacks, demos, science: On Thursday 12/8, Mitsubishi Electric Research Labs (MERL) will host an open house for graduate+ students interested in internships, post-docs, and research scientist positions. The event will be held from 4-7pm and will feature demos & short presentations in our main areas of research: algorithms, multimedia, electronics, communications, computer vision, speech processing, optimization, machine learning, data analytics, mechatronics, dynamics, control, and robotics. MERL is a high impact publication-oriented research lab with very extensive internship and university collaboration programs. Most internships lead to publication; many of our interns and staff have gone on to notable careers at MERL and in academia. Come mix with our researchers, see our state of the art technologies, and learn about our research opportunities. Dress code: casual, with resumes.

      Pre-registration for the event is strongly encouraged:
      https://www.eventbrite.com/e/merl-open-house-tickets-29408503626

      Current internship and employment openings:
      http://www.merl.com/internship/openings
      http://www.merl.com/employment/employment
  •  
  •  EVENT   MERL participating in Engineering Career Fair
    Date & Time: Wednesday, November 16, 2016; 3:30-6:30pm
    MERL Contacts: Elizabeth Phillips; Anthony Vetro
    Location: Sheraton Commander (16 Garden Street, Cambridge, MA)
    Research Areas: Electronics & Communications, Multimedia, Data Analytics, Computer Vision, Mechatronics, Algorithms, Business Innovation
    Brief
    • MERL will be participating in the Engineering Career Fair Collaborative, which is being held on November 16, 2016 at the Sheraton Commander in Cambridge from 3:30-6:30pm. Graduate students with an interest in learning about internship and other employment opportunities at MERL are invited to visit our booth. Staff members will be on hand to discuss current openings. We will also be showing some demonstrations of current research projects.

      Current internship and employment openings:
      http://www.merl.com/internship/openings
      http://www.merl.com/employment/employment
  •  
  •  NEWS   Rui Ma gave invited IEEE course on Modern Topics in Power Amplifier
    Date: October 11, 2016
    Where: MIT Lincoln Laboratory
    MERL Contact: Rui Ma
    Research Areas: Electronics & Communications, Machine Learning, Power & RF, Wireless Communications & Signal Processing, RF, Signal Processing
    Brief
    • Dr. Rui Ma was invited to give a talk on Modern Topics in Power Amplifier, which was IEEE Chapter course organized by IEEE Boston Section.

      This five week lecture series intended to give a tutorial overview of the latest developments in power amplifier technology. It began with a review of RF power amplifier concepts then teaches the modern MMIC design flow process. Efficiency, and linearization techniques were discussed in the following weeks. The course was concluded with a hands on demonstration and exercise.

      Dr. Ma was addressing the advancement of Digital Transmitter as a enabling technology for next generation wireless communications.
  •