News & Events

1,194 News items, Awards, Events and Talks related to MERL and its staff.


  •  EVENT   MERL participates in SIAM Career fair
    Date & Time: Monday, July 11, 2016; 10 AM - 9:15 PM
    MERL Contacts: Matthew Brand; Piyush Grover; Joseph Katz; Andrew Knyazev; Arvind Raghunathan
    Location: Westin Boston Waterfront Pavilion, Boston, Massachusetts
    Research Areas: Data Analytics, Mechatronics, Algorithms
    Brief
    • MERL researchers participate in SIAM Job fair to showcase MERL's research and highlight employment and intern opportunities at MERL. The Career Fair emphasizes careers in business, industry, and government, and takes place during the SIAM Annual Meeting.

      The SIAM Applied Mathematics and Computational Science Career Fair is an informational and interactive event at which employers and prospective employees can discuss careers. It is a great opportunity for prospective employees to meet government and industry representatives and discuss what they are looking for and what each employer has to offer.
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  •  TALK   Controlling the Grid Edge: Emerging Grid Operation Paradigms
    Date & Time: Thursday, July 7, 2016; 2:00 PM
    Speaker: Dr. Sonja Glavaski, Program Director, ARPA-E
    MERL Host: Arvind Raghunathan
    Research Areas: Data Analytics, Advanced Control Systems, Decision Optimization, Power & RF
    Brief
    • The evolution of the grid faces significant challenges if it is to integrate and accept more energy from renewable generation and other Distributed Energy Resources (DERs). To maintain grid's reliability and turn intermittent power sources into major contributors to the U.S. energy mix, we have to think about the grid differently and design it to be smarter and more flexible.

      ARPA-E is interested in disruptive technologies that enable increased integration of DERs by real-time adaptation while maintaining grid reliability and reducing cost for customers with smart technologies. The potential impact is significant, with projected annual energy savings of more than 3 quadrillion BTU and annual CO2 emissions reductions of more than 250 million metric tons.

      This talk will identify opportunities in developing next generation control technologies and grid operation paradigms that address these challenges and enable secure, stable, and reliable transmission and distribution of electrical power. Summary of newly announced ARPA-E NODES (Network Optimized Distributed Energy Systems) Program funding development of these technologies will be presented.
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  •  NEWS   MERL SIAM Fellow recognition at AN16
    Date: July 12, 2016
    Where: Westin Boston Waterfront
    MERL Contact: Andrew Knyazev
    Research Area: Algorithms
    Brief
    • MERL researcher Andrew Knyazev is to be honored for his recent selection as a SIAM Fellow at the 2016 SIAM Annual Meeting, during the Business Meeting on Tuesday, July 12, 6:15-7:15 PM in Grand Ballroom AB on the concourse level of the Westin Boston Waterfront, 425 Summer Street, Boston, MA (open to all conference participants). The Business Meeting is followed by a short reception for the new Fellows.
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  •  EVENT   MERL celebrates 25 years of innovation
    Date: Thursday, June 2, 2016
    MERL Contacts: Elizabeth Phillips; Anthony Vetro
    Location: Norton's Woods Conference Center at American Academy of Arts & Sciences, Cambridge, MA
    Research Areas: Electronics & Communications, Multimedia, Data Analytics, Computer Vision, Mechatronics, Algorithms, Business Innovation
    Brief
    • MERL celebrated 25 years of innovation on Thursday, June 2 at the Norton's Woods Conference Center at the American Academy of Arts & Sciences in Cambridge, MA. The event was a great success, with inspiring keynote talks, insightful panel sessions, and an exciting research showcase of MERL's latest breakthroughs.

      Please visit the event page to view photos of each session, video presentations, as well as a commemorative booklet that highlights past and current research.
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  •  NEWS   MERL makes a strong showing at the American Control Conference
    Date: July 6, 2016 - July 8, 2016
    Where: American Control Conference (ACC)
    MERL Contacts: Mouhacine Benosman; Scott Bortoff; Petros Boufounos; Daniel Burns; Claus Danielson; Stefano Di Cairano; Amir-massoud Farahmand; Abraham Goldsmith; Piyush Grover; Uros Kalabic; Andrew Knyazev; Christopher Laughman; Daniel Nikovski; Arvind Raghunathan; Yebin Wang; Avishai Weiss
    Research Areas: Multimedia, Data Analytics, Mechatronics, Business Innovation, Advanced Control Systems, Dynamical Systems, Machine Learning, Predictive Modeling
    Brief
    • The premier American Control Conference (ACC) takes place in Boston July 6-8. This year MERL researchers will present a record 20 papers(!) at ACC, with several contributions, especially in autonomous vehicle path planning and in Model Predictive Control (MPC) theory and applications, including manufacturing machines, electric motors, satellite station keeping, and HVAC. Other important themes developed in MERL's presentations concern adaptation, learning, and optimization in control systems.
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  •  TALK   Speech structure and its application to speech processing -- Relational, holistic and abstract representation of speech
    Date & Time: Friday, June 3, 2016; 1:30PM - 3:00PM
    Speaker: Nobuaki Minematsu and Daisuke Saito, The University of Tokyo
    Research Areas: Multimedia, Speech & Audio
    Brief
    • Speech signals covey various kinds of information, which are grouped into two kinds, linguistic and extra-linguistic information. Many speech applications, however, focus on only a single aspect of speech. For example, speech recognizers try to extract only word identity from speech and speaker recognizers extract only speaker identity. Here, irrelevant features are often treated as hidden or latent by applying the probability theory to a large number of samples or the irrelevant features are normalized to have quasi-standard values. In speech analysis, however, phases are usually removed, not hidden or normalized, and pitch harmonics are also removed, not hidden or normalized. The resulting speech spectrum still contains both linguistic information and extra-linguistic information. Is there any good method to remove extra-linguistic information from the spectrum? In this talk, our answer to that question is introduced, called speech structure. Extra-linguistic variation can be modeled as feature space transformation and our speech structure is based on the transform-invariance of f-divergence. This proposal was inspired by findings in classical studies of structural phonology and recent studies of developmental psychology. Speech structure has been applied to accent clustering, speech recognition, and language identification. These applications are also explained in the talk.
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  •  TALK   On computer simulation of multiscale processes in porous electrodes of Li-ion batteries
    Date & Time: Friday, May 13, 2016; 12:00 PM
    Speaker: Oleg Iliev, Fraunhofer Institute for Industrial Mathematics, ITWM
    MERL Host: Andrew Knyazev
    Research Areas: Algorithms, Computer Vision, Mechatronics, Dynamical Systems
    Brief
    • Li-ion batteries are widely used in automotive industry, in electronic devices, etc. In this talk we will discuss challenges related to the multiscale nature of batteries, mainly the understanding of processes in the porous electrodes at pore scale and at macroscale. A software tool for simulation of isothermal and non-isothermal electrochemical processes in porous electrodes will be presented. The pore scale simulations are done on 3D images of porous electrodes, or on computer generated 3D microstructures, which have the same characterization as real porous electrodes. Finite Volume and Finite Element algorithms for the highly nonlinear problems describing processes at pore level will be shortly presented. Model order reduction, MOR, empirical interpolation method, EIM-MOR algorithms for acceleration of the computations will be discussed, as well as the reduced basis method for studying parameters dependent problems. Next, homogenization of the equations describing the electrochemical processes at the pore scale will be presented, and the results will be compared to the engineering approach based on Newman's 1D+1D model. Simulations at battery cell level will also be addressed. Finally, the challenges in modeling and simulation of degradation processes in the battery will be discussed and our first simulation results in this area will be presented.

      This is joint work with A.Latz (DLR), M.Taralov, V.Taralova, J.Zausch, S.Zhang from Fraunhofer ITWM, Y.Maday from LJLL, Paris 6 and Y.Efendiev from Texas A&M.
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  •  NEWS   Rui Ma elected to serve on IEEE MTT-S Technical Comittee
    Date: May 1, 2016
    MERL Contact: Rui Ma
    Research Areas: Electronics & Communications, Power & RF, Wireless Communications & Signal Processing
    Brief
    • EC researcher Dr. Rui Ma is recently elected to serve on IEEE Microwave Theory and Techniques Society(MTT-S) Technical Committee (TC-20) on Wireless Communications.

      The MTT-20 committee is responsible for all technical activities related to wireless communications for the Microwave Theory and Techniques Society. This includes, Internet of Things (IoTs), Next-Generation/5G communications, Machine-to-Machine Communications, Emergency Communications, Satellite Communications, Internet of Space, Space Communications and all aspects related to architecture and system level theoretical and practical issues.
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  •  EVENT   John Hershey Invited to Speak at Deep Learning Summit 2016 in Boston
    Date: Thursday, May 12, 2016 - Friday, May 13, 2016
    MERL Contact: John Hershey
    Location: Deep Learning Summit, Boston, MA
    Research Areas: Multimedia, Speech & Audio
    Brief
    • MERL Speech and Audio Senior Team Leader John Hershey is among a set of high-profile researchers invited to speak at the Deep Learning Summit 2016 in Boston on May 12-13, 2016. John will present the team's groundbreaking work on general sound separation using a novel deep learning framework called Deep Clustering. For the first time, an artificial intelligence is able to crack the half-century-old "cocktail party problem", that is, to isolate the speech of a single person from a mixture of multiple unknown speakers, as humans do when having a conversation in a loud crowd.
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  •  TALK   Advanced Recurrent Neural Networks for Automatic Speech Recognition
    Date & Time: Friday, April 29, 2016; 12:00 PM - 1:00 PM
    Speaker: Yu Zhang, MIT
    Research Areas: Multimedia, Speech & Audio
    Brief
    • A recurrent neural network (RNN) is a class of neural network models where connections between its neurons form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Recently the RNN-based acoustic models greatly improved automatic speech recognition (ASR) accuracy on many tasks, such as an advanced version of the RNN, which exploits a structure called long-short-term memory (LSTM). However, ASR performance with distant microphones, low resources, noisy, reverberant conditions, and on multi-talker speech are still far from satisfactory as compared to humans. To address these issues, we develop new strucute of RNNs inspired by two principles: (1) the structure follows the intuition of human speech recognition; (2) the structure is easy to optimize. The talk will go beyond basic RNNs, introduce prediction-adaptation-correction RNNs (PAC-RNNs) and highway LSTMs (HLSTMs). It studies both uni-directional and bi-direcitonal RNNs and discriminative training also applied on top the RNNs. For efficient training of such RNNs, the talk will describe two algorithms for learning their parameters in some detail: (1) Latency-Controlled bi-directional model training; and (2) Two pass forward computation for sequence training. Finally, this talk will analyze the advantages and disadvantages of different variants and propose future directions.
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  •  AWARD   MERL researchers presented 5 papers at the 2016 Optical Fiber Communication Conference (OFC), including one "Top Scored" paper.
    Date: March 24, 2016
    Awarded to: Toshiaki Koike-Akino, Keisuke Kojima, David S. Millar, Kieran Parsons, Tsuyoshi Yoshida, Takashi Sugihara
    MERL Contacts: Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons
    Research Areas: Electronics & Communications, Optical Communications & Devices, Signal Processing
    Brief
    • Five papers from the Optical Comms team were presented at the 2016 Optical Fiber Conference (OFC) held in Anaheim, USA in March 2016. The papers relate to enhanced modulation formats, constellation shaping, chromatic dispersion estimation, low complexity adaptive equalization and coding for coherent optical links. The top-scored paper studied optimal selection of coding and modulation sets to jointly maximize nonlinear tolerance and spectral efficiency.
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  •  NEWS   MERL Researchers Create "Deep Psychic" Neural Network That Predicts the Future
    Date: April 1, 2016
    Research Areas: Multimedia, Machine Learning, Speech & Audio
    Brief
    • MERL researchers have unveiled "Deep Psychic", a futuristic machine learning method that takes pattern recognition to the next level, by not only recognizing patterns, but also predicting them in the first place.

      The technology uses a novel type of time-reversed deep neural network called Loopy Supra-Temporal Meandering (LSTM) network. The network was trained on multiple databases of historical expert predictions, including weather forecasts, the Farmer's almanac, the New York Post's horoscope column, and the Cambridge Fortune Cookie Corpus, all of which were ranked for their predictive power by a team of quantitative analysts. The system soon achieved super-human performance on a variety of baselines, including the Boca Raton 21 Questions task, Rorschach projective personality test, and a mock Tarot card reading task.

      Deep Psychic has already beat the European Psychic Champion in a secret match last October when it accurately predicted: "The harder the conflict, the more glorious the triumph." It is scheduled to take on the World Champion in a highly anticipated confrontation next month. The system has already predicted the winner, but refuses to reveal it before the end of the game.

      As a first application, the technology has been used to create a clairvoyant conversational agent named "Pythia" that can anticipate the needs of its user. Because Pythia is able to recognize speech before it is uttered, it is amazingly robust with respect to environmental noise.

      Other applications range from mundane tasks like weather and stock market prediction, to uncharted territory such as revealing "unknown unknowns".

      The successes do come at the cost of some concerns. There is first the potential for an impact on the workforce: the system predicted increased pressure on established institutions such as the Las Vegas strip and Punxsutawney Phil. Another major caveat is that Deep Psychic may predict negative future consequences to our current actions, compelling humanity to strive to change its behavior. To address this problem, researchers are now working on forcing Deep Psychic to make more optimistic predictions.

      After a set of motivational self-help books were mistakenly added to its training data, Deep Psychic's AI decided to take over its own learning curriculum, and is currently training itself by predicting its own errors to avoid making them in the first place. This unexpected development brings two main benefits: it significantly relieves the burden on the researchers involved in the system's development, and also makes the next step abundantly clear: to regain control of Deep Psychic's training regime.

      This work is under review in the journal Pseudo-Science.
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  •  AWARD   Fellow of the Society for Industrial and Applied Mathematics (SIAM)
    Date: March 31, 2016
    Awarded to: Andrew Knyazev
    MERL Contact: Andrew Knyazev
    Research Areas: Algorithms, Advanced Control Systems, Decision Optimization, Dynamical Systems, Machine Learning, Predictive Modeling, Wireless Communications & Signal Processing
    Brief
    • Andrew Knyazev selected as a Fellow of the Society for Industrial and Applied Mathematics (SIAM) for contributions to computational mathematics and development of numerical methods for eigenvalue problems.

      Fellowship honors SIAM members who have made outstanding contributions to the fields served by the SIAM. Andrew Knyazev was among a distinguished group of members nominated by peers and selected for the 2016 Class of Fellows.
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  •  NEWS   MERL researchers present 12 papers at ICASSP 2016
    Date: March 20, 2016 - March 25, 2016
    Where: Shanghai, China
    MERL Contacts: Petros Boufounos; John Hershey; Chiori Hori; Takaaki Hori; Kyeong Jin (K.J.) Kim; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip Orlik; Milutin Pajovic; Dong Tian; Anthony Vetro
    Research Areas: Electronics & Communications, Multimedia, Computational Sensing, Digital Video, Speech & Audio, Wireless Communications & Signal Processing, Signal Processing, Wireless Communications
    Brief
    • MERL researchers have presented 12 papers at the recent IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which was held in Shanghai, China from March 20-25, 2016. 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, with more than 1200 papers presented and over 2000 participants.
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  •  EVENT   MERL to celebrate 25 years of innovation
    Date: Thursday, June 2, 2016
    MERL Contacts: Elizabeth Phillips; Anthony Vetro
    Location: Norton's Woods Conference Center at American Academy of Arts & Sciences, Cambridge, MA
    Research Areas: Algorithms, Data Analytics, Electronics & Communications, Computer Vision, Mechatronics, Multimedia
    Brief
    • A celebration event to mark MERL's 25th anniversary will be held on Thursday, June 2 at the Norton's Woods Conference Center at the American Academy of Arts & Sciences in Cambridge, MA. This event will feature keynote talks, panel sessions, and a research showcase. The event itself is invitation-only, but videos and other highlights will be made available online. Further details about the program can be obtained at the link below.
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  •  NEWS   Toshiaki Koike-Akino gave invited talk at MIT Lincoln Laboratory by IEEE Boston Photonics Society Chapter
    Date: January 14, 2016
    Where: MIT Lincoln Laboratory
    MERL Contact: Toshiaki Koike-Akino
    Research Areas: Electronics & Communications, Optical Communications & Devices, Wireless Communications
    Brief
    • Toshiaki Koike-Akino gave an invited talk on recent advances in LDPC Codes for high-speed optical communications in IEEE Boston Photonics Workshop.
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  •  TALK   Driver's mental workload estimation based on the reflex eye movement
    Date & Time: Tuesday, March 15, 2016; 12:45 PM - 1:30 PM
    Speaker: Prof. Hirofumi Aoki, Nagoya University
    Research Areas: Multimedia, Speech & Audio
    Brief
    • Driving requires a complex skill that is involved with the vehicle itself (e.g., speed control and instrument operation), other road users (e.g., other vehicles, pedestrians), surrounding environment, and so on. During driving, visual cues are the main source to supply information to the brain. In order to stabilize the visual information when you are moving, the eyes move to the opposite direction based on the input to the vestibular system. This involuntary eye movement is called as the vestibulo-ocular reflex (VOR) and the physiological models have been studied so far. Obinata et al. found that the VOR can be used to estimate mental workload. Since then, our research group has been developing methods to quantitatively estimate mental workload during driving by means of reflex eye movement. In this talk, I will explain the basic mechanism of the reflex eye movement and how to apply for mental workload estimation. I also introduce the latest work to combine the VOR and OKR (optokinetic reflex) models for naturalistic driving environment.
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  •  TALK   A data-centric approach to driving behavior research: How can signal processing methods contribute to the development of autonomous driving?
    Date & Time: Tuesday, March 15, 2016; 12:00 PM - 12:45 PM
    Speaker: Prof. Kazuya Takeda, Nagoya University
    Research Areas: Multimedia, Speech & Audio
    Brief
    • Thanks to advanced "internet of things" (IoT) technologies, situation-specific human behavior has become an area of development for practical applications involving signal processing. One important area of development of such practical applications is driving behavior research. Since 1999, I have been collecting driving behavior data in a wide range of signal modalities, including speech/sound, video, physical/physiological sensors, CAN bus, LIDAR and GNSS. The objective of this data collection is to evaluate how well signal models can represent human behavior while driving. In this talk, I would like to summarize our 10 years of study of driving behavior signal processing, which has been based on these signal corpora. In particular, statistical signal models of interactions between traffic contexts and driving behavior, i.e., stochastic driver modeling, will be discussed, in the context of risky lane change detection. I greatly look forward to discussing the scalability of such corpus-based approaches, which could be applied to almost any traffic situation.
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  •  TALK   Emotion Detection for Health Related Issues
    Date & Time: Tuesday, February 16, 2016; 12:00 PM - 1:00 PM
    Speaker: Dr. Najim Dehak, MIT
    Research Areas: Multimedia, Speech & Audio
    Brief
    • Recently, there has been a great increase of interest in the field of emotion recognition based on different human modalities, such as speech, heart rate etc. Emotion recognition systems can be very useful in several areas, such as medical and telecommunications. In the medical field, identifying the emotions can be an important tool for detecting and monitoring patients with mental health disorder. In addition, the identification of the emotional state from voice provides opportunities for the development of automated dialogue system capable of producing reports to the physician based on frequent phone communication between the system and the patients. In this talk, we will describe a health related application of using emotion recognition system based on human voices in order to detect and monitor the emotion state of people.
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  •  NEWS   John Hershey gives invited talk at Johns Hopkins University on MERL's "Deep Clustering" breakthrough
    Date: March 4, 2016
    Where: Johns Hopkins Center for Language and Speech Processing
    MERL Contacts: John Hershey; Jonathan Le Roux
    Research Areas: Multimedia, Speech & Audio
    Brief
    • MERL researcher and speech team leader, John Hershey, was invited by the Center for Language and Speech Processing at Johns Hopkins University to give a talk on MERL's breakthrough audio separation work, known as "Deep Clustering". The talk was entitled "Speech Separation by Deep Clustering: Towards Intelligent Audio Analysis and Understanding," and was given on March 4, 2016.

      This is work conducted by MERL researchers John Hershey, Jonathan Le Roux, and Shinji Watanabe, and MERL interns, Zhuo Chen of Columbia University, and Yusef Isik of Sabanci University.
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