- Date & Time: Monday, October 8, 2018 - Thursday, October 11, 2018; 8am-5pm
Location: MIT Samberg Conference Center, Cambridge, MA
MERL Contact: Christopher R. Laughman
Research Areas: Control, Multi-Physical Modeling
Brief - The 2018 American Modelica Conference, the first North American conference focused on the Modelica multiphysics modeling language, will be held on Tuesday and Wednesday, October 9-10, 2018 at the Samberg Conference Center at MIT in Cambridge, MA. Chris Laughman, a team leader in the Multiphysical Systems and Devices group, is the local chair for the conference.
This conference will feature over 40 papers and user presentations on the Modelica language and its application to a wide variety of problem domains, including thermofluid, aerospace, automotive, and energy systems. There will also be 2 keynote addresses by John McKibben (Proctor & Gamble) and Hilding Elmqvist (Mogram AB). Nearly 100 attendees from 11 different countries have already registered for the conference, and it promises to be a very educational experience.
MERL is also hosting two free workshops on October 8 to provide opportunities to engineers looking to increase their familiarity with the language and its applications. An introductory workshop will be led by engineers from Modelon during that morning, and then a second workshop on the application of Modelica to building systems will be led by Michael Wetter from Lawrence Berkeley National Labs in the afternoon. MERL will also host a Modelica user meeting on October 11 that will provide more details and discussion about trends in the use and development of Modelica in the larger engineering community.
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- Date: September 19, 2018
Where: MIT Lincoln Laboratory
MERL Contact: Toshiaki Koike-Akino
Research Area: Communications
Brief - Toshiaki Koike-Akino gave an invited talk on new trends of forward error correction codes based on polar coding at seminar series of IEEE Boston Photonics Society at MIT Lincoln Laboratory. The talk covered recent advancement of polar code design for ultra-high-throughput decoding, suited for future Tera-bit optical interconnects.
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- Date: Thursday, October 18, 2018
Location: Google, Cambridge, MA
MERL Contact: Jonathan Le Roux
Research Area: Speech & Audio
Brief - SANE 2018, a one-day event gathering researchers and students in speech and audio from the Northeast of the American continent, will be held on Thursday October 18, 2018 at Google, in Cambridge, MA. MERL is one of the organizers and sponsors of the workshop.
It is the 7th edition in the SANE series of workshops, which started at MERL in 2012. Since the first edition, the audience has steadily grown, with a record 180 participants in 2017.
SANE 2018 will feature invited talks by leading researchers from the Northeast, as well as from the international community. It will also feature a lively poster session, open to both students and researchers.
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- Date: June 25, 2018 - August 3, 2018
Where: Johns Hopkins University, Baltimore, MD
MERL Contact: Jonathan Le Roux
Research Area: Speech & Audio
Brief - MERL Speech & Audio Team researcher Takaaki Hori led a team of 27 senior researchers and Ph.D. students from different organizations around the world, working on "Multi-lingual End-to-End Speech Recognition for Incomplete Data" as part of the Jelinek Memorial Summer Workshop on Speech and Language Technology (JSALT). The JSALT workshop is a renowned 6-week hands-on workshop held yearly since 1995. This year, the workshop was held at Johns Hopkins University in Baltimore from June 25 to August 3, 2018. Takaaki's team developed new methods for end-to-end Automatic Speech Recognition (ASR) with a focus on low-resource languages with limited labelled data.
End-to-end ASR can significantly reduce the burden of developing ASR systems for new languages, by eliminating the need for linguistic information such as pronunciation dictionaries. Some end-to-end systems have recently achieved performance comparable to or better than conventional systems in several tasks. However, the current model training algorithms basically require paired data, i.e., speech data and the corresponding transcription. Sufficient amount of such complete data is usually unavailable for minor languages, and creating such data sets is very expensive and time consuming.
The goal of Takaaki's team project was to expand the applicability of end-to-end models to multilingual ASR, and to develop new technology that would make it possible to build highly accurate systems even for low-resource languages without a large amount of paired data. Some major accomplishments of the team include building multi-lingual end-to-end ASR systems for 17 languages, developing novel architectures and training methods for end-to-end ASR, building end-to-end ASR-TTS (Text-to-speech) chain for unpaired data training, and developing ESPnet, an open-source end-to-end speech processing toolkit. Three papers stemming from the team's work have already been accepted to the 2018 IEEE Spoken Language Technology Workshop (SLT), with several more to be submitted to upcoming conferences.
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- Date: Thursday, July 19, 2018
Location: MERL
MERL Contacts: Elizabeth Phillips; Jinyun Zhang Brief - We hosted the 4th Annual "Women in Science at MERL," event on July 19th. This year we celebrated the contributions of the eleven female interns, three female researchers, and some female members of HQ staff. MERL executives, managers and researchers participated in the event. MERL's interns and researchers were asked probing questions about how they are fulfilled in their work and how they facilitate innovation. This resulted in every participant feeling as though they were moving their field of science forward. Everyone left feeling inspired.
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- Date: August 21, 2018 - July 24, 2018
Where: CCTA2018 Copenhagen
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - MERL researchers Karl Berntorp and Stefano Di Cairano organized an industry session on Autonomous Vehicles at the 2018 Conference on Control Technologies and Applications, Aug. 21-24. (http://ccta2018.ieeecss.org/) They will present the main tutorial paper in the session. Such industry sessions are organized by researchers that are well established in terms of both academic relevance and real-world impact of their research.
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- Date: July 2, 2018 - July 5, 2018
Where: Advanced Photonics Congress 2018
MERL Contacts: Toshiaki Koike-Akino; Kieran Parsons; Ye Wang
Research Areas: Communications, Signal Processing
Brief - Three papers from the Optical Communication team were presented at Advanced Photonics Congress, held at ETH Switzerland from 2-5 July 2018. One of the papers was an invited talk of MERL's recent advancement in high-speed reliable coded modulation schemes based on polar coding. The other papers are related to fiber nonlinearity mitigation techniques based on pulse-shaping filter optimization and deep neural networks.
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- Date: June 13, 2018
Where: Philadelphia, PA
MERL Contact: Philip V. Orlik
Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
Brief - Invited by IEEE MTT-S (Microwave Theory and Techniques Society), Researcher Dr. Rui Ma attended and presented MERL's cutting edge technology demonstration on real-time of multi-band All-Digital Transmitter at 5G Interactive Theater, which was held during IMS2018 in Philadelphia, PA on June 13th 2018. All-digital transmitter (ADT) is envisioned as a key enabling technology for next generation software defined radio.
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- Date: June 27, 2018
Where: American Control Conference, 2018
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - MERL's Stefano Di Cairano, in collaboration with University of Michigan's Prof. Ilya Kolmanovsky have organized a tutorial session at the 2018 American Control Conference on "Real-Time Optimization and Model Predictive Control for Aerospace and Automotive Applications", and will present the main tutorial paper.
Tutorial sessions are organized by researchers that are well established in terms of both academic relevance and real world impact of their research.
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- Date: June 26, 2018 - June 29, 2018
Where: ACC2018 Milwakee
MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Yebin Wang; Avishai Weiss
Research Area: Control
Brief - At the American Control Conference June 26-29, http://acc2018.a2c2.org/, MERL members will give 10 papers on subjects including model predictive control, embedded optimization, urban path planning, motor control, estimation, and calibration.
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- Date: June 4, 2018
Where: Pittsburgh, Pennsylvania
MERL Contact: Arvind Raghunathan
Research Area: Optimization
Brief - Thiago Serra, currently a Visiting Research Scientist in the Data Analytics group, has been awarded the Gerald L. Thompson Doctoral Dissertation Award in Management Science from the Tepper School of Business, Carnegie Mellon University. This is awarded each year to honor an outstanding doctoral dissertation involving theoretical, computational and applied contributions in the area of Management Science. One of the thesis chapters, "The Integrated Last-Mile Transportation Problem" was work performed at MERL in conjunction with Arvind Raghunathan during a summer internship. This work resulted in a patent application and will be presented at the 2018 International Conference on Automated Planning and Scheduling (ICAPS).
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- Date: April 17, 2018
Awarded to: Zhong-Qiu Wang
MERL Contact: Jonathan Le Roux
Research Area: Speech & Audio
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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- Date: April 15, 2018 - April 20, 2018
Where: Calgary, AB
MERL Contacts: Petros T. Boufounos; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip V. Orlik; Pu (Perry) Wang
Research Areas: Computational Sensing, Digital Video, Speech & Audio
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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- Date: March 20, 2018
Where: Asian Conference on Supercomputing Frontiers -
- Date: April 19, 2018
Where: Room 202 Stratton Hall Worcester Polytechnic Institute 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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- Date: March 19, 2018
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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- Date: April 10, 2018
Research Area: Machine Learning
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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- Date: November 30, 2017
Awarded to: Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn Keogh
MERL Contact: Daniel N. Nikovski
Research Area: 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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- Date: March 11, 2018 - March 15, 2018
Where: Optical Fiber Communication Conference and Exhibition (OFC)
MERL Contacts: Toshiaki Koike-Akino; 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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- Date & Time: Tuesday, March 6, 2018; 12:00 PM
Speaker: Scott Wisdom, Affectiva
MERL Host: Jonathan Le Roux
Research Area: Speech & Audio
Abstract 
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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- Date: January 31, 2018
Where: SPIE Photonics West
MERL Contact: Bingnan Wang
Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
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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- Date: February 14, 2018
Where: Tokyo, Japan
MERL Contacts: Devesh K. Jha; Daniel N. Nikovski; Diego Romeres; William S. Yerazunis
Research Areas: Optimization, Computer Vision
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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- Date: February 14, 2018
Where: Tokyo, Japan
MERL Contact: Philip V. Orlik
Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
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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- Date: February 5, 2018
Where: National Public Radio (NPR)
MERL Contact: Jonathan Le Roux
Research Area: Speech & Audio
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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- 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
Abstract 
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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