- 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 Contacts: Mouhacine Benosman; Philip V. Orlik; Koon Hoo Teo
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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- Date: February 1, 2018
MERL Contact: Scott A. 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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- 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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- 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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- 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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- Date: December 16, 2017 - December 20, 2017
Where: Okinawa, Japan
MERL Contacts: Chiori Hori; Jonathan Le Roux
Research Area: Speech & Audio
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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- Date: November 27, 2017
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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- Date: February 15, 2018
Brief - University faculty members are invited to spend part or all of their sabbaticals at MERL, pursuing projects of their own choosing in collaboration with MERL researchers.
To apply, a candidate should identify and contact one or more MERL researchers with whom they would like to collaborate. The applicant and a MERL researcher will jointly prepare a proposal that the researcher will champion internally. Please visit the visiting faculty web page for further details: http://www.merl.com/employment/visiting-faculty.php.
The application deadline for positions starting in Summer/Fall 2018 is February 15, 2018.
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- Date: Sunday, December 10, 2017
Location: Hyatt Regency, Long Beach, CA
MERL Contact: Chiori Hori
Research Area: Speech & Audio
Brief - MERL researcher Chiori Hori led the organization of the 6th edition of the Dialog System Technology Challenges (DSTC6). This year's edition of DSTC is split into three tracks: End-to-End Goal Oriented Dialog Learning, End-to-End Conversation Modeling, and Dialogue Breakdown Detection. A total of 23 teams from all over the world competed in the various tracks, and will meet at the Hyatt Regency in Long Beach, CA, USA on December 10 to present their results at a dedicated workshop colocated with NIPS 2017.
MERL's Speech and Audio Team and Mitsubishi Electric Corporation jointly submitted a set of systems to the End-to-End Conversation Modeling Track, obtaining the best rank among 19 submissions in terms of objective metrics.
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- Date: November 27, 2017
MERL Contact: Mouhacine Benosman Brief - MERL researcher Mouhacine Benosman has been appointed as a member of the Editorial Board of the Journal of Optimization Theory and Applications (JOTA).
The Journal of Optimization Theory and Applications publishes carefully selected papers covering mathematical optimization techniques and their applications to science and engineering. An applications paper should be as much about the application of an optimization technique as it is about the solution of a particular problem.
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- Date: October 28, 2017
Where: Venice, Italy
MERL Contact: Tim K. Marks
Research Area: Machine Learning
Brief - MERL Senior Principal Research Scientist Tim K. Marks will give an invited keynote talk at the 2017 IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2017). The workshop will take place On October 28, 2017, at the International Conference on Computer Vision (ICCV 2017) in Venice, Italy.
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- Date & Time: Monday, October 23, 2017; 8:00am-4:00pm
Location: MIT Samberg Conference Center Floor 7, 50 Memorial Drive, Cambridge, MA 02142
MERL Contact: Petros T. Boufounos
Research Areas: Computational Sensing, Communications, Signal Processing
Brief - Dr. Petros Boufounos is co-organizing the symposium on "The Future of Signal Processing," held in honor of the 80th birthday of Prof. Alan V. Oppenheim.
Details at: https://futureofsp.eecs.mit.edu
Organizing committee:
Dr. Tom Baran, Lumii
Dr. Petros Boufounos, MERL
Prof. Anantha Chandrakasan, MIT
Prof. Yonina Eldar, Technion
Program:
8:00-8:45 Coffee
8:45-9:00 Opening remarks
Prof. Martin Schmidt, Provost, MIT
9:00-9:35 The ever-expanding physical boundaries of Signal Processing
Prof. Martin Vetterli, President of EPFL, Lausanne
9:35-10:10 Signal Processors and the U.S. Navy: Enduring Partners
Admiral John Richardson, Chief of Naval Operations, US Navy
10:10-10:30 Short break
10:30-11:05 Signals and Signal Processing: The Invisibles and The Everlastings
Prof. Min Wu, Professor of Electrical and Computer Engineering, University of Maryland
11:05-11:40 Signal processing with quantum computers
Prof. Isaac Chuang, Professor of Physics and Electrical Engineering; Senior Associate Dean of Digital Learning, MIT
11:40-12:30 A box lunch will be provided. In your lunchbox, you'll find an envelope with four cards in it. Bring these cards back to your seats promptly after lunch for a magical surprise!
12:30-12:40 Your Role in the Future of Signal Processing
Magician Joel Acevedo
12:40-1:05 Future of Low-power Embedded Signal Processing
Prof. Anantha Chandrakasan, Dean, School of Engineering, MIT
1:05-1:30 Synthetic biology and signal processing in living cells
Prof. Ron Weiss, MIT, Professor of Biological Engineering and Director of the Synthetic Biology Center
1:30-1:55 Physics 101 for Data Scientists
Prof. Richard Baraniuk, Professor of Electrical and Computer Engineering at Rice University, Founder and Director of OpenStax College
1:55-2:15 Short break
2:15-2:40 Signals: Representation and Information
Prof. Meir Feder, Professor of Electrical Engineering, Tel Aviv University
2:40-3:05 Exposing and Removing Information: Some new Mathematics for Signal Processing
Dr. Petros Boufounos, Senior Principal Research Scientist, Sensing Team Leader, Mitsubishi Electric Research Labs
3:05-4:00 Panel discussion: The Venn diagram between "Data Science," "Machine Learning" and "Signal Processing"
Moderator:
Prof. Alan Oppenheim, Ford Professor of Engineering, MIT
Panelists:
Prof. Asu Ozdaglar, Associate Department Head, Electrical Engineering and Computer Science, MIT
Prof. Ron Schafer, Georgia Tech (Emeritus) and Stanford Univ.
Prof. Yonina Eldar, Professor of Electrical Engineering, Technion
Prof. Victor Zue, Professor of Electrical and Computer Engineering, MIT
Prof. Alexander Rakhlin, Associate Professor of Statistics, University of Pennsylvania
4:00 Closing remarks.
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- Date: October 18, 2017
Where: International Federation of Automatic Control
MERL Contact: Stefano Di Cairano
Research Area: Control
Brief - MERL Mechatronics Senior Principal Research Scientist and Senior Optimization-based Control Team Leader, Stefano Di Cairano, was recently appointed the Vice-Chair of IFAC (International Federation of Automatic Control) Technical Committee for Optimal Control. His term will continue through July 2020.
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- Date & Time: Thursday, November 30, 2017; 4-6pm
Location: 201 Broadway, 8th floor, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro Brief - Snacks, demos, science: On Thursday 11/30, 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 4-6pm 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://merlopenhouse2.eventbrite.com/
Current internship and employment openings:
http://www.merl.com/internship/openings
http://www.merl.com/employment/employment.
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- Date: September 17, 2017 - September 20, 2017
Where: Beijing, China
MERL Contacts: Petros T. Boufounos; Dehong Liu; Hassan Mansour; Huifang Sun; Anthony Vetro
Research Areas: Computer Vision, Computational Sensing, Digital Video
Brief - MERL presented 5 papers at the IEEE International Conference on Image Processing (ICIP), which was held in Beijing, China from September 17-20, 2017. ICIP is a flagship conference of the IEEE Signal Processing Society and approximately 1300 people attended the event. Anthony Vetro served as General Co-chair for the conference.
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- Date: October 4, 2017 - October 6, 2017
Where: Orange County Convention Center, Orlando, FL
MERL Contacts: Elizabeth Phillips; Jinyun Zhang Brief - Every year, women technologists and the best minds in computing convene to highlight the contributions of women to computing. The Anita Borg Institute co-presents GHC with the Association of Computing Machinery (ACM).
The conference results in collaborative proposals, networking and mentoring for our attendees. Conference presenters are leaders in their respective fields, representing industry, academia and government.
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- Date: September 17, 2017 - September 21, 2017
Where: 2017 European Conference on Optical Communication (ECOC), Sweden
MERL Contacts: Toshiaki Koike-Akino; Kieran Parsons; Ye Wang
Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
Brief - Two papers from the Optical Communications team were presented at the 2017 European Conference on Optical Communication (ECOC) held in Gothenburg, Sweden in September 2017. The papers relate to enhanced error correction coding for coherent optical links and advanced precoding for optical data center networks. The invited paper studied irregular polar coding to reduce computational complexity, decoding latency, and bit error rate at the same time. In addition to two papers, the team member was invited to talk about constellation shaping as a workshop panelist.
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- Date: August 4, 2017
Awarded to: David Zhuzhunashvili and Andrew Knyazev
Research Area: Machine Learning
Brief - David Zhuzhunashvili, an undergraduate student at UC Boulder, Colorado, and Andrew Knyazev, Distinguished Research Scientist at MERL, received the 2017 Graph Challenge Student Innovation Award. Their poster "Preconditioned Spectral Clustering for Stochastic Block Partition Streaming Graph Challenge" was accepted to the 2017 IEEE High Performance Extreme Computing Conference (HPEC '17), taking place 12-14 September 2017 (http://www.ieee-hpec.org/), and the paper was accepted to the IEEE Xplore HPEC proceedings.
HPEC is the premier conference in the world on the convergence of High Performance and Embedded Computing. DARPA/Amazon/IEEE Graph Challenge is a special HPEC event. Graph Challenge encourages community approaches to developing new solutions for analyzing graphs derived from social media, sensor feeds, and scientific data to enable relationships between events to be discovered as they unfold in the field. The 2017 Streaming Graph Challenge is Stochastic Block Partition. This challenge seeks to identify optimal blocks (or clusters) in a larger graph with known ground-truth clusters, while performance is evaluated compared to baseline Python and C codes, provided by the Graph Challenge organizers.
The proposed approach is spectral clustering that performs block partition of graphs using eigenvectors of a matrix representing the graph. Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) method iteratively approximates a few leading eigenvectors of the symmetric graph Laplacian for multi-way graph partitioning. Preliminary tests for all static cases for the Graph Challenge demonstrate 100% correctness of partition using any of the IEEE HPEC Graph Challenge metrics, while at the same time also being approximately 500-1000 times faster compared to the provided baseline code, e.g., 2M static graph is 100% correctly partitioned in ~2,100 sec. Warm-starts of LOBPCG further cut the execution time 2-3x for the streaming graphs.
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