- 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: 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 & 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 & 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: Thursday, June 1, 2017
Location: IEEE Conference on Automatic Face and Gesture Recognition (FG 2017), Washington, DC
Speaker: Tim K. Marks
MERL Contact: Tim K. Marks
Research Area: Machine Learning
Brief - MERL Senior Principal Research Scientist Tim K. Marks will give the invited lunch talk on Thursday, June 1, at the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017). The talk is entitled "Robust Real-Time 3D Head Pose and 2D Face Alignment.".
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- Date & Time: Monday, July 10, 2017; 6:15 PM - 7:15 PM
Location: David Lawrence Convention Center, Pittsburgh PA
Speaker: Andrew Knyazev and other panelists, MERL 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.
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- Date & Time: Tuesday, March 28, 2017; 1:30 - 5:30PM
Location: Google (355 Main St., 5th Floor, Cambridge MA)
MERL Contacts: Daniel N. Nikovski; Anthony Vetro; Jinyun Zhang 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.
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- Date & Time: Tuesday, January 17, 2017; 6:00 pm
Location: 201 Broadway, Cambridge, MA
Speaker: Tim Marks, Esra Cansizoglu and Carl Vondrick, MERL and MIT
Research Area: Computer Vision
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.
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- Date & Time: Wednesday, February 1, 2017; 12:00-13:00
Speaker: Dr. Heiga ZEN, Google
MERL Host: Chiori Hori
Research Area: Speech & Audio
Abstract 
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.
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- 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: Computational Sensing, Machine Learning
Abstract 
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.
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- Date & Time: Monday, December 12, 2016; 12:00 PM
Speaker: Yanlai Chen, Department of Mathematics at the University of Massachusetts Dartmouth
Research Areas: Control, Dynamical Systems
Abstract - 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.
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- Date & Time: Friday, December 2, 2016; 11:00 AM
Speaker: Prof. Waheed Bajwa, Rutgers University
MERL Host: Petros T. Boufounos
Research Area: Computational Sensing
Abstract 
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.
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- Date: Saturday, December 10, 2016
Location: Centre Convencions Internacional Barcelona, Barcelona SPAIN
Research Areas: 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.
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- Date: Tuesday, December 13, 2016 - Friday, December 16, 2016
Location: San Diego, California
Research Area: 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.
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- Date: Tuesday, December 13, 2016
Location: 2016 IEEE Spoken Language Technology Workshop, San Diego, California
Speaker: John Hershey, MERL
MERL Contact: Jonathan Le Roux
Research Areas: 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.
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- Date & Time: Thursday, December 8, 2016; 4:00-7:00pm
Location: 201 Broadway, 8th Floor, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro 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.
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- Date & Time: Wednesday, November 16, 2016; 3:30-6:30pm
Location: Sheraton Commander (16 Garden Street, Cambridge, MA)
MERL Contacts: Elizabeth Phillips; Anthony Vetro 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.
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- Date: Friday, October 21, 2016
Location: MIT, McGovern Institute for Brain Research, Cambridge, MA
MERL Contact: Jonathan Le Roux
Research Area: Speech & Audio
Brief - SANE 2016, a one-day event gathering researchers and students in speech and audio from the Northeast of the American continent, will be held on Friday October 21, 2016 at MIT's Brain and Cognitive Sciences Department, at the McGovern Institute for Brain Research, in Cambridge, MA.
It is a follow-up to SANE 2012 (Mitsubishi Electric Research Labs - MERL), SANE 2013 (Columbia University), SANE 2014 (MIT CSAIL), and SANE 2015 (Google NY). Since the first edition, the audience has steadily grown, gathering 140 researchers and students in 2015.
SANE 2016 will feature invited talks by leading researchers: Juan P. Bello (NYU), William T. Freeman (MIT/Google), Nima Mesgarani (Columbia University), DAn Ellis (Google), Shinji Watanabe (MERL), Josh McDermott (MIT), and Jesse Engel (Google). It will also feature a lively poster session during lunch time, open to both students and researchers.
SANE 2016 is organized by Jonathan Le Roux (MERL), Josh McDermott (MIT), Jim Glass (MIT), and John R. Hershey (MERL).
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- Date & Time: Friday, September 23, 2016; 12:00 PM- 1:00 PM
Speaker: Dr. Earl McCune, Eridan Communications
Research Areas: Communications, Signal Processing
Abstract 
To maximize the operating energy efficiency of any wireless communication link requires a global optimization not only across the entire block diagram, but also including the selected signal modulation and aspects of the link operating protocol. Achieving this global optimization is first examined for the transmitter, receiver, and baseband circuitry. Then the important aspects of signal modulation necessary to access these circuit optimizations, with examples, are presented, followed by the correspondingly important protocol aspects needed. A metric called modulation-available energy efficiency (MAEE) compares proposed signals for compatibility with high energy efficiency objectives.
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- Date & Time: Wednesday, August 17, 2016; 1 PM
Speaker: Gilles Zerah, Centre Francais en Calcul Atomique et Moleculaire-Ile-de-France (CFCAM-IdF)
Research Areas: Applied Physics, Electronic and Photonic Devices
Abstract - The first part of the talk is a high-level review of modern technologies for atomic-level modelling of materials. The second part discusses band gap calculations and MERL results for semi-conductors.
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- Date & Time: Friday, July 22, 2016; 12:00 Noon
Location: Cambridge Brewery
MERL Contacts: Elizabeth Phillips; Jinyun Zhang Brief - MERL hosted its 2nd Annual "Women In Science Celebration". MERL's current team of female interns discussed and celebrated the contributions they've made during their internships at MERL.
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- Date & Time: Wednesday, July 13, 2016; 2:30 PM - 3:30
Speaker: Richard Lehoucq, Sandia National Laboratories
Research Areas: Computer Vision, Digital Video, Machine Learning
Abstract 
My presentation considers the research question of whether existing algorithms and software for the large-scale sparse eigenvalue problem can be applied to problems in spectral graph theory. I first provide an introduction to several problems involving spectral graph theory. I then provide a review of several different algorithms for the large-scale eigenvalue problem and briefly introduce the Anasazi package of eigensolvers.
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- Date & Time: Monday, July 11, 2016; 10 AM - 9:15 PM
Location: Westin Boston Waterfront Pavilion, Boston, Massachusetts
MERL Contacts: Matthew Brand; Arvind Raghunathan 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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- Date & Time: Thursday, July 7, 2016; 2:00 PM
Speaker: Dr. Sonja Glavaski, Program Director, ARPA-E
MERL Host: Arvind Raghunathan
Research Area: Electric Systems
Abstract 
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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- Date: Thursday, June 2, 2016
Location: Norton's Woods Conference Center at American Academy of Arts & Sciences, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro 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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