News & Events

47 News items, Awards, Events or Talks found.



Learn about the MERL Seminar Series.



  •  NEWS    MERL Scientists Presenting 5 Papers at IEEE International Conference on Communications (ICC) 2022
    Date: May 16, 2022 - May 20, 2022
    Where: Seoul, Korea
    MERL Contacts: Jianlin Guo; Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Philip V. Orlik; Kieran Parsons; Pu (Perry) Wang; Ye Wang
    Research Areas: Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Machine Learning, Signal Processing
    Brief
    • MERL Connectivity & Information Processing Team scientists remotely presented 5 papers at the IEEE International Conference on Communications (ICC) 2022, held in Seoul Korea on May 16-20, 2022. Topics presented include recent advancements in communications technologies, deep learning methods, and quantum machine learning (QML). Presentation videos are also found on our YouTube channel. In addition, K. J. Kim organized "Industrial Private 5G-and-beyond Wireless Networks Workshop" at the conference.

      IEEE ICC is one of two IEEE Communications Society’s flagship conferences (ICC and Globecom). Each year, close to 2,000 attendees from over 70 countries attend IEEE ICC to take advantage of a program which consists of exciting keynote session, robust technical paper sessions, innovative tutorials and workshops, and engaging industry sessions. This 5-day event is known for bringing together audiences from both industry and academia to learn about the latest research and innovations in communications and networking technology, share ideas and best practices, and collaborate on future projects.
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  •  TALK    [MERL Seminar Series 2022] Beyond the First Portrait of a Black Hole
    Date & Time: Tuesday, February 15, 2022; 1:00 PM EST
    Speaker: Katie Bouman, California Institute of Technology
    MERL Host: Joshua Rapp
    Research Area: Computational Sensing
    Abstract
    • As imaging requirements become more demanding, we must rely on increasingly sparse and/or noisy measurements that fail to paint a complete picture. Computational imaging pipelines, which replace optics with computation, have enabled image formation in situations that are impossible for conventional optical imaging. For instance, the first black hole image, published in 2019, was only made possible through the development of computational imaging pipelines that worked alongside an Earth-sized distributed telescope. However, remaining scientific questions motivate us to improve this computational telescope to see black hole phenomena still invisible to us and to meaningfully interpret the collected data. This talk will discuss how we are leveraging and building upon recent advances in machine learning in order to achieve more efficient uncertainty quantification of reconstructed images as well as to develop techniques that allow us to extract the evolving structure of our own Milky Way's black hole over the course of a night, perhaps even in three dimensions.
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  •  AWARD    Joshua Rapp wins Best Dissertation Award from the IEEE Signal Processing Society
    Date: December 20, 2021
    Awarded to: Joshua Rapp
    MERL Contact: Joshua Rapp
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • Joshua Rapp has won the 2021 Best PhD Dissertation Award from the IEEE Signal Processing Society.
      The award recognizes a PhD thesis completed on a signal processing subject within the past three years for its relevant work in signal processing while stimulating further research in the field.

      Dr. Rapp completed his PhD at Boston University in 2020 with a thesis entitled "Probabilistic Modeling for Single-Photon Lidar." The dissertation tackles challenges of the acquisition and processing of 3D depth maps reconstructed from time-of-flight data captured one photon at a time.
      The award will be presented at the 2022 IEEE International Conference on Image Processing (ICIP) in France.
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  •  EVENT    Prof. Melanie Zeilinger of ETH to give keynote at MERL's Virtual Open House
    Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
    Location: Virtual Event
    Speaker: Prof. Melanie Zeilinger, ETH
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
    Brief
    • MERL is excited to announce the second keynote speaker for our Virtual Open House 2021:
      Prof. Melanie Zeilinger from ETH .

      Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

      Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Zeilinger's talk is scheduled for 3:15pm - 3:45pm (EST).

      Registration: https://mailchi.mp/merl/merlvoh2021

      Keynote Title: Control Meets Learning - On Performance, Safety and User Interaction

      Abstract: With increasing sensing and communication capabilities, physical systems today are becoming one of the largest generators of data, making learning a central component of autonomous control systems. While this paradigm shift offers tremendous opportunities to address new levels of system complexity, variability and user interaction, it also raises fundamental questions of learning in a closed-loop dynamical control system. In this talk, I will present some of our recent results showing how even safety-critical systems can leverage the potential of data. I will first briefly present concepts for using learning for automatic controller design and for a new safety framework that can equip any learning-based controller with safety guarantees. The second part will then discuss how expert and user information can be utilized to optimize system performance, where I will particularly highlight an approach developed together with MERL for personalizing the motion planning in autonomous driving to the individual driving style of a passenger.
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  •  AWARD    Petros Boufounos Elevated to IEEE Fellow
    Date: January 1, 2022
    Awarded to: Petros T. Boufounos
    MERL Contact: Petros T. Boufounos
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • MERL’s Petros Boufounos has been elevated to IEEE Fellow, effective January 2022, for “contributions to compressed sensing.”

      IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society. Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.
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  •  EVENT    Prof. Ashok Veeraraghavan of Rice University to give keynote at MERL's Virtual Open House
    Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
    Location: Virtual Event
    Speaker: Prof. Ashok Veeraraghavan, Rice University
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
    Brief
    • MERL is excited to announce the first keynote speaker for our Virtual Open House 2021:
      Prof. Ashok Veeraraghavan from Rice University.

      Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

      Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Veeraraghavan's talk is scheduled for 1:15pm - 1:45pm (EST).

      Registration: https://mailchi.mp/merl/merlvoh2021

      Keynote Title: Computational Imaging: Beyond the limits imposed by lenses.

      Abstract: The lens has long been a central element of cameras, since its early use in the mid-nineteenth century by Niepce, Talbot, and Daguerre. The role of the lens, from the Daguerrotype to modern digital cameras, is to refract light to achieve a one-to-one mapping between a point in the scene and a point on the sensor. This effect enables the sensor to compute a particular two-dimensional (2D) integral of the incident 4D light-field. We propose a radical departure from this practice and the many limitations it imposes. In the talk we focus on two inter-related research projects that attempt to go beyond lens-based imaging.

      First, we discuss our lab’s recent efforts to build flat, extremely thin imaging devices by replacing the lens in a conventional camera with an amplitude mask and computational reconstruction algorithms. These lensless cameras, called FlatCams can be less than a millimeter in thickness and enable applications where size, weight, thickness or cost are the driving factors. Second, we discuss high-resolution, long-distance imaging using Fourier Ptychography, where the need for a large aperture aberration corrected lens is replaced by a camera array and associated phase retrieval algorithms resulting again in order of magnitude reductions in size, weight and cost. Finally, I will spend a few minutes discussing how the wholistic computational imaging approach can be used to create ultra-high-resolution wavefront sensors.
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  •  EVENT    MERL Virtual Open House 2021
    Date & Time: Thursday, December 9, 2021; 100pm-5:30pm (EST)
    Location: Virtual Event
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
    Brief
    • Mitsubishi Electric Research Laboratories cordially invites you to join our Virtual Open House, on December 9, 2021, 1:00pm - 5:30pm (EST).

      The event will feature keynotes, live sessions, research area booths, and time for open interactions with our researchers. Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities.

      Registration: https://mailchi.mp/merl/merlvoh2021
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  •  TALK    [MERL Seminar Series 2021] Prof. Greg Ongie presents talk at MERL entitled Learning to Solve Inverse Problems in Computational Imaging: Recent Innovations
    Date & Time: Tuesday, October 12, 2021; 1:00 PM EST
    Speaker: Prof. Greg Ongie, Marquette University
    MERL Host: Hassan Mansour
    Research Areas: Computational Sensing, Machine Learning, Signal Processing
    Abstract
    • Deep learning is emerging as powerful tool to solve challenging inverse problems in computational imaging, including basic image restoration tasks like denoising and deblurring, as well as image reconstruction problems in medical imaging. This talk will give an overview of the state-of-the-art supervised learning techniques in this area and discuss two recent innovations: deep equilibrium architectures, which allows one to train an effectively infinite-depth reconstruction network; and model adaptation methods, that allow one to adapt a pre-trained reconstruction network to changes in the imaging forward model at test time.
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  •  NEWS    Keynote Speech by Dr. Petros Boufounos
    Date: August 5, 2021
    MERL Contact: Petros T. Boufounos
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • MERL's Distinguished Researcher Dr. Petros Boufounos is the keynote speaker for the Center for Advanced Signal and Image Sciences (CASIS) 25th Annual Workshop on Aug. 5, 2021, with talk titled, "The Computational Sensing Revolution in Array Processing."
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  •  AWARD    Best Paper - Honorable Mention Award at WACV 2021
    Date: January 6, 2021
    Awarded to: Rushil Anirudh, Suhas Lohit, Pavan Turaga
    MERL Contact: Suhas Lohit
    Research Areas: Computational Sensing, Computer Vision, Machine Learning
    Brief
    • A team of researchers from Mitsubishi Electric Research Laboratories (MERL), Lawrence Livermore National Laboratory (LLNL) and Arizona State University (ASU) received the Best Paper Honorable Mention Award at WACV 2021 for their paper "Generative Patch Priors for Practical Compressive Image Recovery".

      The paper proposes a novel model of natural images as a composition of small patches which are obtained from a deep generative network. This is unlike prior approaches where the networks attempt to model image-level distributions and are unable to generalize outside training distributions. The key idea in this paper is that learning patch-level statistics is far easier. As the authors demonstrate, this model can then be used to efficiently solve challenging inverse problems in imaging such as compressive image recovery and inpainting even from very few measurements for diverse natural scenes.
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  •  NEWS    MERL published four papers in 2020 IEEE Global Communications Conference
    Date: December 7, 2020 - December 11, 2020
    Where: Taipei, Taiwan
    MERL Contacts: Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Philip V. Orlik; Pu (Perry) Wang; Ye Wang
    Research Areas: Communications, Computational Sensing, Machine Learning, Signal Processing
    Brief
    • MERL researchers have published four papers in 2020 IEEE Global Communications Conference (GlobeComm). This conference is one of the two IEEE Communications Societies flagship conferences dedicated to Communications for Human and Machine Intelligence. Topics of the published papers include, transmit diversity schemes, coding for molecular networks, and location and human activity sensing via WiFi signals.
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  •  EVENT    MERL Virtual Open House 2020
    Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
    Location: Virtual
    MERL Contacts: Elizabeth Phillips; Anthony Vetro
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
    Brief
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  •  NEWS    MERL Researcher Pu (Perry) Wang organized a special session on automotive radar sensing at IEEE SAM Workshop 2020
    Date: June 8, 2020 - June 12, 2020
    Where: Virtual Hangzhou
    MERL Contact: Pu (Perry) Wang
    Research Areas: Artificial Intelligence, Computational Sensing, Dynamical Systems, Machine Learning, Signal Processing
    Brief
    • MERL researcher Pu (Perry) Wang organized a special session on June 10, 2020 titled Automotive Radar Sensing. Presentations included topics from deep waveform design, object tracking, mutual interference mitigation with their applications to high-resolution automotive imaging. The session's contributors come from both academia and industry.

      In this special session, our previous intern Yuxuan Xia (Chalmers Institute of Technology, Sweden) presented our work on extended object tracking using low-cost automotive radar sensors with a realistic measurement model. Yuxuan was also selected to be one of the six best student paper finalists at IEEE SAM 2020.
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  •  NEWS    MERL presenting 13 papers and an industry talk at ICASSP 2020
    Date: May 4, 2020 - May 8, 2020
    Where: Virtual Barcelona
    MERL Contacts: Karl Berntorp; Petros T. Boufounos; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Philip V. Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
    Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio
    Brief
    • MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.

      Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.

      This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.

      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. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
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  •  NEWS    IEEE-NH ComSig lecture by MERL's Petros Boufounos
    Date: April 4, 2019
    Where: Nashua Public Library, Nashua, NH
    MERL Contact: Petros T. Boufounos
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • MERL's Petros Boufounos gave a lecture for the IEEE-NH ComSig chapter at the Nashua Public Library as part of the IEEE Signal Processing Society Distinguished Lecturer series.

      Title: "An Inverse Problem Framework for Array Processing Systems."

      Abstract: Array-based sensing systems, such as ultrasonic, radar and optical (LIDAR) are becoming increasingly important in a variety of applications, including robotics, autonomous driving, medical imaging, and virtual reality, among others. This has led to continuous improvements in sensing hardware, but also to increasing demand for theory and methods to inform the system design and improve the processing. In this talk we will discuss how recent advances in formulating and solving inverse problems, such as compressed sensing, blind deconvolution, and sparse signal modeling can be applied to significantly reduce the cost and improve the capabilities of array-based and multichannel sensing systems. We show that these systems share a common mathematical framework, which allows us to describe both the acquisition hardware and the scene being acquired. Under this framework we can exploit prior knowledge on the scene, the system, and a variety of errors that might occur, allowing for significant improvements in the reconstruction accuracy. Furthermore, we can consider the design of the system itself in the context of the inverse problem, leading to designs that are more efficient, more accurate, or less expensive, depending on the application. In the talk we will explore applications of this model to LIDAR and depth sensing, radar and distributed radar, and ultrasonic sensing. In the context of these applications, we will describe how different models can lead to improved specifications in ultrasonic systems, robustness to position and timing errors in distributed array systems, and cost reduction and new capabilities in LIDAR systems.
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  •  NEWS    MERL presenting 16 papers at ICASSP 2019
    Date: May 12, 2019 - May 17, 2019
    Where: Brighton, UK
    MERL Contacts: Petros T. Boufounos; Anoop Cherian; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Tim K. Marks; Philip V. Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
    Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio
    Brief
    • MERL researchers will be presenting 16 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Brighton, UK from May 12-17, 2019. Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, and parameter estimation. MERL is also a sponsor of the conference and will be participating in the student career luncheon; please join us at the lunch to learn about our internship program and career opportunities.

      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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  •  NEWS    Petros Boufounos is appointed 2019 IEEE Signal Processing Society Distinguished Lecturer
    Date: December 12, 2018
    MERL Contact: Petros T. Boufounos
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • MERL's Petros Boufounos has been appointed as a member of the 2019 class of the IEEE Signal Processing Society Class of Distinguished Lecturers for the term of 1 January 2019 to 31 December 2020.

      The IEEE SPS Distinguished Lecturer (DL) Program provides a means for Chapters to have access to well-known educators and authors in the fields of signal processing to lecture at Chapter meetings. Each year, five DLs are appointed by the society. In addition to Dr. Boufounos, his year's class includes Israel Cohen (Technion - Israel Institute of Technology), Janusz Konrad (Boston University), Anna Scaglione (Arizona State University), and Rui Zhang (National University of Singapore).
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  •  EVENT    Dr. Petros Boufounos is co-organizing workshop on the Intersection of Information Theory and Signal Processing
    Date: Sunday, October 28, 2018 - Friday, November 2, 2018
    Location: Banff International Research Station (BIRS), Alberta, Canada
    MERL Contact: Petros T. Boufounos
    Research Areas: Computational Sensing, Signal Processing
    Brief
    • Dr. Petros Boufounos, Prof. Stark Draper (U. of Toronto) and Prof. Yonina Eldar (Technion) are co-organizing a workshop on the intersection of Information Theory and Signal Processing. The 5-day workshop will take place Oct. 28 - Nov. 2 at the Banff International Research Station (BIRS) in Alberta, Canada. The workshop schedule includes invited talks from prominent researchers in the two fields, coming together from all over the world. Parts of the workshop will be streamed live through the BIRS website.
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  •  EVENT    MERL 3rd Annual Open House
    Date & Time: Thursday, November 29, 2018; 4-6pm
    Location: 201 Broadway, 8th floor, Cambridge, MA
    MERL Contacts: Elizabeth Phillips; Anthony Vetro
    Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
    Brief
    • Snacks, demos, science: On Thursday 11/29, 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 including artificial intelligence, robotics, computer vision, speech processing, optimization, machine learning, data analytics, signal processing, communications, sensing, control and dynamical systems, as well as multi-physyical modeling and electronic devices. 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:
      merlopenhouse.eventbrite.com

      Current internship and employment openings:
      www.merl.com/internship/openings
      www.merl.com/employment/employment

      Information about working at MERL:
      www.merl.com/employment.
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  •  NEWS    MERL presenting 9 papers at ICASSP 2018
    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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  •  EVENT    MERL's Petros Boufounos is co-organizing symposium on The Future Of Signal Processing
    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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  •  NEWS    MERL presents 5 papers at ICIP 2017, Anthony Vetro serves as general co-chair
    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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  •  NEWS    MERL to present 10 papers at ICASSP 2017
    Date: March 5, 2017 - March 9, 2017
    Where: New Orleans
    MERL Contacts: Petros T. Boufounos; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Anthony Vetro; Ye Wang
    Research Areas: Computer Vision, Computational Sensing, Digital Video, Information Security, Speech & Audio
    Brief
    • MERL researchers will presented 10 papers at the upcoming IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), to be held in New Orleans from March 5-9, 2017. Topics to be presented include recent advances in speech recognition and audio processing; graph signal processing; computational imaging; and privacy-preserving data analysis.

      ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
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  •  TALK    High-Dimensional Analysis of Stochastic Optimization Algorithms for Estimation and Learning
    Date & Time: Tuesday, December 13, 2016; Noon
    Speaker: Yue M. Lu, John A. Paulson School of Engineering and Applied Sciences, Harvard University
    MERL Host: Petros T. Boufounos
    Research Areas: 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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  •  TALK    Collaborative dictionary learning from big, distributed data
    Date & Time: Friday, December 2, 2016; 11:00 AM
    Speaker: Prof. Waheed Bajwa, Rutgers University
    MERL Host: Petros T. Boufounos
    Research 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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