News & Events

7 Events and Talks were found.

  •  TALK   Prof. Pere Gilabert gave an invited talk at MERL on Machine Learning for Digital Predistortion Linearization of High Efficient Power Amplifier
    Date & Time: Tuesday, February 16, 2021; 11:00-12:00
    Speaker: Prof. Pere Gilabert, Universitat Politecnica de Catalunya, Barcelona, Spain
    MERL Host: Rui Ma
    Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
    • Digital predistortion (DPD) linearization is the most common and spread solution to cope with power amplifiers (PA) inherent linearity versus efficiency trade-off. The use of new radio 5G spectrally efficient signals with high peak-to-average power ratios (PAPR) occupying wider bandwidths only aggravates such compromise. When considering wide bandwidth signals, carrier aggregation or multi-band configurations in high efficient transmitter architectures, such as Doherty PAs, load-modulated balanced amplifiers, envelope tracking PAs or outphasing transmitters, the number of parameters required in the DPD model to compensate for both nonlinearities and memory effects can be unacceptably high. This has a negative impact in the DPD model extraction/adaptation, because it increases the computational complexity and drives to over-fitting and uncertainty.
      This talk will discuss the use of machine learning techniques for DPD linearization. The use of artificial neural networks (ANNs) for adaptive DPD linearization and approaches to reduce the coefficients adaptation time will be discussed. In addition, an overview on several feature-extraction techniques used to reduce the number of parameters of the DPD linearization system as well as to ensure proper, well-conditioned estimation for related variables will be presented.
  •  EVENT   MERL Virtual Open House 2020
    Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
    MERL Contacts: Elizabeth Phillips; Jeroen van Baar; Anthony Vetro
    Location: Virtual
    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
  •  TALK   A Prospect in Wireless Connectivity Beyond 5G: Heterogeneity, Learning, Caution, and New Opportunities
    Date & Time: Thursday, May 7, 2020; 11:00 AM
    Speaker: Prof. Petar Popovski, Aalborg University, Denmark
    MERL Host: Toshiaki Koike-Akino
    Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
    • The wireless landscape evolves towards supporting a large population of connections for humans and machines with very diverse features and requirements. Perhaps the main motivation of 5G wireless systems is its flexibility to support heterogeneous connectivity requirements: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). However, this classification is rather limited and is currently undergoing a revision within the research community. The first part of this talk will discuss how this heterogeneity can be revised and which opportunities it opens with respect to spectrum usage. The second part of the talk will deal with performance guarantees of wireless services and, specifically, ultra-reliable communication and outline the importance of machine learning in that context. The final part of the talk will provide a broader view on the evolution of wireless connectivity, including aspects that are implied by the resistance to the deployment of 5G, but also the new opportunities that can transform the way we build and utilize connected systems.
  •  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
    MERL Contact: Petros Boufounos
    Location: Banff International Research Station (BIRS), Alberta, Canada
    Research Areas: Computational Sensing, Signal Processing
    • 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.
  •  EVENT   MERL 3rd Annual Open House
    Date & Time: Thursday, November 29, 2018; 4-6pm
    MERL Contacts: Marissa Deegan; Elizabeth Phillips; Jeroen van Baar; Anthony Vetro
    Location: 201 Broadway, 8th floor, Cambridge, MA
    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
    • 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:

      Current internship and employment openings:

      Information about working at MERL:
  •  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
    MERL Contact: Petros Boufounos
    Location: MIT Samberg Conference Center Floor 7, 50 Memorial Drive, Cambridge, MA 02142
    Research Areas: Computational Sensing, Communications, Signal Processing
    • 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:

      Organizing committee:
      Dr. Tom Baran, Lumii
      Dr. Petros Boufounos, MERL
      Prof. Anantha Chandrakasan, MIT
      Prof. Yonina Eldar, Technion

      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"
      Prof. Alan Oppenheim, Ford Professor of Engineering, MIT
      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.
  •  TALK   Foundations of Green Communications
    Date & Time: Friday, September 23, 2016; 12:00 PM- 1:00 PM
    Speaker: Dr. Earl McCune, Eridan Communications
    MERL Host: Rui Ma
    Research Areas: Communications, Signal Processing
    • 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.