News & Events

13 were found.




  •  TALK   [MERL Seminar Series 2021] Harnessing machine learning to build better Earth system models for climate projection
    Date & Time: Tuesday, December 14, 2021; 1:00 PM EST
    Speaker: Prof. Chris Fletcher, University of Waterloo
    MERL Host: Ankush Chakrabarty
    Research Areas: Dynamical Systems, Machine Learning, Multi-Physical Modeling
    Brief
    • Decision-making and adaptation to climate change requires quantitative projections of the physical climate system and an accurate understanding of the uncertainty in those projections. Earth system models (ESMs), which solve the Navier-Stokes equations on the sphere, are the only tool that climate scientists have to make projections forward into climate states that have not been observed in the historical data record. Yet, ESMs are incredibly complex and expensive codes and contain many poorly constrained physical parameters—for processes such as clouds and convection—that must be calibrated against observations. In this talk, I will describe research from my group that uses ensembles of ESM simulations to train statistical models that learn the behavior and sensitivities of the ESM. Once trained and validated the statistical models are essentially free to run, which allows climate modelling centers to make more efficient use of precious compute cycles. The aim is to improve the quality of future climate projections, by producing better calibrated ESMs, and to improve the quantification of the uncertainties, by better sampling the equifinality of climate states.
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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
    Speaker: Prof. Melanie Zeilinger, ETH
    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
    • 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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  •  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
    Speaker: Prof. Ashok Veeraraghavan, Rice University
    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
    • 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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  •  NEWS   Ankush Chakrabarty gave an invited talk at CRAN: Centre de Recherche en Automatique de Nancy, France
    Date: October 21, 2021
    Where: Université de Lorraine, France
    MERL Contact: Ankush Chakrabarty
    Research Areas: Artificial Intelligence, Control, Machine Learning, Multi-Physical Modeling, Optimization
    Brief
    • Ankush Chakrabarty (RS, Multiphysical Systems Team) gave an invited talk on `Bayesian-Optimized Estimation and Control for Buildings and HVAC' at the Research Center for Automatic Control (CRAN) in the University of Lorraine in France. The talk presented recent MERL research on probabilistic machine learning for set-point optimization and calibration of digital twins for building energy systems.
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  •  NEWS   Ankush Chakrabarty gave an invited talk at University of Illinois at Chicago
    Date: April 9, 2021
    MERL Contact: Ankush Chakrabarty
    Research Areas: Control, Machine Learning, Multi-Physical Modeling, Optimization
    Brief
    • Ankush Chakrabarty, a Research Scientist at MERL's Multiphysical Systems (MS) Team, gave an invited talk on "Learning for Control and Estimation using Digital Twins" at the Department of Electrical and Computer Engineering Seminar Series organized at UIC. The talk proposed new learning-based control/estimation architectures that can utilize simulation data obtained from digital twins to add self-optimization and constraint-enforcement features to grey/black-box control systems.
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  •  EVENT   MERL Virtual Open House 2020
    Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
    MERL Contacts: Elizabeth Phillips; 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
    Brief
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  •  TALK   Universal Differential Equations for Scientific Machine Learning
    Date & Time: Thursday, May 7, 2020; 12:00 PM
    Speaker: Christopher Rackauckas, MIT
    MERL Host: Christopher R. Laughman
    Research Areas: Machine Learning, Multi-Physical Modeling, Optimization
    Brief
    • In the context of science, the well-known adage "a picture is worth a thousand words" might well be "a model is worth a thousand datasets." Scientific models, such as Newtonian physics or biological gene regulatory networks, are human-driven simplifications of complex phenomena that serve as surrogates for the countless experiments that validated the models. Recently, machine learning has been able to overcome the inaccuracies of approximate modeling by directly learning the entire set of nonlinear interactions from data. However, without any predetermined structure from the scientific basis behind the problem, machine learning approaches are flexible but data-expensive, requiring large databases of homogeneous labeled training data. A central challenge is reco nciling data that is at odds with simplified models without requiring "big data". In this talk we discuss a new methodology, universal differential equations (UDEs), which augment scientific models with machine-learnable structures for scientifically-based learning. We show how UDEs can be utilized to discover previously unknown governing equations, accurately extrapolate beyond the original data, and accelerate model simulation, all in a time and data-efficient manner. This advance is coupled with open-source software that allows for training UDEs which incorporate physical constraints, delayed interactions, implicitly-defined events, and intrinsic stochasticity in the model. Our examples show how a diverse set of computationally-difficult modeling issues across scientific disciplines, from automatically discovering biological mechanisms to accelerating climate simulations by 15,000x, can be handled by training UDEs.
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  •  NEWS   Scott Bortoff gave Mercer Distinguished Lecture at Rensselaer Polytechnic Institute
    Date: September 25, 2019
    Where: Rensselaer Polytechnic Institute (RPI), Troy, NY
    MERL Contact: Scott A. Bortoff
    Research Areas: Control, Multi-Physical Modeling
    Brief
    • The seminar, entitled “HVAC System Control and Optimization,” was part of the Mercer Distinguished Lecture Series in the Electrical, Computer and Systems Engineering Department at Rensselaer Polytechnic Institute (RPI), Troy, NY. Given on Wednesday September 25, 2019, it focused on the systems engineering and control issues associated with highly integrated Heating, Ventilation and Air Conditioning Systems for low and zero energy buildings.
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  •  NEWS   The Ab Initio paper selected as "HOT Physical Chemistry Chemical Physics article" and is made free to access the end of July 2019
    Date: June 12, 2019
    Where: Physical Chemistry Chemical Physics – Published 22 Feb 2019
    MERL Contact: Chungwei Lin
    Research Areas: Applied Physics, Multi-Physical Modeling
    Brief
    • The journal "Physical Chemistry Chemical Physics (PCCP)" selects a few well-received articles highlighted as HOT by the handling editor or referees. The following paper "Band Alignment in Quantum Wells from Automatically Tuned DFT+U" with MERL authors Grigory Kolesov, Chungwei Lin, Andrew Knyazev, Keisuke Kojima, Joseph Katz has been selected as a 2019 HOT Physical Chemistry Chemical Physics article, and is made free to access until the end of July 2019. This paper provides a semi-empirical methodology to compute the lattice and electronic structures of systems composed of 400+ atoms. The efficiency of this method allows for realistic simulations of interfaces between semiconductors, which is nearly impossible using the existing methods due to the extremely large degrees of freedom involved. The formalism is tested against a few established band alignments and then applied to determine the band gaps of quantum wells; the agreement is within the experimental uncertainty.
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  •  EVENT   MERL 3rd Annual Open House
    Date & Time: Thursday, November 29, 2018; 4-6pm
    MERL Contacts: Marissa Deegan; Elizabeth Phillips; 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
    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 collaborates with MIT on heat management in compact fusion reactors
    Date: October 11, 2018
    MERL Contact: Christopher R. Laughman
    Research Area: Multi-Physical Modeling
    Brief
    • A new approach to heat management in compact fusion reactors that emerged from a class at MIT, developed by graduate student Adam Kuang and 14 other MIT students, engineers from Commonwealth Fusion Systems as well as Piyush Grover and Chris Laughman from MERL, and Professor Dennis Whyte, was recently published in Fusion Engineering and Design. This solution was made possible by an innovative approach to compact fusion reactors, using high-temperature superconducting magnets. This method formed the basis for a massive new research program launched this year at MIT and the creation of an independent startup company to develop the concept. The new design, unlike that of typical fusion plants, would make it possible to open the device's internal chamber and replace critical components; this capability is essential for the newly proposed heat-draining mechanism.

      In the one-semester graduate class 22.63 (Principles of Fusion Engineering), students were divided into teams to address different aspects of the heat rejection challenge. These teams evaluated alternate concepts and subjected candidate designs to detailed calculations and simulations based, in part, on data from decades of research on research fusion devices such as MIT's Alcator C-Mod, which was retired two years ago. C-Mod scientist Brian LaBombard also shared insights on new kinds of divertors, and two engineers from MERL worked with the team as well. Several of the students continued working on the project after the class ended, ultimately leading to the solution described in this new paper.
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  •  EVENT   MERL hosts Workshops for 2018 American Modelica Conference
    Date & Time: Monday, October 8, 2018 - Thursday, October 11, 2018; 8am-5pm
    MERL Contact: Christopher R. Laughman
    Location: MIT Samberg Conference Center, Cambridge, MA
    Research Areas: Control, Multi-Physical Modeling
    Brief
    • The 2018 American Modelica Conference, the first North American conference focused on the Modelica multiphysics modeling language, will be held on Tuesday and Wednesday, October 9-10, 2018 at the Samberg Conference Center at MIT in Cambridge, MA. Chris Laughman, a team leader in the Multiphysical Systems and Devices group, is the local chair for the conference.

      This conference will feature over 40 papers and user presentations on the Modelica language and its application to a wide variety of problem domains, including thermofluid, aerospace, automotive, and energy systems. There will also be 2 keynote addresses by John McKibben (Proctor & Gamble) and Hilding Elmqvist (Mogram AB). Nearly 100 attendees from 11 different countries have already registered for the conference, and it promises to be a very educational experience.

      MERL is also hosting two free workshops on October 8 to provide opportunities to engineers looking to increase their familiarity with the language and its applications. An introductory workshop will be led by engineers from Modelon during that morning, and then a second workshop on the application of Modelica to building systems will be led by Michael Wetter from Lawrence Berkeley National Labs in the afternoon. MERL will also host a Modelica user meeting on October 11 that will provide more details and discussion about trends in the use and development of Modelica in the larger engineering community.
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