News & Events

122 News items and Awards were found.

  •  NEWS   Mouhacine Benosman co-edited a special issue on Learning-based Adaptive Control: Theory and Applications
    Date: February 4, 2019
    MERL Contact: Mouhacine Benosman
    Research Areas: Control, Data Analytics, Dynamical Systems
    • Mouhacine Benosman is a guest editor of a special issue on Learning-based Adaptive Control: Theory and Application, recently published by the International Journal of Adaptive Control and Signal Processing. Other guest editors included Professor F.L. Lewis (University of Texas at Arlington Research Institute), Professor M. Guay (Queen's University), and Professor D. Owens (The University of Sheffield).

      The special issue presents results of current research on learning-based adaptive methods, merging together model-based and data-driven machine learning approaches.

      More information on the content of this special issue can be found at:
  •  NEWS   Mouhacine Benosman joins the Editorial Board of the new Wiley Journal of Advanced Control for Applications
    Date: November 1, 2018
    MERL Contact: Mouhacine Benosman
    Research Areas: Control, Data Analytics, Dynamical Systems
    • Wiley has recently launched the Journal of Advanced Control for Applications: Engineering and Industrial Systems, which seeks original and high-quality contributions on the design of advanced control for applications. The aim is to stimulate the adoption of new and improved control design methods and provide a forum for the discussion of control application problems. Papers for the journal must include sufficient novelty in either the control design methods, the modelling and simulation techniques used, or the applications studied. MERL researcher, Mouhacine Benosman, has been invited to join the Editorial Board of this new journal.
  •  NEWS   MERL Researchers Demonstrate Robot Learning Technology at CEATEC'18
    Date: October 15, 2018 - October 19, 2018
    Where: CEATEC'18, Makuhari Messe, Tokyo
    MERL Contacts: Devesh Jha; Daniel Nikovski; Diego Romeres; Alan Sullivan; Jeroen van Baar; William Yerazunis
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Robotics
    • MERL's work on robot learning algorithms was demonstrated at CEATEC'18, Japan's largest IT and electronics exhibition and conference held annually at Makuhari Messe near Tokyo. A team of researchers from the Data Analytics Group at MERL and the Artificial Intelligence Department of the Information Technology Center (ITC) of MELCO presented an interactive demonstration of a model-based artificial intelligence algorithm that learns how to control equipment autonomously. The algorithm developed at MERL constructs models of mechanical equipment through repeated trial and error, and then learns control policies based on these models. The demonstration used a circular maze, where the objective is to drive a ball to the center of the maze by tipping and tilting the maze, a task that is difficult even for humans; approximately half of the CEATEC'18 visitors who tried to steer the ball by means of a joystick could not bring it to the center of the maze within one minute. In contrast, MERL's algorithm successfully learned how to drive the ball to the goal within ten seconds without the need for human programming. The demo was at the entrance of MELCO's booth at CEATEC'18, inviting visitors to learn more about MELCO's many other AI technologies on display, and was seen by an estimated more than 50,000 visitors over the five days of the expo.
  •  NEWS   Best doctoral dissertation award received by Visiting Research Scientist Thiago Serra
    Date: June 4, 2018
    Where: Pittsburgh, Pennsylvania
    MERL Contacts: Arvind Raghunathan; Thiago Serra
    Research Areas: Optimization, Data Analytics
    • Thiago Serra, currently a Visiting Research Scientist in the Data Analytics group, has been awarded the Gerald L. Thompson Doctoral Dissertation Award in Management Science from the Tepper School of Business, Carnegie Mellon University. This is awarded each year to honor an outstanding doctoral dissertation involving theoretical, computational and applied contributions in the area of Management Science. One of the thesis chapters, "The Integrated Last-Mile Transportation Problem" was work performed at MERL in conjunction with Arvind Raghunathan during a summer internship. This work resulted in a patent application and will be presented at the 2018 International Conference on Automated Planning and Scheduling (ICAPS).
  •  NEWS   Mouhacine Benosman joins the Editorial Board of the International Journal of Adaptive Control and Signal Processing
    Date: March 19, 2018
    MERL Contact: Mouhacine Benosman
    • MERL researcher Mouhacine Benosman has been appointed as a member of the Editorial Board of the International Journal of Adaptive Control and Signal Processing.

      The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.
  •  NEWS   Andrew Knyazev (MERL) presents at the Schlumberger-Tufts U. Computational and Applied Math Seminar
    Date: April 10, 2018
    Research Areas: Machine Learning, Signal Processing
    • Andrew Knyazev, Distinguished Research Scientist of MERL, has accepted an invitation to speak about his work on Big Data and spectral graph partitioning at the Schlumberger-Tufts U. Computational and Applied Math Seminar. A primary focus of this seminar series is on mathematical and computational aspects of remote sensing. A partial list of the topics of interest includes: numerical solution of large scale PDEs (a.k.a. forward problems); theory and numerical methods of inverse and ill-posed problems; imaging; related problems in numerical linear algebra, approximation theory, optimization and model reduction. The seminar meets on average once a month, the location alternates between Schlumberger's office in Cambridge, MA and the Tufts Medford Campus.

      Abstract: Data clustering via spectral graph partitioning requires constructing the graph Laplacian and solving the corresponding eigenvalue problem. We consider and motivate using negative edge weights in the graph Laplacian. Preconditioned iterative solvers for the Laplacian eigenvalue problem are discussed and preliminary numerical results are presented.
  •  AWARD   Best Student Paper Award at the International Conference on Data Mining
    Date: November 30, 2017
    Awarded to: Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn Keogh
    MERL Contact: Daniel Nikovski
    Research Areas: Data Analytics
    • 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.
  •  NEWS   MERL Researchers Demonstrate New Model-Based AI Learning Technology for Equipment Control
    Date: February 14, 2018
    Where: Tokyo, Japan
    MERL Contacts: Devesh Jha; Daniel Nikovski; Diego Romeres; William Yerazunis; Jeroen van Baar; Alan Sullivan
    Research Areas: Optimization, Computer Vision, Artificial Intelligence, Data Analytics, Robotics
    • 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.
  •  NEWS   Andrew Knyazev (MERL) invited to 2018 MathWorks Research Summit
    Date: June 2, 2018 - June 4, 2018
    Where: Newton, Massachusetts (USA)
    Research Areas: Control, Computer Vision, Dynamical Systems, Machine Learning, Data Analytics
    • 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.
  •  NEWS   MERL invites applications for Visiting Faculty
    Date: February 15, 2018
    • 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:

      The application deadline for positions starting in Summer/Fall 2018 is February 15, 2018.
  •  NEWS   MERL attends The Grace Hopper Celebration of Women in Computing
    Date: October 4, 2017 - October 6, 2017
    Where: Orange County Convention Center, Orlando, FL
    MERL Contacts: Elizabeth Phillips; Jinyun Zhang
    • 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.
  •  AWARD   2017 Graph Challenge Student Innovation Award
    Date: August 4, 2017
    Awarded to: David Zhuzhunashvili and Andrew Knyazev
    Research Area: Machine Learning
    • 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 (, 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.
  •  NEWS   MERL researchers presented 11 papers at ACC 2017 (American Controls Conference)
    Date: May 24, 2017 - May 26, 2017
    MERL Contacts: Mouhacine Benosman; Daniel Burns; Claus Danielson; Stefano Di Cairano; Abraham Goldsmith; Uroš Kalabić; Saleh Nabi; Daniel Nikovski; Arvind Raghunathan; Yebin Wang
    Research Areas: Control, Dynamical Systems, Machine Learning
    • Talks were presented by members of several groups at MERL and covered a wide range of topics:
      - Similarity-Based Vehicle-Motion Prediction
      - Transfer Operator Based Approach for Optimal Stabilization of Stochastic Systems
      - Extended command governors for constraint enforcement in dual stage processing machines
      - Cooperative Optimal Output Regulation of Multi-Agent Systems Using Adaptive Dynamic Programming
      - Deep Reinforcement Learning for Partial Differential Equation Control
      - Indirect Adaptive MPC for Output Tracking of Uncertain Linear Polytopic Systems
      - Constraint Satisfaction for Switched Linear Systems with Restricted Dwell-Time
      - Path Planning and Integrated Collision Avoidance for Autonomous Vehicles
      - Least Squares Dynamics in Newton-Krylov Model Predictive Control
      - A Neuro-Adaptive Architecture for Extremum Seeking Control Using Hybrid Learning Dynamics
      - Robust POD Model Stabilization for the 3D Boussinesq Equations Based on Lyapunov Theory and Extremum Seeking
  •  NEWS   MERL makes a strong showing at the American Control Conference
    Date: July 6, 2016 - July 8, 2016
    Where: American Control Conference (ACC)
    MERL Contacts: Mouhacine Benosman; Scott Bortoff; Petros Boufounos; Daniel Burns; Claus Danielson; Stefano Di Cairano; Abraham Goldsmith; Piyush Grover; Uroš Kalabić; Christopher Laughman; Daniel Nikovski; Arvind Raghunathan; Yebin Wang; Avishai Weiss
    Research Areas: Control, Dynamical Systems, Machine Learning, Optimization, Robotics, Data Analytics
    • The premier American Control Conference (ACC) takes place in Boston July 6-8. This year MERL researchers will present a record 20 papers(!) at ACC, with several contributions, especially in autonomous vehicle path planning and in Model Predictive Control (MPC) theory and applications, including manufacturing machines, electric motors, satellite station keeping, and HVAC. Other important themes developed in MERL's presentations concern adaptation, learning, and optimization in control systems.
  •  AWARD   Fellow of the Society for Industrial and Applied Mathematics (SIAM)
    Date: March 31, 2016
    Awarded to: Andrew Knyazev
    Research Areas: Control, Optimization, Dynamical Systems, Machine Learning, Data Analytics, Communications, Signal Processing
    • Andrew Knyazev selected as a Fellow of the Society for Industrial and Applied Mathematics (SIAM) for contributions to computational mathematics and development of numerical methods for eigenvalue problems.

      Fellowship honors SIAM members who have made outstanding contributions to the fields served by the SIAM. Andrew Knyazev was among a distinguished group of members nominated by peers and selected for the 2016 Class of Fellows.
  •  NEWS   MERL Researchers Attend Modelica North American Users Group Meeting
    Date: November 11, 2015 - November 12, 2015
    Where: University of Connecticut
    MERL Contacts: Christopher Laughman; Scott Bortoff; Hongtao Qiao
    Research Area: Data Analytics
    • MERL Researchers Scott A. Bortoff, Chris Laughman and Hongtao Qiao attended the North America Modelica User's Group Meeting, hosted by the University of Connecticut, November 11-12, 2015. Scott Bortoff gave the Keynote Address entitled "Using Modelica in Industrial Research and Development," and Chris Laughman and Hongtao Qiao each presented a paper on modelling of HVAC systems. The Meeting attracted approximately 80 Modelica users from a diverse set of companies and universities including United Technologies, Johnson Controls and Ford. Use of Modelica is accelerating in North America, lead by largely by automotive and similar "systems manufacturing" type companies.
  •  NEWS   MERL researchers attend International Modelica Conference
    Date: September 21, 2015
    MERL Contacts: Scott Bortoff; Daniel Burns; Christopher Laughman
    • MERL researchers Scott Bortoff, Dan Burns and Chris Laughman attended the 11th Annual Modelica Conference in Versailles, France. Modelica is a computer language for modelling and simulation of multiphysical systems. There were 421 attendees, with representatives from Toyota, automobile companies, European universities and companies like Dassault. Conference topics included a plenary on cyber-physical systems modelling by Prof. Sangiovanni Vincentelli of UC Berkeley, new libraries for modelling HVAC systems, automobile systems and buildings, and research results for new solvers. An important trend is virtual modelling and simulation of building thermodynamics (scaling up to city districts), automotive systems (autonomous vehicles), and especially Factory Automation: Dassault is investing heavily in this area, focusing on smaller customers, with tools for 3D virtual modelling of assembly lines including machine dynamics (robotics), and in partnerships with Siemens and other European FA companies.
  •  NEWS   MERL researchers present 10 papers at the American Controls Conference
    Date: July 3, 2015
    MERL Contacts: Daniel Nikovski; Yebin Wang; Uroš Kalabić; Stefano Di Cairano; Arvind Raghunathan; Avishai Weiss; Daniel Burns
    • MERL researchers presented 10 papers at the American Controls Conference, in Chicago, USA. The ACC is one of the most important conferences on control systems in the world. Topics ranged from theoretical, including new algorithms for Model Predictive Control and Co-Design, to applications including spacecraft control and HVAC systems.
  •  NEWS   MERL researcher's spam filter finds automobile safety defects at NHTSA
    Date: June 25, 2015
    MERL Contact: William Yerazunis
    Research Area: Data Analytics
    • The CRM114 Discriminator, an open-source spam filter / text classifier created by William Yerazunis in MERL's Data Analytics group, continues to turn up in interesting places - and apparently one of them is in the US Department of Transportation's process for analysis of car safety defect reports.

      Although CRM114 is usually used as a spam filter, CRM114 has been used to analyze resumes for jobseekers, scanning outgoing emails to detect accidental confidential information leaks, perusing blogs for relevance, scanning syslog files for interesting events, and now, apparently, searching complaints sent to NHTSA to find safety-related vehicle malfunctions.
  •  NEWS   Fast three-phase load-flow analysis algorithms developed by MERL included in MELCO's Smart Grid Demonstration Project
    Date: February 13, 2014
    MERL Contacts: Hongbo Sun; Daniel Nikovski
    Research Area: Data Analytics
    • Mitsubishi Electric Corporation announced that it has developed energy loss-reduction technology that uses algorithms for fast analysis of three-phase electricity developed by MERL to establish optimal coordination of power-distribution grids for reductions in energy loss and power-generation costs. The technology was achieved under Mitsubishi Electric's Smart Grid Demonstration Project.