- Date: July 10, 2019 - July 12, 2019
Where: Philadelphia
MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Yebin Wang; Avishai Weiss
Research Areas: Control, Machine Learning, Optimization
Brief - At the American Control Conference, MERL presented 8 papers on subjects including model predictive control applications, estimation and motion planning for vehicles, modular control architectures, and adaptation and learning.
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- Date & Time: Tuesday, July 16, 2019; 12:00 PM
Speaker: Prof. Jeff Linderoth, University of Wisconsin-Madison
MERL Host: Arvind Raghunathan
Research Areas: Machine Learning, Optimization
Abstract 
Algorithms to solve mixed integer linear programs have made incredible progress in the past 20 years. Key to these advances has been a mathematical analysis of the structure of the set of feasible solutions. We argue that a similar analysis is required in the case of mixed integer quadratic programs, like those that arise in sparse optimization in machine learning. One such analysis leads to the so-called perspective relaxation, which significantly improves solution performance on separable instances. Extensions of the perspective reformulation can lead to algorithms that are equivalent to some of the most popular, modern, sparsity-inducing non-convex regularizations in variable selection. Based on joint work with Hongbo Dong (Washington State Univ. ), Oktay Gunluk (IBM), and Kun Chen (Univ. Connecticut).
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- Date: June 25, 2019 - June 28, 2019
Where: Naples, Italy
MERL Contacts: Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Devesh K. Jha; Christopher R. Laughman; Daniel N. Nikovski; Diego Romeres; William S. Yerazunis
Research Areas: Control, Machine Learning, Optimization
Brief - The European Control Conference is the premier control conference in Europe. This year MERL was well represented with papers on control for HVAC, machine learning for estimation and control, robot assembly, and optimization methods for control.
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- Date: July 4, 2019
Where: University of Edinburgh
MERL Contact: Arvind Raghunathan
Research Area: Optimization
Brief - Arvind Raghunathan, of MERL's Data Analytics group, will deliver a keynote titled "Embedding Perfect Structures in Process Systems" in the School of Engineering at University of Edinburgh. Abstract of the talk can be found in the link below.
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- Date: July 2, 2019
Where: Imperial College London
MERL Contact: Arvind Raghunathan
Research Area: Optimization
Brief - Arvind Raghunathan, of MERL's Data Analytics group, will deliver a seminar titled "Chordal Completions – Semidefinite Programming and Minimum Completions" in the Computational Optimisation Group at Imperial College London. Abstract of the talk can be found in the link below.
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- Date: June 10, 2019 - June 14, 2019
Where: Paris
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Optimization
Brief - MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
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- Date: April 28, 2019
Where: 3rd IAVSD Workshop on Dynamics of Road Vehicles: Connected and Automated Vehicles
MERL Contact: Stefano Di Cairano
Research Areas: Control, Optimization, Robotics
Brief - Stefano Di Cairano, Distinguished Scientist and Senior Team Leader in the Control and Dynamical Systems Group, will give an invited talk entitled: "Modularity, integration and synergy in architectures for autonomous driving" that covers recent work in the lab concerning building a modular, robust control framework for autonomous driving.
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- Date: March 3, 2019 - March 7, 2019
Where: San Diego, CA
MERL Contacts: Devesh K. Jha; Toshiaki Koike-Akino; Chungwei Lin; Kieran Parsons; Bingnan Wang; Ye Wang
Research Areas: Communications, Machine Learning, Optimization, Signal Processing
Brief - MERL researchers are presenting 4 papers at the OSA Optical Fiber Conference (OFC), which is being held in San Diego from March 3-7, 2019. Topics to be presented include recent advances in nonbinary polar codes, joint polar-coded shaping, and deep learning-based photonics circuit design. Additionally, recent work on multiset-partition distribution matching is presented as an invited talk.
OFC is the flagship conference of the OSA, and the world's most comprehensive technical conference focused on the research advances and latest technological development in optics and photonics. The event attracts more than 10000 participants each year.
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- 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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- Date: June 4, 2018
Where: Pittsburgh, Pennsylvania
MERL Contact: Arvind Raghunathan
Research Area: Optimization
Brief - 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).
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- Date: February 14, 2018
Where: Tokyo, Japan
MERL Contacts: Devesh K. Jha; Daniel N. Nikovski; Diego Romeres; William S. Yerazunis
Research Areas: Optimization, Computer Vision
Brief - 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.
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- 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: March 31, 2016
Awarded to: Andrew Knyazev
Research Areas: Control, Optimization, Dynamical Systems, Machine Learning, Data Analytics, Communications, Signal Processing
Brief - 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.
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- Date: July 9, 2013
Where: International Journal of Control
MERL Contacts: Stefano Di Cairano; Matthew Brand; Scott A. Bortoff
Research Area: Control
Brief - The article "Projection-free Parallel Quadratic Programming for Linear Model predictive Control" by Di Cairano, S., Brand, M. and Bortoff, S.A. was published in International Journal of Control.
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- Date: June 10, 2013
Where: International Conference on Automated Planning and Scheduling (ICAPS)
MERL Contact: Daniel N. Nikovski
Research Area: Optimization
Brief - The paper "Operational Planning of Thermal Generators with Factored Markov Decision Process Models" by Nikovski, D. was presented at the International Conference on Automated Planning and Scheduling (ICAPS).
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- Date: March 14, 2013
Where: SIAM Journal of Scientific Computing Brief - The article "Absolute Value Preconditioning for Symmetric Indefinite Linear Systems" by Vecharynski, E. and Knyazev, A.V. was published in SIAM Journal of Scientific Computing.
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- Date: October 1, 2012
Where: Allerton Conference on Communication, Control, and Computing
MERL Contacts: Arvind Raghunathan; Daniel N. Nikovski
Research Area: Optimization
Brief - The paper "Global Optimization of Optimal Power Flow Using a Branch & Bound Algorithm" by Gopalakrishnan, A., Raghunathan, A.U., Nikovski, D. and Biegler, L.T. was presented at the Allerton Conference on Communication, Control, and Computing.
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- Date: December 12, 2011
Where: IEEE Conference on Decision and Control and European Control Conference (CDC-ECC)
MERL Contact: Daniel N. Nikovski
Research Area: Optimization
Brief - The paper "Construction of Embedded Markov Decision Processes for Optimal Control of Non-Linear Systems with Continuous State Spaces" by Nikovski, D. and Esenther, A. was presented at the IEEE Conference on Decision and Control and European Control Conference (CDC-ECC).
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- Date: August 4, 2011
Where: North American Power Symposium (NAPS)
MERL Contact: Daniel N. Nikovski
Research Area: Optimization
Brief - The paper "State-space Approximate Dynamic Programming for Stochastic Unit Commitment" by Zhang, W. and Nikovski, D. was presented at the North American Power Symposium (NAPS).
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- Date: September 27, 2010
Where: IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (CITRES)
MERL Contact: Daniel N. Nikovski
Research Area: Optimization
Brief - The paper "Factored Markov Decision Process Models for Stochastic Unit Commitment" by Nikovski, D. and Zhang, W. was presented at the IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (CITRES).
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- Date: July 16, 2009
Where: Machine Learning
MERL Contact: Daniel N. Nikovski
Research Areas: Optmization, Data Analytics
Brief - The article "Fast Adaptive Algorithms for Abrupt Change Detection" by Nikovski, D.N. and Jain, A. was published in Machine Learning.
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- Date: June 23, 2007
Where: IEEE International Conference on Industrial Informatics
MERL Contact: Daniel N. Nikovski
Research Areas: Optmization, Data Analytics
Brief - The paper "Memory-Based Algorithms for Abrupt Change Detection in Sensor Data Streams" by Nikovski, D. and Jain, A. was presented at the IEEE International Conference on Industrial Informatics.
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- Date: September 1, 2006
Where: European Symposium on Algorithms (ESA)
MERL Contact: Matthew Brand Brief - The paper "Stochastic Shortest Paths Via Quasi-convex Maximization" by Nikolova, E., Kelner, J., Brand, M. and Mitzenmacher, M. was presented at the European Symposium on Algorithms (ESA).
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- Date: September 13, 2005
Where: International IEEE Conference on Intelligent Transportation Systems (ITSC)
MERL Contact: Daniel N. Nikovski
Research Area: Optimization
Brief - The paper "Univariate Short-Term Prediction of Road Travel Times" by Nikovski, D., Nishiuma, N., Goto, Y. and Kumazawa, H. was presented at the International IEEE Conference on Intelligent Transportation Systems (ITSC).
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- Date: July 3, 2005
Where: IEEE Antennas and Propagation Society International Symposium (AP-S International Symposium)
Research Area: Optimization
Brief - The paper "Sidelobe Minimization of Uniformly-Excited Sparse Linear Arrays using Exhaustive Search and Visual Browsing" by Leigh, D., Ryall, K., Lanning, T., Lesh, N., Miyashita, H., Hirata, K., Hara, Y. and Sakura, T. was presented at the IEEE Antennas and Propagation Society International Symposium (AP-S International Symposium).
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