Data Analytics
Predictive analytics, decision analytics, modeling, simulation, and optimization.
Data Analytics technologies aim to improve the performance of devices, systems, and business processes by means of collecting data, constructing predictive models from that data, and making improved decisions based on the constructed models. The Data Analytics group at MERL has been working on both predictive and decision analytics, as well as supporting fields such as signal processing, numerical methods, and information systems infrastructure.
The focus of the group is on innovative high-performance algorithms that can be applied to various product lines of Mitsubishi Electric, including electrical power systems, various transportation systems (trains, elevators, car navigation), heating, ventilation, and air conditioning (HVAC) systems and solutions, and factory automation. The application of these algorithms minimizes costs, maximizes profits, increases reliability, improves energy efficiency, and reduces environmental impact of products.
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Research Areas
Predictive Modeling
Research on predictive analytics, supported by advances in the field of statistical machine learning, aims to create accurate data-driven models of electromechanical and thermodynamical systems, as well as models of complex natural and man-made phenomena, such as road traffic and demand for electrical power.
Decision Optimization
Numerical methods for fast solution of network problems find application in the analysis of electrical power systems and Smart Grids that include renewable power sources with intermittent output, as well as highly variable loads such as electrical vehicles. Many problems in transportation systems, such as train operation optimization, group elevator scheduling, and route guidance for car navigation, can be reduced to planning and optimization problems. Energy consumption in buildings can be minimized by solving sequential decision and optimization problems, both at the level of individual air conditioning devices, as well as at the level of entire buildings.
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Researchers
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Awards
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AWARD Best Student Paper Award at the International Conference on Data Mining Date: November 30, 2017
Awarded to:
MERL Contact: Daniel Nikovski
Research Areas: Data Analytics, Predictive ModelingBrief- 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.
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AWARD DEIM 2010 Best Paper Award Date: February 1, 2010
Awarded to:
MERL Contact: William Yerazunis
Research Area: Data Analytics -
AWARD SICE 2008 Best Paper Award Date: July 1, 2008
Awarded to:
MERL Contact: Daniel Nikovski
Research Area: Data Analytics
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News & Events
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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: Data Analytics, Decision OptimizationBrief- 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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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
Research Areas: Multimedia, Data AnalyticsBrief- 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.
- MERL researcher Mouhacine Benosman has been appointed as a member of the Editorial Board of the International Journal of Adaptive Control and Signal Processing.
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Recent Publications
- , "Semi-Supervised Transfer Learning Using Marginal Predictors", IEEE Data Science Workshop, June 6, 2018.
- , "LDL^T Direction in interior point method for semidefinite programming", SIAM Journal on Optimization, DOI: 10.1137/16M1105888, Vol. 28, No. 1, pp. 693-734, March 2018.
- , "Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control," Tech. Rep. TR2018-028, arXiv, February 2018.BibTeX Download PDFRead TR2018-028
- @techreport{MERL_TR2018-028,
- author = {Pan, Y. and Farahmand, A.-M. and White, M. and Nabi, S. and Grover, P. and Nikovski, D.N.},
- title = {Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control},
- institution = {MERL - Mitsubishi Electric Research Laboratories},
- address = {Cambridge, MA 02139},
- number = {TR2018-028},
- month = feb,
- year = 2018,
- url = {http://www.merl.com/publications/TR2018-028/}
- }
- , Fast Market Clearing Algorithms, December 2017.
- , "Three-Level Co-optimization Model for Generation Scheduling of Integrated Energy and Regulation Market", IEEE Innovative Smart Grid Technologies Conference , December 2017.
- , "Random Projection Filter Bank for Time Series Data", Advances in Neural Information Processing Systems (NIPS), December 2017.
- , "Learning to Regulate Rolling Ball Motion", IEEE Symposium on Computational Intelligence in Engineering Solutions, November 2017.
- , "Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining", International Conference on Data Mining 2017, November 2017.
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