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 DEIM 2010 Best Paper Award Date: February 1, 2010
Awarded to:
MERL Contact: William S. Yerazunis
Research Area: Data Analytics -
AWARD SICE 2008 Best Paper Award Date: July 1, 2008
Awarded to:
MERL Contact: Daniel N. Nikovski
Research Area: Data Analytics
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News & Events
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EVENT Society for Industrial and Applied Mathematics panel for students on careers in industry Date & Time: Monday, July 10, 2017; 6:15 PM - 7:15 PM
Speaker: Andrew Knyazev and other panelists, MERL
MERL Contacts: Joseph Katz; Andrew Knyazev
Location: David Lawrence Convention Center, Pittsburgh PA
Research Areas: Electronics & Communications, Multimedia, Data Analytics, Computer Vision, Mechatronics, Algorithms, Advanced Control Systems, Computational Geometry, Computational Photography, Computational Sensing, Decision Optimization, Digital Video, Dynamical Systems, Information Security, Machine Learning, Optical Communications & Devices, Power & RF, Predictive Modeling, Speech & Audio, Wireless Communications & Signal ProcessingBrief- Andrew Knyazev accepted an invitation to represent MERL at the panel on Student Careers in Business, Industry and Government at the annual meeting of the Society for Industrial and Applied Mathematics (SIAM).
The format consists of a five minute introduction by each of the panelists covering their background and an overview of the mathematical and computational challenges at their organization. The introductions will be followed by questions from the students.
- Andrew Knyazev accepted an invitation to represent MERL at the panel on Student Careers in Business, Industry and Government at the annual meeting of the Society for Industrial and Applied Mathematics (SIAM).
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EVENT MERL to participate in Xconomy Forum on AI & Robotics Date & Time: Tuesday, March 28, 2017; 1:30 - 5:30PM
MERL Contacts: John R. Hershey; Joseph Katz; Daniel N. Nikovski; Alan Sullivan; Jay E. Thornton; Anthony Vetro; Richard C. (Dick) Waters; Jinyun Zhang
Location: Google (355 Main St., 5th Floor, Cambridge MA)
Research Areas: Multimedia, Data Analytics, Computer Vision, MechatronicsBrief- How will AI and robotics reshape the economy and create new opportunities (and challenges) across industries? Who are the hottest companies that will compete with the likes of Google, Amazon, and Uber to create the future? And what are New England innovators doing to strengthen the local cluster and help lead the national discussion?
MERL will be participating in Xconomy's third annual conference on AI and robotics in Boston to address these questions. MERL President & CEO, Dick Waters, will be on a panel discussing the status and future of self-driving vehicles. Lab members will also be on hand demonstrate and discuss recent advances AI and robotics technology.
The agenda and registration for the event can be found online: https://xconomyforum85.eventbrite.com
- How will AI and robotics reshape the economy and create new opportunities (and challenges) across industries? Who are the hottest companies that will compete with the likes of Google, Amazon, and Uber to create the future? And what are New England innovators doing to strengthen the local cluster and help lead the national discussion?
See All News & Events for Data Analytics -
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Recent Publications
- , "Attentional Network for Visual Object Detection", arXiv, January 2017.BibTeX Download PDFRead TR2017-028
- @techreport{MERL_TR2017-028,
- author = {Hara, K. and Liu, M.-Y. and Tuzel, C.O. and Farahmand, A.-M.},
- title = {Attentional Network for Visual Object Detection},
- institution = {MERL - Mitsubishi Electric Research Laboratories},
- address = {Cambridge, MA 02139},
- number = {TR2017-028},
- month = jan,
- year = 2017,
- url = {http://www.merl.com/publications/TR2017-028/}
- }
- , "Learning to Control Partial Differential Equations: Regularized Fitted Q-Iteration Approach", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC.2016.7798966, December 2016, pp. 4578-4585.
- , "An IoT System to Estimate Personal Thermal Comfort", IEEE World Forum on Internet of Things (WF- IoT), DOI: 10.1109/WF-IoT.2016.7845401, December 2016, pp. 672-677.
- , "Value-Aware Loss Function for Model Learning in Reinforcement Learning", European Workshop on Reinforcement Learning (EWRL), December 2016.
- , "On the Influence of State Selection on Mass Conservation in Dynamic Vapor Compression Cycle Models", Mathematical and Computer Modeling of Dynamical Systems, DOI: 10.1080/13873954.2017.1298625, Vol. 23, No. 3, pp. 262-283, December 2016.
- , "Dynamic State Estimation Based on Unscented Kalman Filter and Very Short-Term Load and Distributed Generation Forecasting", IEEE International Conference on Power System Technology (POWERCON), DOI: 10.1109/POWERCON.2016.7753928, September 2016.
- , "Mitigating Substation Demand Fluctuations Using Decoupled Price Schemes for Demand Response", IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), DOI: 10.1109/ISGT.2016.7781189, September 2016.
- , "Kernel Regression for the Approximation of Heat Transfer Coefficients", Gustav Lorentzen Natural Working Fluids Conference, August 2016.
- , "Attentional Network for Visual Object Detection", arXiv, January 2017.
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