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Romania
Citizenship:
Ph.D. degree award:
Ion
Necoara
-
UNIVERSITATEA NAȚIONALĂ DE ȘTIINȚĂ ȘI TEHNOLOGIE POLITEHNICA BUCUREȘTI
Researcher | Teaching staff
Personal public profile link.
Expertise & keywords
Convex optimization
Numerical methods
Optimal control
Machine learning
Image processing
Electrical power system
power flow
Smart grid
Projects
Publications & Patents
Entrepreneurship
Reviewer section
Modeling, Control and Optimization for Big Data Systems
Call name:
Projects for Young Research Teams - RUTE -2014 call
PN-II-RU-TE-2014-4-2459
2015
-
2017
Role in this project:
Coordinating institution:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI
Project partners:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI (RO)
Affiliation:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI (RO)
Project website:
http://acse.pub.ro/person/ion-necoara/
Abstract:
Experiments, observations and numerical simulations in many areas of science and business are currently generating terabytes of data. Analyses of the information contained in these data sets have already led to major breakthroughs in fields ranging from genomics to power grids and process industry. The availability of these massive data sets is transforming society and the way we think about information storage, retrieval and data processing.
Not only because our team has already acquired expertise on Big Data Systems, but also because of the potential for future applications, we have identified modeling, control and optimization for big data systems as the common theme for this research proposal. The central objective of this proposal is the analysis, design and implementation of data-driven mathematical methods and numerical algorithms for the analysis and optimization of Big Data Systems, as well as modeling and control challenges. While inspired by concrete cases from application ranging from data access networks, power grids to process industry, the real focus in this project will be on tackling generic problems starting from quantitative measured data collected from Big Data Systems and developing efficient numerical algorithms for solving them. We will develop novel algorithms for modeling, control and optimization of Big Data Systems, implement the new algorithms in a programming language, test them in a wide variety of applications and include them in a toolbox.
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Mathematical Engineering Tools for Network Systems: Optimization and Control
Call name:
Projects for Young Research Teams - TE-2010 call
PN-II-RU-TE-2010-0231
2010
-
2013
Role in this project:
Coordinating institution:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI
Project partners:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI (RO)
Affiliation:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI (RO)
Project website:
http://metnet.freedns.ro/
Abstract:
MATHEMATICAL ENGINEERING COULD BE DESCRIBED AS THE INTERDISCIPLINARY ENGINEERING FIELD, IN WHICH NEW APPLICATION DRIVEN CONCEPTS AND NUMERICAL ALGORITHMS ARE DEVELOPED AND IMPLEMENTED IN SOFTWARE, BASED ON INGREDIENTS FROM MATRIX THEORY, ALGEBRAIC GRAPH THEORY, GAME THEORY, SYSTEMS AND CONTROL THEORY, STATISTICS AND OPTIMIZATION. NOT ONLY BECAUSE OUR TEAM HAS ALREADY ACQUIRED EXPERTISE ON NETWORKS, BUT ALSO BECAUSE OF THE POTENTIAL FOR FUTURE APPLICATIONS, WE HAVE IDENTIFIED MATHEMATICAL ENGINEERING FOR NETWORKS AS THE COMMON THEME FOR THIS RESEARCH PROPOSAL. THE CENTRAL OBJECTIVE OF THIS PROPOSAL IS THE ANALYSIS, DESIGN AND IMPLEMENTATION OF DATA-DRIVEN MATHEMATICAL ENGINEERING METHODS AND NUMERICAL ALGORITHMS FOR THE ANALYSIS AND OPTIMIZATION OF NETWORKS, AS WELL AS NETWORK ESTIMATION AND CONTROL CHALLENGES. WHILE INSPIRED BY CONCRETE CASES FROM APPLICATION AREAS RANGING FROM DATA ACCESS NETWORKS, TRAFFIC NETWORKS TO PROCESS INDUSTRY, THE REAL FOCUS OF THE RESEARCH IN THIS PROJECT WILL BE ON TACKLING GENERIC NETWORK PROBLEMS STARTING FROM QUANTITATIVE MEASURED DATA COLLECTED FROM NETWORK NODES AND LINKS AND DEVELOPING MATHEMATICAL ENGINEERING ALGORITHMS TO SOLVE THEM. WE WILL DEVELOP DISTRIBUTED, MODEL-BASED METHODS FOR OPTIMIZATION, ESTIMATION AND CONTROL OVER NETWORKS, IMPLEMENT THE NEW ALGORITHMS EFFICIENTLY IN A PROGRAMMING LANGUAGE, TEST THEM IN A WIDE VARIETY OF APPLICATIONS AND INCLUDE THEM IN A TOOLBOX. THE RESEARCH OBJECTIVES OF THIS PROPOSAL CAN BE GROUPED IN TWO CLASSES: (I) NETWORKS OPTIMIZATION PROBLEMS; (II) MODEL-BASED ESTIMATION AND CONTROL PROBLEMS. IN BOTH CLASSES, WE WILL BE DEVELOPING OR IMPROVING ON CONCEPTS AND ALGORITHMS FOR DEALING WITH HETEROGENEOUS DATA SOURCES, AND DEPLOY THE RESULTS IN SEVERAL APPLICATION DOMAINS: TELECOMMUNICATION DATA ACCESS NETWORK OPTIMIZATION, DISTRIBUTED CONTROL OF INTERCONNECTED CHEMICAL PLANTS IN THE PROCESS INDUSTRY AND URBAN TRAFFIC CONTROL.
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Call name:
Premierea obtinerii atestatului de abilitare - Competitia 2015
PN-II-RU-ABIL-2015-2-0049
2015
-
Role in this project:
Coordinating institution:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI
Project partners:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI (RO)
Affiliation:
UNIVERSITATEA POLITEHNICA DIN BUCURESTI (RO)
Project website:
Abstract:
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FILE DESCRIPTION
DOCUMENT
List of research grants as project coordinator
Download (112.08 kb) 10/05/2016
List of research grants as partner team leader
Download (112.08 kb) 10/05/2016
List of research grants as project coordinator or partner team leader
Significant R&D projects for enterprises, as project manager
R&D activities in enterprises
Peer-review activity for international programs/projects
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