Investigators - Computer Science

Faculty members pursuing energy-related research, who are affiliated with the Computer Science Department (http://cs.mst.edu/). Click on the person's web site for more information. Click on an e-mail address to correspond. You may also find additional information by clicking at the left on the 'Research/Publications' category.

Bruce McMillin, http://cs.mst.edu/facultystaffandfacilities/Bruce_McMillin.html,
ff@mst.edu

Sanjay Madria, http://www.mst.edu/~cswebdb and www.mst.edu/~madrias,
madrias@mst.edu

Daniel R. Tauritz,http://cs.mst.edu/facultystaffandfacilities/Daniel_Tauritz.html,
tauritzd@mst.edu

Zhaozheng Yin, http://cs.mst.edu/facultystaffandfacilities/zhaozhengyin/,
yinz@mst.edu

Dr. Maggie Cheng: In power systems, due to natural failures and cyber attacks, bad data may appear in measurements, system models (e.g. topology errors), and parameters. The detection and removal of those bad data are the prior condition of the availability of state estimation solution. The commonly used state estimator, Weighted Least Square (WLS) algorithm, is not robust against bad data. Many papers have been published to improve the robustness of WLS methods, but they can only deal with random bad data, not the maliciously modified data, and still cannot guarantee convergence in the presence of bad data. Dr. Cheng's research involves developing new theories for the power and information network under cyber attacks, including State Estimation with missing data (due to the data removal attack or jamming attack) and with maliciously modified data, detection and identification of topology errors, and algorithms for missing data inference. The theory and algorithms developed for anomaly detection in power grids can also be applied to communication networks for network anomaly detection and diagnosis. Another research area is to develop fast solver for power system transient stability simulation by using combinatorial preconditioning.

Keywords: bad data detection, data modification attack, anomaly detection, network tomography, combinatorial preconditioning, graph sparsification

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Dr. Bruce McMillin's interests revolve around the distributed management of power and energy for transmission, distributed, and distribution energy resources. Distributed computing systems form the basis for the Cyber aspect of this management of physical resources.  As a Computer Scientist, the main thread of this research activity has been to create sound theory and practice of fault tolerance and security for distributed computing applications. His work treats these aspects as functions of the power and energy application rather than of the underlying system. This has required development of a new theory of how program correctness is understood. The approach is to provide semantics to ensure, at runtime, that a distributed program is survivable (has fault tolerance) and maintains its security, in the presence of system failures and security intrusions. These semantics form Bridge Theories to span the Cyber and Physical worlds.

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Dr. Sanjay Madria's research interest is in energy efficient computing over mobile ad hoc and sensor networks. These networks are mainly constrained by battery power and therefore, the computing, security and communication algorithms have to be energy-efficient. Dr Madria has designed test-beds and experimented with many power-aware security algorithms, power-efficient routing, energy-efficient data management and privacy preserving schemes. There are many wireless network applications such as disaster recovery, battlefield environment, moving object tracking which can benefit from such power-efficient solutions. More recently, he has worked on SCADA system security and security in cyber physical systems. More information on Dr. Madria's research can be obtained from www.mst.edu/~cswebdb.

Keywords: energy efficient algorithms, SCADA, security, sensor networks, cloud computing, smart buildings

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Dr. Daniel R. Tauritz's primary research interest is in Evolutionary computing, both the design of novel types of Evolutionary Algorithms and their application to real-world problem solving in areas such as Cyber Security (intrusion/malware detection, situational awareness in computer networks), Critical Infrastructure Protection (coevolutionary armsraces for hardening electric power transmission systems), and Automated Software Engineering (automated software testing & correction). His long-term research goal is to create self-configuring, dynamic Evolutionary Algorithms which require no parameter tuning by users and whose parameters dynamically adapt during problem solving. Such structures have the potential to autonomously regulate population dynamics via emergent behavior rather than the centralized control structures traditionally employed by Evolutionary Algorithms. More information on Dr. Tauritz’s research can be obtained from: http://web.mst.edu/~tauritzd

Keywords: cyber security, meta-heuristics, critical infrastructure protection, evolutionary computing, search based software engineering, computational intelligence

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Dr. Zhaozheng Yin's research interest is in computing technologies that are theoretically-sound and practically-applicable in civilian, military, healthcare and multimedia applications. To that end, he is particularly interested in perception, sensor fusion, learning methods that can make these technologies as realities. He has been working on single or multi-camera visual information processing for detecting, tracking, and recognizing objects. These research activities lead to algorithms and systems capable of understanding object behaviors in biomedical and natural scene images.

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