CISE News & Events
Assistant Professor My T. Thai receives the prestigious DoD YIP Award
September 4th, 2009
My T. Thai, an assistant professor in the CISE Department, received the DoD YIP Award for her research project, entitled "C-WMD: Models, Complexity, and Algorithms in Complex Dynamic and Evolving Networks." The Young Investigator research Program (YIP) recognizes and supports early career development of outstanding young investigators who show exceptional ability and promise for conducting basic research. In addition to this award, Dr. Thai's research group has been supported by two other NSF grants.
Dr. Thai's research group has been working on combinatorial optimization and its application in networks, including computer networks, online social networks, and biological networks. More specifically, her group research focuses on the designs and analyses of several new models and approximation algorithms for various practical problems, mostly optimization, arising from the networking fields mentioned above. These studies have led into many beautiful and challenging questions and results in theory, which enrich other computer science and mathematical areas, such as graph theory and advance the optimization theory. Besides seeking for theoretical solutions with a provable performance bound, the group is also concerned about their practical implementation in real life. More details about her research group can be found at http://www.cise.ufl.edu/AppliedOptimization.
One of the most challenging aspects in studying this type of networks is that it is complex, dynamic, and evolving over time, yet often greatly affected by uncertain factors, which may arise in many forms, including natural or man-made interferences. This often results in dynamic changes in network characteristics, thus leading to a set of fundamental issues: How to characterize and forecast the interdependent response of network components in evolving networks with limited data? What are the quantitative benefits of using adaptive solutions via re-computing them from scratch for each change? How to design an approximation algorithm which can be adaptive to changes with a guarantee on the performance bound? This new approximation technique is very essential, yet very difficult, for adaptive recovery strategies and once found, it can provide a mathematical framework for several existing problems in dynamic networks such as routing protocols, network design and management.
Dr. Thai's research group has introduced several new problems and concepts based on their studies, such as Size Constraint Group Testing, Minimum Weight Routing Backbone, and beta-Disruptor. They have recently introduced a novel framework and efficient algorithms against several types of DoS attacks on both the Internet and Wireless Sensor Networks. They have successfully brought the alpha-beta tree into wireless networks serving as a performance analysis framework for energy consumption and transmission latency. They have shown several hardness and approximation algorithms for constructing a virtual backbone in the networks, both directional and unidirectional links, provided the first fault-tolerant scheme with a provable performance bound for transmitting data in sensor networks, and proposed the best interference-free broadcast model with a new coloring technique in 3D. Recently, they have provided the first mathematical framework to adaptively update the network community in online social networks and other complex networks, such as biological networks. They have also provided several approximation algorithms to identify the set of disruptors who play a key role in maintaining the network connectivity, thus it can serve as a fundamental framework for the design of network topology, network vulnerability and reliability.
My T. Thai received her Ph.D. degree from the University of Minnesota and joined the CISE department of the University of Florida in 2006. She is also serving as an associate editor for Optimization Letters and Journal of Combinatorial Optimization.
