Welcome to visit Dr. Chung-Shou Liao’s lab! Our research mainly focuses on designing efficient algorithms that can be used to solve difficult combinatorial optimization problems from real applications. His lab has developed approximation algorithms with theoretical analysis for well-known hard problems such as online shortest path, facility location, domination, and scheduling and packing problems. Other areas of interest include computational geometry, graph theory, and machine learning. In particular, they have also extended their study to systems biology: they have proposed graph-theoretic algorithms for global alignment between multiple biological networks and conducted comparative analysis across species. In recent years, they put more attention on dynamic and online algorithms for the fundamental problems such as data clustering and classification, as well as their applications to AI manufacturing.
|2021.05.||Our PI receives 2021 IEET Outstanding Teaching Award.|
|2021.04.||Our lab receives the funding support of the MOST Semiconductor Research Alliance Project.|
|2021.02.||Our lab organizes the 14th AAAC in Tainan, Taiwan on Oct. 22-24, 2021.|
|2021.01.||Our PI and Yamming Huang’s paper, entitled “Approximating the Canadian Traveller Problem with Online Randomization” and published in Algorithmica receives 2020 AACT Best Paper Award.|
|2020.09.||Our AI team win the Most Potential Award at the AI Workshop, NCKU, Tainan.|
|2020.07.||Our PI has been nominated by ACM as the Senior Member from 2020.|
The AI project on smart manufacturing would like to investigate practical problems and challenges derived from our recent industrial collaboration with high-tech manufacturing companies. Although there were some manufacturing process problems that can be overcome by conventional machine learning approaches, these problems, however, had easy-to-retrieve features. As the high-tech manufacturing process ” getting increasingly complicated, the “key” processes have become a serious challenge for most of the high-tech manufacturing.”We first take into consideration the lithography process in the semiconductor industry as the short-term goal to elaborate the artificial intelligence optimization applications. Apart from most advanced process control systems that used statistical measured data, we further attempt to make use of real data-driven approaches.(more details)
Modern technologies such as Global Positioning Systems (GPS) and mobile communication have contributed to the development of dynamic navigation planning based on real-time information. However, traffic conditions vary enormously and unpredictable accidents significantly affect planned routes, which increase the problem complexity, even though current navigation systems use information about road distances and speed limits to find the fastest routes. Therefore, online decision-making strategies play an important role in solving traffic congestion problems. We consider an old online route planning problem, called the Canadian Traveller Problem (CTP), which finds practical applications in designing dynamic navigation systems. We study several generalizations of the CTP and propose deterministic algorithms with theoretical competitive ratio. We also present the first polynomial time randomized algorithm that surpasses the deterministic lower bound. Recently, we consider the electric vehicle (EV) routing problem that takes into consideration of possible battery charging or swapping operations. We develop efficient algorithms which can be implemented on an online EV routing map interface (more details).
A fundamental goal of biology is to understand the cell as a system of interacting components and especially, almost every biological process is mediated by a network of molecular interactions. In particular, there has been a considerable amount of research devoted to the discovery and exploration of interactions between proteins in the last decade. Since many cellular activities are a result of protein interactions, proteins often interact with other proteins to perform their functions, and form a complex biological system, i.e., a protein-protein interaction (PPI) network. This powerful way of representing and analyzing the vast corpus of PPI data describes the interaction relationship among proteins in a cell. Furthermore, knowledge about the topology of a PPI network in one organism can yield insights about not only the networks of similar organisms, but also the function of their components. Hence comparison between protein interaction networks is becoming central to systems biology. We have collaborated with the MIT team and developed global alignment algorithms for performing comparative analysis of multiple biological networks (more details).
When the global energy crisis and related issues become critically important, more researchers focus on the energy management problems and especially, Smart Grid is one of the most popular research topics. In order to solve the technical challenges of communications between power plants and stations, power companies have to observe the real-time state of a power grid and continually monitor the whole electricity system. The PMU (phasor measurement unit) was invented and such devices can measure the electrical waves on a power grid and determine the health of the utility system. We consider the power observation problem of optimally placing PMU devices on wide-area power grids according to different objectives, while maintaining the ability to observe electricity systems (more details).
With the rapid growth of international logistics market, one of the most important research issues is designing a large-scale distribution network. The question of large-scale distribution network design is also becoming central to globalization supply chain management. In general, the location and network design problems have become more important and have been studied extensively during the last decade. In order to deal with different real-world applications in which the constraints and requirements appear in different scenarios, these problems can be formulated in various ways. We study capacitated facility location in large-scale networks and its application to distribution network design. In a distribution network, each distribution center or client has associated with a demand, and each plant or facility has a capacity that specifies the maximum service the plant can provide to its distribution centers. (more details).