https://engineering.wustl.edu/Profiles/Pages/Weixiong-Zhang.aspx45Weixiong Zhang<img alt="Weixiong Zhang" src="/Profiles/PublishingImages/Zang_Weixiong.jpg?RenditionID=6" style="BORDER:0px solid;" />ProfessorWeixiong Zhang - Computer Science & Engineering - ​Applies computational methods to understand Alzheimer’s disease & psoriasis​​​PhD, University of California–Los Angeles, 1994<br/>BS, Tsinghua University, 1984 <div> <br/> </div><p>  <a href="https://scholar.google.com/citations?user=vuKTnnsAAAAJ&hl=en&oi=ao"><img src="/Profiles/PublishingImages/gscholar.png" alt="" style="margin: 0px 0px -5px;"/> Google Scholar</a></p>http://www.cse.wustl.edu/~zhang/<p>​​Professor</p><h3>Research​</h3><p>In biology and medical science areas, Weixiong Zhang is interested in developing computational methods for complex problems appeared in molecular biology, genetics, systems biology and genomics. He is particularly interested in applying computational methods to the understanding of complex human diseases, including Alzheimer’s disease and psoriasis, and environmental stress response in agri-economically important plants, such as rice and cassava. In recent years, he has been focusing on three lines of biological research: gene regulation through small noncoding RNAs, transcriptome analysis and genotype-phenotype association.</p> <br/>In Artificial Intelligence, his main focuses are heuristic search, combinatorial optimization and planning. He has made several important contributions to these areas, documented in many papers in top journals (e.g. 11 in Artificial Intelligence) and conferences. Among these important results are two worthwhile to mention. First, he showed that linear-space heuristic search algorithms, including depth-first search and iterative deepening, are asymptotically optimal, so that they are the algorithms of choice for large problems. Moreover, this result also resolved an anomaly of look-ahead search, which has been widely adopted as a model of real-time problem solving. Second, he analyzed phase transitions in combinatorial optimization problems, e.g., the Traveling Salesman Problem and the maximum Satisifiability, showing their easy-difficulty phase transitions, which are in sharp contrast to the easy-hard-easy phase transitions in decision problems. Furthermore, he also developed effective approximation algorithms that exploit phase transitions. In recent years, Professor Zhang has been focusing on Satisifiability-based planning. His joint work with Ruoyun Huang and Yixin Chen on planning won the Outstanding Paper Award of the 2010 National Conference on AI.​<h3>Biography</h3><p>After spending several years at Information Sciences Institute, University of Southern California, Professor Zhang joined the faculty at Washington University in St. Louis in 2000. He currently has a joint appointment in the Genetics Department, School of Medicine.</p><div class="ExternalClassD80094F63D6B43498DD16405547C1A1B">Professor Zhang is currently Deputy Editor of <em>PLoS Computational Biology</em>, a leading journal in the field of computational biology, Associate Editor of <em>Artificial Intelligence</em>, the premier journal of the field of artificial intelligence, and Associate Editor of <em>AI Communication: The European Journal on Artificial Intelligence</em>.</div><div class="ExternalClassD80094F63D6B43498DD16405547C1A1B"><br/></div><div class="ExternalClassD80094F63D6B43498DD16405547C1A1B">Professor Zhang’s research is multi-disciplinary and spans across two fields, Computational Biology and Artificial Intelligence.</div><img alt="" src="/Profiles/ResearchImages/shield_red.jpg?RenditionID=13" style="BORDER:0px solid;" /><p>​314-935-8788<br/><a href="mailto:weixiong.zhang@wustl.edu">weixiong.zhang@wustl.edu</a><br/>Jolley Hall, Room 530​</p><ul><li>​<a href="/news/Pages/Big-data-allows-computer-engineers-to-find-genetic-clues-in-humans.aspx" style="background-color: #ffffff;">Big data allows computer engineers to find genetic clues in humans</a><br/></li></ul>