Welcome to the homepage of Xiong Wang. I'm currently a 3nd year Ph.D student at the University of Sydney. My supervisor is Dr. Andy Dong. My research deals with computational linguistics in design. The aim is to develop a SVM-based computational linguistic system to understand the appraisal of design processes and the designed work. The outcome of the research will be a machine-learning based computational linguistic system which can ascertain the sentiments expressed by designers toward the design process and the designed work. This research may impact the way that emotions are studied in design research, given an object-relations perspective on emotions. My research interests range from the area of statistical machine learning (SML) to computational linguistics.

I always hold the belief that life is a process of continuous learning in various environments. It is with this belief that I have come to the University of Sydney to study towards PhD degree. The topic of my PhD research is A Machine Learning System for Understanding Appraisal in Design Documents. For this project, knowledge of Statistics Machine Learning(SML) is essential. Knowledge in Computer Science, Neural Networks and Optimization techniques, is extra credit.

Previously, I have had 4-year undergraduate study in Computer Science, 1.5 year working as a  software engineer (in an IT company), 1 year working as a research assistant (research associate equivalent, in the University of Queensland) and 2-year master study in the same area (awarded with the ITEE Postgraduate Scholarship in the University of Queensland). All of these working or studying experience well suit my current research and will definitely benefit my study in future. Research is a path into inquiry and to understand why things happen and the philosophy beneath. To this end, we need prepared knowledge and skills to speed up the process, perseverance to go through the period of drought, and faith to oneself and the work we are doing. With my solid background in the area and outstanding research conditions provided by KCDC, I am confident to fulfill my PhD research with a full success.  

• Statistics Machine Learning

        - Kernels methods, optimization and exponential families

        - Rapid stochastic gradient methods

        - Global convergence analysis of learning algorithms

• Design Computing  

• Development of appraisal system for design teams' work

EDUCATION

• University of Sydney, NSW, Australia (4/2005 - Present)          

       Ph.D. in Architecture, Expected graduation: 2008

• University of Queensland, Queensland, Australia (11/2001 - 03/2004)

        M.Phil. in Statistics Machine Learning (July, 2004), School of ITEE, University of Queensland, Australia.

• SiChuan University, Sichuan, China (09/1996 - 07/2000)          

        B.Eng. in Computer Science (July, 2000), Dept. of Computer Science, Sichuan University, China

RESEARCH EXPERIENCE

• Computational Methods for the Social Accounting of Teamwork, Australian Research Council (ARC) Discovery Project DP0557346, Key Centre of Design Computing and Cognition, University of Sydney, Sydney.

• SimplerSVM QP Optimizer,SML Program, NICTA Canberra Research Lab, 05/2005~07/2005

    -This project is about a fast iterative support vector training algorithm for a large variety of different formulations, with Dr. Vishy Vishwanathan, Dr. Nic Schraudolph, and Dr. Alex Smola

• Improving the Segmentation of MR Images with Recursive Bias Field Correction via an ECM algorithm, ARC Centre for Complex Systems, 10/2004~02/2005

• Applying Incremental Machine Learning method to predict the mortality rate of Intensive Care Unit(ICU) patients, School of ITEE, Univ. of QLD, 04/2004~02/2005