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Retail Banking Fraud Analytics, Financial Risk Management, Credit Risk Modeling, Business Intelligence, Business Rule Management and Predicative Analytics.
Data Mining, Machine Learning and Neural Networks
in the areas of Financial Analysis (Risk Modeling) and Statistical Analysis (Behavioral Modeling).
2008~ Now Analytic Science Scientist
II, Fair Isaac Corporation, USA
Retail Banking Fraud Analytics.
2006~ 2007 Analytics Scientist, Zementis Inc., USA
Credit Risk Modeling: Designing, developing, and deploying
credit risk models using the latest technologies in predictive analytics, data
mining, machine learning, pattern recognition, and artificial intelligence.
Main responsibilities include: data cleaning, feature extraction, feature
selection, and algorithm development. Risk models have been successfully
deployed by financial institutes in automated underwriting loan origination
systems.
Business Rule Management: Implementing mortgage lending guidelines by
converting business rules into decision engine language based on the
interactions with external business clients; participating proof of
concepts/presale meeting; and providing post-implementation product support.
The loan pre-qualification system, ADAPA, has been successfully deployed as
multi-million-dollar-per-month wholesale/retail mortgage origination channels.
， 2003 ~ 2006 Research Fellow, M.I.N.D Institute . USA.
Project I:
Data Driven Education (DDE). Applying data mining algorithms (classification, clustering, regression), statistical analysis (significance test) to identify important information on learning process of children based on M.I.N.D. Institute unique spatial-temporal database. Field evaluating of rapid prototype products, i.e. onsite pre/post test, statistical significance analysis and corresponding technical report delivery for both R&D and marketing purpose. Sponsored in part by Seaver Institute, Los Angeles, USA. ( Publication [2] ).
， 2002 ~ 2003, Postdoctoral Fellow, Center for
Digital Security, Department of Applied Science, University of California,
Davis. USA.
Project I: Anomaly Intrusion Detection Using Machine learning Techniques.
Statistical Analysis of Program/User profiling. Sponsored in part by US Air Force Grant. ( Publication [3]).
Project II: Knowledge Discovery in World Wide Web. Internet-based
Information Retrieval (Data Mining) and Knowledge Inference (Naive
Bayesian Network).
， 1999 ~ 2002, Research Scholar, Intelligence
Machines Research Laboratory, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
Project I: Computerized Firing Range Scoring System. Development of a
computerized firing range scoring system using image processing, pattern
recognition and machine learning techniques. Sponsored by CISCO, Singapore.
( Publications [1][4][6][9][10] ).
Project II: Robust Neural Network Controller for Variable Airflow Volume
System. Design and application of robust neural network controller to handle the
increasing functionality, range of operation and robustness of the Heating,
ventilating, and air-conditioning (HVAC) system (
Publications [5][7][11][12] ).
Project III: Biomedical Model Analysis using Markov Chain Monte Carlo Method.
Hepatitis B statistical model analysis using Markov Chain Monte Carlo Method
(Gibbs Sampler) for statistical inference.，
1996 ~ 1999, Research Assistant, Department of
Electrical Engineering, Zhejiang University, PR. China.
Project I: Concrete Density and Moisture Measurement by Micro-processor-Aided
Control and Nuclear Technique. A microprocessor-based system (8051) used to
measure the density and moisture of dam concrete. Design of the
microprocessor-based system (MCS-80c32) and corresponding software development
by assembly language ( Publications [13]).
Post Doctorate. Department of Applied Science, University of
California, Davis, CA, USA.
Ph.D. School of EEE 2002, Nanyang Technology University, Singapore.
M. Eng. Department of Electrical Engineering 1999. Zhejiang University,
PR.China.
B. Eng. Department of Electrical Engineering 1996. Zhejiang University, PR.
China.
[1]. Q. Song, W. Hu and X. Yang. "An Accelerated Robust Support Vector Machine Algorithm.", Support Vector Machines: Theory and Applications, Springer, 2005, ISBN:978-3-540-24388-5.
[2]. Wenjie Hu, Mark Bodner, Edward G. Jones, Matthew R. Peterson, Gordon L. Shaw. "Dynamics of Innate Spatial-Temporal Learning Process: Data Driven Education Results Identify Universal Barriers to Learning". International Conference on Complex Systems (ICCS 2004), Boston , MA , May 2004.
[3]. Wenjie Hu, Yihua Liao and V. Rao Vemuri. "Robust Support Vector Machines for Anomaly Detection in Computer Security". The 2003 International Conference on Machine Learning and Applications (ICMLA'03). Los Angeles , California , June 2003.
[4]. Wenjie Hu and Qing Song, "An Accelerated Training Algorithm for Robust Support Vector Machine", IEEE Transaction on Circuits and Systems II: Express Briefs, Volume: 51, Issue: 5, Page(s): 234- 240, 2004.
[5]. Q. Song, W. J. Hu; T.N. Zhao. "Robust neural network controller for variable airflow volume system." Control Theory and Applications, IEE Proceedings, Volume: 150 Issue: 2, Page(s): 112 -118 Mar 2003.
[6]. Qing Song, Wenjie Hu and Wenfang Xie, "Robust Support Vector Machine for Bullet Hole Image Classification", IEEE Transaction on Systems, Man and Cybernetics Part C, Vol 32, Issue 4, pp 440-448. Nov 2002.
[7]. Q. Song and W. J. Hu, "Robust neural network controller for variable airflow volume system", American Control Conference, 2002. Proceedings of the 2002, Volume: 1, Page(s): 418 -423, 2002
[8]. Sheng Liu, Qing Song, Wenjie Hu, Aize Cao, "Disease Classification Using Support Vector Machine (SVM)." Proceedings of the 9th International Conference on Neural Information Processing (ICONIP'02), computational intelligence for the E-Age, volume 2, pp760-763, November 18-22, 2002 . Orchid Country Club , Singapore . ISBN: 981-04-7524-1.
[9]. W. J. Hu and Q. Song, "A Pre-selection Method for Training of Support Vector Machines", Proceeding of the Artificial Neural Networks in Engineering Conference (ANNIE 2001), Vol 11:15 -20. St. Louis , US . 2001.
[10]. W. J. Hu and Q. Song, "Principle Component Classifier", NIPS 2000 workshop on New Perspectives in Kernel-based Learning Methods. Dec. 2000 in Breckenridge , US .
[11]. Q. Song, W. J. Hu and Y. C. Soh, "Robust Adaptive Dead Zone Technology for Fault Diagnosis and Control of Robot Manipulators Using Neural Networks", Journal of Intelligent and Robotic Systems, Vol. 33, pp.113-137. 2001.
[12]. Q. Song, W. J. Hu and Y. C. Soh, "Robust Identification of Nonlinear Plant Using Neural Networks", Special Issue on Advances in Neural and Fuzzy Controllers, Asian Journal of Control, Vol. 3, No. 2, pp.156-162. 2001.
[13]. X. E. Lin, C. Z. Fan, and W. J. Hu, "Concrete Density and Moisture Measurement by Micro-processor-Aided Control and Nuclear Technique" Dam Observation and Geotechnical Tests, Journal of State Power Corporation of China . Vol. 23, pp24-26. 1999.
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