I'm
Dr. Xiaoguang Wang
Benjamin
- Practicing +15 years
- Address 385 Jerseyville Rd W, Ancaster, ON L9G 3L5, Canada
- E-mail xwang@dimensioninstitute.org
- Phone +1 902 9890635
I work at UYUN. I did my Ph.D. in Computer Science at University of Ottawa under Professor Stan Matwin. I was co-advised by Professor Nathalie Japkowicz. My research interests include machine learning and applications of AI, as well as other use cases.
Download my storyWork Experience
Conducted research and stayed abreast of the latest advancements in AI and AIOps, providing thought leadership and strategic guidance to executive leadership.
Led and contributed to research projects focused on AI platform-PAI.
Developed novel machine learning algorithms and models, resulting in applications of Alibaba AI brain.
Developed predictive models using machine learning algorithms to identify patterns and trends in patient data, leading to improved diagnostic accuracy and personalized treatment strategies.
Professional Skills
Education
Publications
For a complete list, see Google Scholar.
ARTICLES PUBLISHED OR ACCEPTED IN REFEREED JOURNALS
- Automatic Target Recognition Using Multiple-Aspect Sonar Images. Journal of Artificial Intelligence and Soft Computing Research. 12 pages. (2014). Wang, X., Liu, X., Japkowicz, N., & Matwin, S.
- Boosting support vector machines for imbalanced data sets. Knowl. Inf. Syst. 25(1): 1-20 (2010). Wang, X., Japkowicz, N.
- Meta-MapReduce for Scalable Data Mining. Journal of Big Data. 12 pages. (2015) Wang, X., Japkowicz, N. Liu, X., Wang, X., Matwin, S., & Japkowicz, N.
PAPERS IN REFEREED CONFERENCE PROCEEDINGS
- A Multi-View Two-level Classification Method for Generalized Multi-instance Problems.. Wang, X., Liu, X., Matwin, S. & Japkowicz, N., Guo, H. 2014 IEEE International Conference on Big Data, 104-111.
- Vessel Route Anomaly Detection with Hadoop MapReduce.. Wang, X., Liu, X., Bo Liu, Erico N. de Souza & Matwin, S. 2014 IEEE International Conference on Big Data, 25-30.
- Applying Instance-weighted Support Vector Machines to Class Imbalanced Datasets.. Wang, X., Liu, X., Matwin, S. & Japkowicz, N. 2014 IEEE International Conference on Big Data, 112-118.
- A Distributed Instance-weighted SVM Algorithm on Large-scale Imbalanced Datasets.. Wang, X., Liu, X. & Matwin, S. 2014 IEEE International Conference on Big Data, 45-51.
- Automatic Target Recognition using multiple-aspect sonar images.. Wang, X., Liu, X., Japkowicz, N., Matwin, S. & Nguyen B. IEEE Congress on Evolutionary Computation 2014: 2330-2337.
- Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning.. Wang, X., Liu, X., Japkowicz, N., & Matwin, S. 2013 IEEE International Conference on Data Mining (ICDM), 9 pages.
- Ensemble of Multiple Kernel SVM Classifiers.. Wang, X., Liu, X., Japkowicz, N., & Matwin, S. Canadian Conference on AI 2014: 239-250.
- Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets.. Wang, X., Matwin, S., Japkowicz, N., & Liu, X. In Advances in Artificial Intelligence (pp. 174-186). Springer Berlin Heidelberg.
- Meta-learning for Large Scale Machine Learning with MapReduce.. Wang, X., Matwin, S., Japkowicz, N., & Liu, X. 2013 IEEE International Conference on Big Data, 6 pages.
- An Ensemble Method Based on AdaBoost and Meta-Learning.. Liu, X., Wang, X., Japkowicz, N., & Matwin, S. In Advances in Artificial Intelligence (pp.278-285). Springer Berlin Heidelberg.
- Using SVM with Adaptively Asymmetric Misclassification Costs for Mine-Like Objects Detection.. Wang, X., Shao, H., Japkowicz, N., Matwin, S., Liu, X., Bourque, A., & Nguyen, B. (2012). In Machine Learning and Applications (ICMLA), 2012 11th International Conference on (Vol. 2, pp. 78-82). IEEE.
- Boosting Support Vector Machines for Imbalanced Data Sets. . Wang, X., Japkowicz, N. (2012). ISMIS 2008: 38-47 (The Best Paper Award).
BOOK CHAPTERS
- Automated Mine-like Objects Recognition Using Instance-weighted Boosting SVM on Imbalanced Multiple Instance Dataset. Wang, X., Liu, X., Japkowicz, N., & Matwin, S. (2015). Recent Advances in Computational Intelligence in Defense and Security. Submitted, 30 pages.
Patents
- Training method, credit estimation method and the device of credit evaluation model. Patent number : CN107301577A
- Model training method, sample balancing method, model training device, sample balancing device and personal credit scoring system Patent number : CN106909981B
- Model data updating method, device and system Patent number : CN107229966B
- Model training method, apparatus and system and sample set optimization method, device Patent number : CN106934413A
- A kind of Risk Forecast Method and equipment Patent number : CN106779272A
- Method and device for determining user intention based on user voice information Patent number : CN108205525B
- The method and device that the belonging kinds of data are predicted Patent number : CN107203774A
- The sorting technique and system of data Patent number : CN106934410A
- A kind of method and device for optimizing user credit model modeling process Patent number : CN106997484A
- A kind of Feature Selection method and device Patent number : CN107169571A
- Feature engineering strategy determination method and device Patent number : CN107168965B
- User characteristics sorting technique, user credit appraisal procedure and the device of user credit model Patent number : CN106997472A
- A kind of method and device for screening user characteristics Patent number : CN106874286A
- A kind of information extracting method and device Patent number : CN107133207A
- User group classification method and device Patent number : CN106897282B
- User credit model establishing method and device Patent number : CN107203916B
- object grouping method, model training method and device Patent number : CN106874925A
- Intelligent operation and maintenance system based on data middling platform technology Patent number : CN112182077B
- Intelligent operation and maintenance framework system based on AIOps Patent number : CN112181960B
- Three-dimensional microscopic road network generation method capable of realizing real-time interaction Patent number : CN111535099B
- Method and system for adaptively calculating IT intelligent operation and maintenance health index Patent number : CN113360358A
- Fault root cause positioning method and system based on multidimensional data map Patent number : CN113360722A
- Semi-supervised man-machine combined operation and maintenance fault library generation method and system Patent number : CN112783865A
- Disk capacity prediction method for identifying manual cleaning behavior based on second-order difference method Patent number : CN113157204B
Academic Activity
Awards
References
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Stan Matwin Professor & Director, Institute for Big Data Analytics -
Nathalie Japkowicz Professor and Department Chair, Computer Science -
Justin Zhan Geier Endowed Professor and Department Head
My Interests
My passion is butterflies, I am collecting butterflies since childhood, also I love to swim and to jump from springboard. I love to play tennis on Thursdays and sing some songs.
- Teeths
- Tennis
- Spa
- Burgers
- Jumping from springboard
- Swimming