Quang M. Nguyen (Nguyễn Minh Quang)

Hi, I'm a PhD student at Computer Science Department, University of Pittsburgh. My PhD advisor is Dr. Milos Hauskrecht.

Before going to the US to join PITT I lived in Moscow, Russia and got my BS/MS degree from Department of Computional Mathematics and Cybernetics, Lomonosov Moscow State University.

Here is my CV

CONTACT INFORMATION

Computer Science Department, University of Pittsburgh

210 S Bouquet St, Office 5406, Pittsburgh, PA 15213

Phone: (+1) 412-482-0545

Email: quang (at) cs (dot) pit (dot) edu

RESEARCH INTERESTS

Machine learning and data mining

• Leaning from multiple annotators
• Learning from auxiliary information

Decision support in biomedical informatics

• Application of machine learning and data mining techniques for disease diagnosis
• Visualization of medical data to support decision making in medicine

RESEARCH PROJECTS

These projects are sponsored by National Institute of Health (NIH)

Learning from multiple annotators

• Developed methods to learn a consensus model from multiple annotators by modeling differences in knowledge, reliability and bias

Learning from auxiliary information

• Developed a framework to learn better classification models with smaller sample complexity by incorporating auxiliary probabilistic information

Outlier detection in large clinical databases

• Designed and developed a web-based system to visualize medical data and support disease diagnosis. The system has been used by physicians from University of Pittsburgh Medical Center.

PUBLICATIONS

Q. Nguyen, H. Valizadegan, and M. Hauskrecht. Learning from multiple experts. Twenty-sixth AAAI Conference on Artificial Intelligence (AAAI’12), Toronto, Canada. Submitted, under review

Q. Nguyen, H. Valizadegan, and M. Hauskrecht. Learning classification with auxiliary probabilistic information. IEEE International Conference on Data Mining (ICDM’11), Vancouver, Canada, December 2011 (regular paper, acceptance rate: 101/822 = 12%)

Q. Nguyen, H. Valizadegan, and M. Hauskrecht. Sample-efficient learning with auxiliary class-label information. Annual American Medical Informatics Association Symposium (AMIA’11), October 2011

Q. Nguyen, I. Mashechkin. Design and implementation of log consolidation system. BS/MS thesis, Department of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, June 2006

PRESENTATIONS

Learning classification with auxiliary probabilistic information, IEEE International Conference on Data Mining (ICDM’11), Vancouver, Canada, December 2011

Sample-efficient learning with auxiliary class-label information, Annual American Medical Informatics Association Symposium (AMIA’11), October 2011

Kernel methods, CS Departments, University of Pittsburgh, November 2011

TEACHING

CS007 - Introduction to Computer Programming (Fall 2009)

CS401 - Intermediate Programming Using Java (Summer 2008, Spring 2009)

CS445 - Data Structures (Spring 2008, Summer 2009)

CS1530 - Software Engineering (Fall 2008)

CS1538 - Introduction to Simulation (Fall 2007)

CS1550 - Introduction to Operating Systems (Summer 2008)

CS1621 - Structure of Programming Languages (Fall 2007)

CS1622 - Introduction to Compiler Design (Fall 2008)