Educational Background

B.S., Computer Science Southwest Texas State University 1986
M.S., Computer Science Vanderbilt University 1988
Ph.D., Computer Science Columbia University 1996

Professional Experience

Associate Professor, Computer Science, Florida Institute of Technology (2002-present); Assistant Professor (1997-2002); Visiting Assistant Professor (1995-97).

Visiting Scientist/Faculty (sabbatical), Laboratory of Computer Science, Massachusetts Institute of Technology (2002-3).

Selected Publications

• Representation learning with function call graph transformations for malware open set recognition.
  J. Jia and P. Chan
  Proc. Intl. Joint Conf. Neural Networks, to appear, 2022.
• A Machine Learning Approach to Predicting SEP Events Using Properties of Coronal Mass Ejections.
  J. Torres, L. Zhao, P. Chan, and M. Zhang
  Space Weather, 20(7), 2022.
• Learning a Neural-network-based Representation for Open Set Recognition. [supplement]
  M. Hassen and P. Chan
  Proc. SIAM Intl. Conf. Data Mining, pp. 154-162, 2020.
• Estimating Effectiveness of Twitter Messages with a Personalized Machine Learning Approach.
  X. Sun and P. Chan.
  Knowledge and Information Systems, 56(1):27-53, 2018.
• Scalable Function-Call Graph based Malware Classification.
  M. Hassen and P. Chan
  ACM Conference on Data and Applications Security and Privacy (CODASPY), pp. 239-248, 2017.
• Improving Efficiency of Maximizing Spread in the Flow Authority Model for Large Sparse Networks. [longer version]
  P. Chan and E. Ahmadzadeh
  Proc. IEEE Intl. Conf. Big Data, pp. 863-868, 2016.

Research

• Machine Learning and Data Mining
• Anomaly Detection
• Learning from imbalacned data