Dr. Yixin Chen
Professor and Graduate Program Coordinator
207 Weir Hall
Dr. Yixin Chen, Professor, joined the faculty in 2006 after three years on the faculty of the University of New Orleans. He has a PhD in computer science from Pennsylvania State University and a PhD in electrical engineering from the University of Wyoming.
Yixin came to University of Mississippi in August 2006 as a displaced New Orleans resident after Hurricane Katrina. He was an Assistant Professor of CS at University of New Orleans from 2003 to 2006.
The School of Engineering named Dr. Chen its Outstanding Faculty Member in 2012.
While on sabbatical, Yixin was a Visiting Scientist at St. Jude Children’s Research Hospital from June 2013-December 2013. He established a valuable collaboration with the Department of Computational Biology during that time.
You can view Dr. Chen’s homepage here.
Chen’s research focuses on the design, analysis, implementation, and applications of machine learning algorithms. He is especially interested in solving real world problems arising from biomedicine and life science. He has worked on various projects on brain-computer interfaces, knowledge discovery in taxonomic research, content-based image retrieval, automatic image annotation, and control of robotic manipulators. Chen is working with Dr. Dawn Wilkins is working on an NSF EPSCoR project to investigate the development of a data provenance system for scientific data. Chen is serving as an Associate Editor of the journal Pattern Recognition. A complete list of Dr. Chen’s publications and research can be found here.
At the graduate level, Chen teaches courses on algorithm analysis, machine learning, image processing, computer vision, artificial intelligence, mobile robotics, and randomized algorithms.
- CSci 345 Information Storage and Retrieval
- CSci 390 Special Topic: Robotics
- CSci 433 Algorithms and Data Structure Analysis
- CSci 531 Artificial Intelligence
- CSci 533 Analysis of Algorithms
- CSci 581 Special Topic: Computer Vision
- CSci 581 Special Topic: iOS Programming with Swift
- CSci 582 Special Topic: Image Processing
- CSci 632 Machine Learning
- ENGR 692 Special Topic: Randomized Algorithms
- ENGR 692 Special Topic: Pattern Recognition
- Yixin Chen and John E. McInroy, “Identification and Decoupling Control of Flexure Jointed Hexapods,” Proc. IEEE International Conference on Robotics and Automation (IRCA), pp. 1936-1941, San Francisco, CA, April 2000.
- Yixin Chen and John E. McInroy, “Estimating Symmetric, Positive Definite Matrices in Robotic Control,” Proc. IEEE International Conference on Robotics and Automation (ICRA), pp. 4269-4274, Washington D.C., May 2002.
- Yixin Chen and James Z. Wang, “Image Categorization by Learning and Reasoning with Regions,” Journal of Machine Learning Research, vol. 5, pp. 913-939, 2004.
- Yixin Chen, Henry L. Bart, Jr., Shuqing Huang, and Huimin Chen, “A Computational Framework for Taxonomic Research: Diagnosing Body Shape within Fish Species Complexes,” The Fifth IEEE International Conference on Data Mining (ICDM), pp. 593-596, Houston, Texas, November 2005.
- Yixin Chen, Ya Zhang, and Xiang Ji, “Size Regularized Cut for Data Clustering,” Advances in Neural Information Processing Systems (NIPS), 18, MIT Press, Cambridge, pp. 211-218, 2006.
- Yixin Chen, Jinbo Bi, and James Z. Wang, “MILES: Multiple-Instance Learning via Embedded Instance Selection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 12, pp. 1931-1947, 2006.
- Yixin Chen, Henry L. Bart, Jr., Xin Dang, and Hanxiang Peng, “Depth-Based Novelty Detection and its Application to Taxonomic Research,” The Seventh IEEE International Conference on Data Mining (ICDM), pp. 113-122, Omaha, Nebraska, October 2007.
- James C. Church, Yixin Chen, and Steven V. Rice, “A Spatial Median Filter for Noise Removal in Digital Images,” Proc. of the IEEE Southeast Conference (SECON), pp. 618-623, Huntsville, Alabama, April 2008.
- Yixin Chen, Xin Dang, Hanxiang Peng, and Henry L. Bart, Jr., “Outlier Detection with the Kernelized Spatial Depth Function,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 2, pp. 288-305, 2009.
- Chad Vicknair, Michael Macias, Zhendong Zhao, Xiaofei Nan, Yixin Chen, and Dawn Wilkins, “A Comparision of a Graph Database and a Relational Database: A Data Provenance Perspective,” Proc. of the ACM Southeast Conference (ACMSE), pp. –, Oxford, Mississippi, April 2010.
- Z. Zhao, G. Fu, S. Liu, K. M. Elokely, R. Doerksen, Y. Chen, D. Wilkins, “Drug Activity Prediction Using Multi-Instance Learning via Joint Instance and Feature Selection,” The Tenth Annual Conference of the MidSouth Computational Biology and Bioinformatics Society, pp. 60, Columbia, MO, April 2013.
- S. Liu, S. Dissanayake, S. Patel, X. Dang, T. Mlsna, Y. Chen and D. Wilkins, “Learning Accurate and Interpretable Models Based on Regularized Random Forests Regression,” BMC Systems Biology, vol. 8(Suppl 3):S5, 9 pages, 2014.
- Kai Yu, Xin Dang, Yixin Chen, “Robustness of the Affine Equivariant Scatter Estimator Based on the Spatial Rank Covariance Matrix,” Communications in Statistics – Theory and Methods, vol. 44, no. 5, pp. 914-932, 2015.
- P. Gong, X. Nan, N.D. Barker, R.E. Boyd, Y. Chen, D.E. Wilkins, D.R. Johnson, B.C. Suedel, and E.J. Perkins, “Predicting Chemical Bioavailability Using Microarray Gene Expression Data and Regression Modeling: A Tale of Three Explosive Compuunds,” BMC Genomics, vol. 17, no. 205, 10 pages, 2016.
- S. Zhang, Y. Mo, T. Ghoshal, D. Wilkins, Y. Chen, Y. Zhou, ”Novel Gene Selection Method for Breast Cancer Intrinsic Subtypes from Two Large Cohort Study,” 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2198-2203, 2017.
- S. Zhang, J. Wang, T. Ghoshal, D. Wilkins, Y. Mo, Y. Chen, Y. Zhou, `”lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis,” Genes, 9(2), 65; 2018.