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Jianguo Liu

Title: Associate Professor

Department: Mathematics

College: College of Science

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, Cornell University, 1994
    Major: Applied Mathematics
  • MS, Cornell University, 1991
    Major: Mathematics
  • MS, Xiangtan University, Xiangtan, China, 1985
    Major: Computational Mathematics
  • BS, Xiangtan University, Xiangtan, China, 1982
    Major: Computational Mathematics

Current Scheduled Teaching

MATH 1710.200Calculus ISpring 2025
MATH 3410.001Differential Equations IFall 2024 Syllabus
MATH 3850.001Mathematical ModelingFall 2024 Syllabus

Previous Scheduled Teaching

MATH 3410.002Differential Equations ISummer 5W2 2024 Syllabus SPOT
MATH 3350.001Introduction to Numerical AnalysisSummer 5W2 2024 Syllabus SPOT
MATH 3850.001Mathematical ModelingSpring 2024 Syllabus SPOT
MATH 3850.201Mathematical ModelingSpring 2024 Syllabus SPOT
MATH 3410.001Differential Equations IFall 2023 Syllabus SPOT
MATH 3850.001Mathematical ModelingFall 2023 Syllabus SPOT
MATH 3410.002Differential Equations ISummer 5W2 2023 Syllabus
MATH 3350.001Introduction to Numerical AnalysisSummer 5W2 2023 Syllabus
MATH 3850.001Mathematical ModelingSpring 2023 Syllabus SPOT
MATH 3850.201Mathematical ModelingSpring 2023 Syllabus SPOT
MATH 5900.705Special ProblemsSpring 2023
MATH 3410.001Differential Equations IFall 2022 Syllabus SPOT
MATH 3850.001Mathematical ModelingFall 2022 Syllabus SPOT
MATH 3680.001Applied StatisticsSummer 5W2 2022 Syllabus SPOT
MATH 3410.002Differential Equations ISummer 5W2 2022 Syllabus SPOT
MATH 3850.001Mathematical ModelingSpring 2022 Syllabus SPOT
MATH 3850.201Mathematical ModelingSpring 2022 Syllabus SPOT
MATH 4900.702Special ProblemsSpring 2022
MATH 5900.706Special ProblemsSpring 2022
MATH 3850.001Mathematical ModelingFall 2021 Syllabus SPOT
MATH 5210.001Numerical AnalysisFall 2021 SPOT
MATH 3350.001Introduction to Numerical AnalysisSummer 5W2 2021 Syllabus SPOT
MATH 3850.001Mathematical ModelingSpring 2021 Syllabus SPOT
MATH 2700.009Linear Algebra and Vector GeometryFall 2020 Syllabus SPOT
MATH 3850.001Mathematical ModelingFall 2020 Syllabus SPOT
MATH 2700.003Linear Algebra and Vector GeometrySummer 5W2 2020 Syllabus SPOT
MATH 2730.002Multivariable CalculusSummer 5W2 2020 Syllabus SPOT
MATH 2730.004Multivariable CalculusSpring 2020 Syllabus
MATH 2730.201Multivariable CalculusSpring 2020 Syllabus
MATH 3850.001Mathematical ModelingFall 2019 Syllabus SPOT
MATH 5210.001Numerical AnalysisFall 2019 SPOT
MATH 3410.001Differential Equations ISummer 5W1 2019 Syllabus SPOT
MATH 2700.001Linear Algebra and Vector GeometrySummer 5W1 2019 Syllabus SPOT
MATH 3850.001Mathematical ModelingSpring 2019 Syllabus SPOT
MATH 4900.704Special ProblemsSpring 2019
MATH 3850.001Mathematical ModelingFall 2018 Syllabus SPOT
MATH 4900.708Special ProblemsFall 2018
MATH 3410.004Differential Equations ISummer 5W2 2018 Syllabus SPOT
MATH 3350.001Introduction to Numerical AnalysisSummer 5W2 2018 Syllabus SPOT
MATH 4900.702Special ProblemsSummer 5W2 2018
MATH 3850.001Mathematical ModelingSpring 2018 Syllabus SPOT
MATH 4900.703Special ProblemsSpring 2018
MATH 5900.711Special ProblemsSpring 2018
MATH 3850.001Mathematical ModelingFall 2017 Syllabus SPOT
MATH 5210.001Numerical AnalysisFall 2017 SPOT
MATH 5900.717Special ProblemsFall 2017
MATH 3410.003Differential Equations ISummer 5W2 2017 Syllabus SPOT
MATH 2730.001Multivariable CalculusSummer 5W2 2017 Syllabus SPOT
MATH 5900.702Special ProblemsSummer 5W1 2017
MATH 3350.001Introduction to Numerical AnalysisSpring 2017 Syllabus SPOT
MATH 3850.001Mathematical ModelingSpring 2017 Syllabus SPOT
MATH 5900.718Special ProblemsSpring 2017
MATH 3350.001Introduction to Numerical AnalysisFall 2016 Syllabus SPOT
MATH 3850.001Mathematical ModelingFall 2016 Syllabus SPOT
MATH 5900.717Special ProblemsFall 2016
MATH 3410.003Differential Equations ISummer 5W2 2016 Syllabus SPOT
MATH 2730.001Multivariable CalculusSummer 5W2 2016 Syllabus SPOT
MATH 3850.001Mathematical ModelingSpring 2016 Syllabus SPOT
MATH 5220.001Numerical AnalysisSpring 2016 SPOT
MATH 3410.001Differential Equations IFall 2015 Syllabus SPOT
MATH 5210.001Numerical AnalysisFall 2015 SPOT
MATH 3410.001Differential Equations ISummer 5W1 2015 Syllabus SPOT
MATH 3410.002Differential Equations ISummer 5W1 2015 Syllabus SPOT
MATH 3350.001Introduction to Numerical AnalysisSpring 2015 Syllabus
MATH 3850.001Mathematical ModelingSpring 2015 Syllabus
MATH 3350.001Introduction to Numerical AnalysisFall 2014 Syllabus
MATH 2700.001Linear Algebra and Vector GeometryFall 2014 Syllabus
MATH 2730.001Multivariable CalculusSummer 5W2 2014 Syllabus
MATH 3350.001Introduction to Numerical AnalysisSpring 2014 Syllabus
MATH 5950.718Master's ThesisSpring 2014
MATH 3850.001Mathematical ModelingSpring 2014 Syllabus
MATH 5900.718Special ProblemsSpring 2014
MATH 2100.001Functions and Modeling for Secondary Mathematics InstructionFall 2013 Syllabus
MATH 4900.713Special ProblemsFall 2013
MATH 4910.704Special ProblemsFall 2013
MATH 5900.713Special ProblemsFall 2013
MATH 6710.001Topics in Applied MathematicsFall 2013
MATH 1710.004Calculus ISummer 5W1 2013 Syllabus
MATH 4900.703Special ProblemsSummer 5W2 2013
MATH 5900.001Special ProblemsSummer 10W 2013
MATH 3350.001Introduction to Numerical AnalysisSpring 2013 Syllabus
MATH 5950.705Master's ThesisSpring 2013
MATH 5950.706Master's ThesisSpring 2013
MATH 4900.703Special ProblemsSpring 2013
MATH 4900.706Special ProblemsSpring 2013
MATH 5900.705Special ProblemsSpring 2013
MATH 5900.712Special ProblemsSpring 2013
MATH 5900.724Special ProblemsSpring 2013
MATH 1720.003Calculus IIFall 2012 Syllabus
MATH 1720.009Calculus IIFall 2012 Syllabus
MATH 6950.703Doctoral DissertationFall 2012
MATH 3350.001Introduction to Numerical AnalysisFall 2012 Syllabus
MATH 5950.702Master's ThesisFall 2012
MATH 5900.713Special ProblemsFall 2012
MATH 5910.705Special ProblemsFall 2012
MATH 1100.002AlgebraSummer 5W1 2012
MATH 3410.001Differential Equations ISummer 5W1 2012
MATH 6950.702Doctoral DissertationSpring 2012
MATH 4980.001Experimental CourseSpring 2012 Syllabus
MATH 3350.001Introduction to Numerical AnalysisSpring 2012 Syllabus
MATH 5900.712Special ProblemsSpring 2012
MATH 6950.703Doctoral DissertationFall 2011
MATH 3350.001Introduction to Numerical AnalysisFall 2011 Syllabus
MATH 6710.001Topics in Applied MathematicsFall 2011
MATH 1710.004Calculus ISummer 5W1 2011
MATH 6950.702Doctoral DissertationSpring 2011
MATH 3350.001Introduction to Numerical AnalysisSpring 2011 Syllabus
MATH 2730.005Multivariable CalculusSpring 2011 Syllabus
MATH 5900.712Special ProblemsSpring 2011
MATH 3410.001Differential Equations IFall 2010
MATH 6950.703Doctoral DissertationFall 2010
MATH 3350.001Introduction to Numerical AnalysisFall 2010
MATH 5900.764Special ProblemsFall 2010
MATH 3410.001Differential Equations ISummer 5W1 2010
MATH 3410.001Differential Equations ISpring 2010
MATH 3350.001Introduction to Numerical AnalysisSpring 2010
MATH 5900.718Special ProblemsSpring 2010
MATH 6900.714Special ProblemsSpring 2010
MATH 1720.210Calculus IIFall 2009
MATH 5900.701Special ProblemsFall 2009
MATH 3410.001Differential Equations ISummer 5W1 2009
MATH 2700.001Linear Algebra and Vector GeometrySummer 5W1 2009
MATH 1710.200Calculus ISpring 2009
MATH 4450.001Introduction to the Theory of MatricesSpring 2009
MATH 5500.001Introduction to the Theory of MatricesSpring 2009
MATH 5900.718Special ProblemsSpring 2009
MATH 1710.200Calculus IFall 2008
MATH 1710.210Calculus IFall 2008
MATH 6950.703Doctoral DissertationFall 2008
MATH 6900.726Special ProblemsFall 2008
MATH 6950.709Doctoral DissertationSummer 5W1 2008
MATH 1710.009Calculus ISpring 2008
MATH 6950.714Doctoral DissertationSpring 2008
MATH 3350.001Introduction to Numerical AnalysisSpring 2008
MATH 5900.718Special ProblemsSpring 2008
MATH 5910.702Special ProblemsSpring 2008
MATH 1710.050Calculus IFall 2007
MATH 6950.703Doctoral DissertationFall 2007
MATH 3350.001Introduction to Numerical AnalysisFall 2007
MATH 3410.001Differential Equations ISummer 5W1 2007
MATH 1680.001Elementary Probability and StatisticsSummer 5W1 2007
MATH 1710.007Calculus ISpring 2007
MATH 6950.714Doctoral DissertationSpring 2007
MATH 3350.001Introduction to Numerical AnalysisSpring 2007
MATH 1710.025Calculus IFall 2006
MATH 3350.001Introduction to Numerical AnalysisFall 2006
MATH 6900.726Special ProblemsFall 2006
MATH 1400.002College Math with CalculusSummer 5W2 2006
MATH 1680.001Elementary Probability and StatisticsSummer 5W2 2006
MATH 6900.774Special ProblemsSummer 5W2 2006
MATH 1710.009Calculus ISpring 2006
MATH 1710.025Calculus ISpring 2006
MATH 5900.718Special ProblemsSpring 2006
MATH 5910.702Special ProblemsSpring 2006
MATH 1710.003Calculus IFall 2005
MATH 1400.003College Math with CalculusFall 2005
MATH 1650.623Pre CalculusFall 2005
MATH 5900.718Special ProblemsFall 2005
MATH 6900.726Special ProblemsFall 2005
MATH 1190.001Business CalculusSummer 5W2 2005
MATH 1400.001College Math with CalculusSummer 5W2 2005
MATH 1710.022Calculus ISpring 2005
MATH 1680.007Elementary Probability and StatisticsSpring 2005
MATH 6940.718Individual ResearchSpring 2005
MATH 5900.718Special ProblemsSpring 2005
MATH 1680.006Elementary Probability and StatisticsFall 2004
MATH 6940.708Individual ResearchFall 2004
MATH 6940.723Individual ResearchFall 2004
MATH 1650.623Pre CalculusFall 2004
MATH 5900.718Special ProblemsFall 2004

Published Intellectual Contributions

    Abstracts and Proceedings

  • P. Dong and J. Liu. (2010). " Earth Observing-1 (EO-1) Hyperspectral Image Classification Using Support Vector Machine".
  • Book Chapter

  • X. Yuan, B. Giritharan, M. Abouelenien, J. Liu, and X. Yuan. (2013). "Geometric Incremental Support Vector Machine for Object Detection from Capsule Endoscopy Videos".
  • Conference Proceeding

  • Liu, J., Vyas, A., Rebello, E. (2023). A Lagrangian Approach to Loss Function Optimization on Traffic Network Regularity. IEEE.
  • Liu, J., Li, Z. (2023). Fake and Untrue News Dataset (FUND): An Expanded Dataset for Fake News Classification. IEEE.
  • Liu, J., Li, Z., Yang, J. (2022). An Undersampled Model for Automated Sleep Stage Scoring Using EEG Data. Association for Computing Machinery New York, NY, United States.
  • Liu, J., Jiang, J. (2020). Predicting Stock Market N-Days Ahead Using SVM Optimized by Selective Thresholds. ACM International Conference Proceeding Series.
  • Liu, J., Woodson, B. (2019). Deep Learning Classification for Epilepsy Detection Using a Single Channel Electroencephalography (EEG). ACM International Conference Proceeding Series.
  • Liu, J. (2018). Instance Selection in the Projected High Dimensional Feature Space for SVM.
  • Liu, J. (2017). US Financial Market Forecasting using Data Classification With Features From Global Markets.
  • Yuan, X., Abouelenien, M., Giritharan, B., Liu, J., Yuan, X. (2013). Geometric Incremental Support Vector Machine for Object Detection from Capsule Endoscopy Videos.
  • Echeverria, E., Luo, G., Liu, J., Mei, W., Pasquale, F., Colon Santanta, J., Dowben, P., Zhang, L., Kelber, J. (2013). Magneto-Resistance in thin film boron carbides. APS Meeting Abstracts.
  • Giritharan, B., Yuan, X., Liu, J., Buckles, B., Oh, J., Tang, S.J. (2008). Bleeding detection from capsule endoscopy videos. Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE. 4780--4783.
  • Liu, J., Yuan, X., Buckles, B. (2008). Breast cancer diagnosis using level-set statistics and support vector machines. Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE. 3044--3047.
  • Quintanilla, J.A., Liu, J., D'Souza, N.A., Mirshams, R.A. (2007). Integration of Engineering Concepts in Freshman Calculus. AC 2007-1878.
  • Journal Article

  • Zhang, J., Xie, S., Gonzales, S., Liu, J., Wang, X. (2020). A fast and powerful eQTL weighted method to detect genes associated with complex trait using GWAS summary data. Genetic Epidemiology. Wiley.
  • Mai, B., Liu, J. (2019). Information Security Risks Propagation and Management in Supply Chain: An Analytical Approach. Journal of Information System Security. 15 (1)
  • Liu, J. (2016). Epilepsy Detection Using EEG With Different Time Frames. 4 Science and Engineering Publishing Company.
  • Liu, J. (2015). Does model misspecification matter for hedging? A computational finance experiment based approach. The International Journal of Finance. 2 (3) World Scientific.
  • Liu, J., Bao, X., Hrovat, D.A., Borden, W.T. (2015). Theoretical Analysis of the Fragmentation of (CO)5: A Symmetry-Allowed Highly Exothermic Reaction that Follows a Stepwise Pathway.. The Journal of Organic Chemistry. 80 (23) 11788-93.
  • J. Liu, N. Danait, S. Hu, and S. Sengupta,. (2013). "A Leave-One-Feature-Out Wrapper Method for Feature Selection in Data Classification".
  • Abouelenien, M., Yuan, X., Giritharan, B., Liu, J., Tang, S. (2013). Cluster-based sampling and ensemble for bleeding detection in capsule endoscopy videos. American Journal of Science and Engineering. 2 (1) 24--32.
  • S. Fu, J. Liu and H. Pannu. (2012). "A Hybrid Anomaly Detection Framework in Cloud Computing using One-Class and Two-Class Support Vector Machines".
  • H. Pannu, J. Liu and S. Fu. (2012). "A Self-Evolving Anomaly Detection Framework for Developing Highly Dependable Utility Clouds".
  • H. Pannu, J. Liu and S. Fu. (2012). "AAD: Adaptive Anomaly Detection System for Cloud Computing Infrastructures".
  • H. Pannu, J. Liu and S. F. (2012). "AFD: Adaptive Failure Detection System for Cloud Computing Infrastructures".
  • J. Liu. (2011). " Computational Error Control in Numerical Solution of Differential Equations ".
  • P. Dong and J. Liu. (2011). " Hyperspectral Image Classification Using Support Vector Machines with an Efficient Principal Component Analysis Scheme ".
  • D. Kaown and J. Liu. (2009). "A Fast Geometric Algorithm for Finding the Minimum Distance between Two Convex Hulls".
  • B. Giritharan, X. Yuan, and J. Liu. (2009). "Incremental Classification Learning for Anomaly Detection in Medical Images".
  • J. Liu and X. Yuan. (2009). "Obscure Bleeding Detection in Endoscopy Images Using Support Vector Machines".
  • Liu, J., Yuan, X. (2009). Obscure bleeding detection in endoscopy images using support vector machines. Optimization and Engineering. 10 (2) 289--299. Springer US.
  • J. Liu, X. Yuan, and B. Buckles. (2008). "Automated Breast Cancer Diagnosis using Level-set Statistics and Support Vector Machines".
  • B. Giritharan, X. Yuan, J. Liu, B. Buckles, S. Tang, and J. Oh. (2008). "Bleeding Detection from Capsule Endoscopy Videos".
  • J. Quintanilla, N. D'Souza, J. Liu and R. Mirshams. (2007). "Integration of Engineering Concepts in Freshman Calculus".
  • Liu, J., Yuan, X. (2007). Obscure bleeding detection in endoscopy images using support vector machine. Other. 49 383. UNIVERSAL ACADEMY PRESS, INC..
  • D. Kaown and J. Liu. (2006). "Geometric Methods for Support Vector Machines".
  • Liu, J., Lei, J., Magtoto, N., Rudenja, S., Garza, M., Kelber, J. (2005). The effects of an iodine surface layer on Ru reactivity in air and during Cu electrodeposition. Journal of the Electrochemical Society. 152 (2) G115–G121. The Electrochemical Society.
  • Garza, M., Liu, J., Magtoto, N., Kelber, J. (2004). Adhesion behavior of electroless deposited Cu on Pt/Ta silicate and Pt/SiO 2. Applied Surface Science. 222 (1) 253–262. North-Holland.
  • S. Yan, J. Liu, and W. Shi. (2003). "Improving the Accuracy of Boundary Element Method for Parasitic Extraction".
  • T.F. Coleman, J. Liu, and W. Yuan. (2002). " A New Trust-region Algorithm for Equality Constrained Optimization".
  • W. Shi, J. Liu, N. Kakani, T. Yu. (2002). "A Fast Hierarchical Algorithm for 3-D Capacitance Extraction".
  • J. Liu. (2002). "An Interior Trust Region Algorithm for Nonlinear Minimization with Linear Constraints".
  • T.F. Coleman, J. Liu, and W. Yuan. (2000). " A Quasi-Newton Quadratic Penalty Method for Minimization Subject to Nonlinear Equality Constraints".
  • T.F. Coleman and J. Liu. (2000). " An Exterior Newton Method for Large-scale Convex Quadratic Programming".
  • T.F. Coleman and J. Liu. (1999). " An Interior Newton Method for Quadratic Programming".

Contracts, Grants and Sponsored Research

    Sponsored Research

  • Liu, J. (Co-Principal), Wang, X. (Co-Principal), "Novel Methodological Strategies in Genetic Discovery and Risk Prediction for Schizophrenia," sponsored by College of Science, UNT, University of North Texas, $10000 Funded. (2019 - 2019).
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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