Curriculum Vitae

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Education

  • Ph.D., Mathematics 2017
    University of Tulsa Tulsa, OK
  • M.S., Mathematics 2013
    University of Tulsa Tulsa, OK
  • B.S., Mathematics 2013
    University of Tulsa Tulsa, OK
  • B.S., Geology 2013
    University of Tulsa Tulsa, OK

Professional Experience

  • Postdoctoral fellow 2018-
    University of Pennsylvania Philadelphia, PA
  • Graduate intern 2016-2017
    Laureate Institute for Brain Research Tulsa, OK
  • Graduate research assistant 2015-2017
    University of Tulsa Tulsa, OK
  • Undergraduate research assistant 2012-2013
    University of Tulsa Tulsa, OK

Select Software Packages

  • npdr: Select features with nearest-neighbor concepts (2019)      
  • pmlb: Penn Machine Learning Benchmarks (PMLB) (2020)      
  • pmlb-r: an R interface to PMLB (2020)      
  • privateEC: Differential privacy for machine learning (2017)      
  • stir: ReliefF on steroid (2018)      
  • treeheatr: Heatmap-integrated decision tree visualizations (2020)      

Courses and Workshops

  • On visualization: Take a sad chart and make it better, R Ladies Philly, Dec 8, 2020      
  • Fundamentals of AI guest lecturer, University of Pennsylvania, Mar 30, 2020      
  • Machine learning workshop, R Ladies Philly, Dec 2, 2019      
  • Introduction to R seminar, University of Tulsa, Aug 25, 2017  
  • Precalculus instructor, University of Tulsa, Jan 11, 2016  
  • Calculus I & II teaching assistant, University of Tulsa, Jan 13, 2014  
  • Natural science tutors, University of Tulsa, Feb 7, 2011  

Presentations

  • treeheatr: an R package for interpretable decision tree visualizations. R/Medicine Virtual Conference, Aug 28, 2020      
  • Analysis of ISCB honorees and keynotes reveals disparities. Conference on Intelligent Systems for Molecular Biology, Jun 30, 2020      
  • Scaling tree-based automated machine learning to biomedical big data with a feature set selector. Genetic and evolutionary computation conference, Jun 10, 2020      
  • Multilocus risk scores: rethinking genetic risk scores to account for epistasis. International Joint Conference on Biomedical Engineering Systems and Technologies, Feb 25, 2020      
  • Multilocus risk scores. Rocky Mountain Bioinformatics Conference, Dec 6, 2019      
  • Detect network interactions and control for confounders and multiple testing. Rocky Mountain Bioinformatics Conference, Dec 6, 2019      
  • Multilocus risk scores. Penn Genetics Retreat, Sep 4, 2019      
  • TPOT: Overview and live demonstration. Clinical Research Informatics Core, University of Pennsylvania, Mar 13, 2019      
  • STIR feature selection. Pacific Symposium on Biocomputing, Jan 5, 2019      
  • Scalable automated machine learning. AI Therapeutics, Dec 21, 2018      
  • Statistical Inference Relief (STIR) feature selection. Mid-Atlantic Bioinformatics Conference, Oct 29, 2018      
  • Transcriptomics of Brain Age Gap Estimate. Society of Biological Psychiatry Meeting, May 11, 2018      
  • Deciphering interdependent immunologic biomarkers of lupus. DBEI and CCEB Research Day, University of Pennsylvania, Apr 10, 2018      
  • Integrative network analysis for major depressive disorder. Organization for Human Brain Mapping Meeting, Jun 28, 2017      
  • Optimized random forest classification accuracy. International Conference on Integral Methods in Science and Engineering, Jul 25, 2016      
  • Structural identifiability issues of epidemiological models. International Conference on Integral Methods in Science and Engineering Special Session, 2015      
  • Simulation and identification of synchronization in resting-state fMRI networks. Research Colloquium, University of Tulsa, 2015      
  • Structural and practical identifiability issues of epidemic models. American Institute of Mathematical Sciences Meeting, 2016      
  • Spread of Avian influenza pandemic to USA via air travel. American Mathematics Society Sectional Meeting, 2013      
  • Structural identifiability issues of epidemic models. Joint Mathematics Meetings, 2016      
  • Mathematical analysis of the spread of HIV/AIDS using SEAIT model. Research Colloquium, University of Tulsa, 2013      
  • Spread of Avian influenza pandemic to USA via air travel. Society for Industrial and Applied Mathematics Meeting, 2013      

Apprentices

  • Hoyt Gong, undgraduate student (2020)  
  • Jeremy Rubin, PhD student (2020)  
  • Monica Ionescu, Master student (2019)
  • Summer

  • Wara Laura, undgraduate student (2020)
  • Beverly Chang, undgraduate student (2020)
  • Praneel Chakraborty, undgraduate student (2020)
  • Natasha Ray, highschool student (2020)
  • Daniel Goldberg, undgraduate student (2020)

Publications

  • Necibe Tuncer and Trang Le (2014) Effect of air travel on the spread of an avian influenza pandemic to the United States. doi:10.1016/j.ijcip.2014.02.001
  • Trang T Le, Bryan A Dawkins and Brett A McKinney (2020) Nearest-neighbor Projected-Distance Regression (NPDR) for detecting network interactions with adjustments for multiple tests and confounding. doi:10.1093/bioinformatics/btaa024
  • Trang T Le, W Kyle Simmons, Masaya Misaki, Jerzy Bodurka, Bill C White, Jonathan Savitz and Brett A McKinney (2017) Differential privacy-based evaporative cooling feature selection and classification with relief-F and random forests. doi:10.1093/bioinformatics/btx298
  • Trang T Le, Weixuan Fu and Jason H Moore (2019) Scaling tree-based automated machine learning to biomedical big data with a feature set selector. doi:10.1093/bioinformatics/btz470
  • Sahib S. Khalsa, ..., Trang T Le, ... and Nancy Zucker (2017) Interoception and Mental Health: A Roadmap. doi:10.1016/j.bpsc.2017.12.004
  • Trang T. Le, Rayus Kuplicki, Brett A. McKinney, Hung-wen Yeh, Wesley K. Thompson, Martin P. Paulus and NA NA (2018, preprint) A nonlinear simulation framework supports adjusting for age when analyzing BrainAGE. doi:10.1101/377648
  • Bryan A. Dawkins, Trang T. Le and Brett A. McKinney (2019, preprint) Theoretical properties of nearest-neighbor distance distributions and novel metrics for high dimensional bioinformatics data. doi:10.1101/857821
  • Trang T Le, Weixuan Fu and Jason H Moore (2018, preprint) Scaling tree-based automated machine learning to biomedical big data with a dataset selector. doi:10.1101/502484
  • Trang T Le, Ryan J Urbanowicz, Jason H Moore and Brett A McKinney (2018) STatistical Inference Relief (STIR) feature selection. doi:10.1093/bioinformatics/bty788
  • Trang T L├¬, Zach Osman, D K Watson, Martin Dunn and B A McKinney (2019) Generalization of the Fermi pseudopotential. doi:10.1088/1402-4896/ab0811
  • Necibe Tuncer and Trang T. Le (2018) Structural and practical identifiability analysis of outbreak models. doi:10.1016/j.mbs.2018.02.004
  • Trang T. Le, Rayus Kuplicki, Hung-Wen Yeh, Robin L. Aupperle, Sahib S. Khalsa, W. Kyle Simmons and Martin P. Paulus (2018) Effect of Ibuprofen on BrainAGE: A Randomized, Placebo-Controlled, Dose-Response Exploratory┬áStudy. doi:10.1016/j.bpsc.2018.05.002
  • Trang T. Le, Bryan A. Dawkins and Brett A. McKinney (2019, preprint) Nearest-neighbor Projected-Distance Regression (NPDR) for detecting network interactions with adjustments for multiple tests and confounding. doi:10.1101/861492
  • Trang T. Le, Daniel S. Himmelstein, Ariel A. Hippen Anderson, Matthew R. Gazzara and Casey S. Greene (2020, preprint) Analysis of ISCB honorees and keynotes reveals disparities. doi:10.1101/2020.04.14.927251