Curriculum Vitae

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)      
  a nearest-neighbor feature selection algorithm that fits a generalized linear model for projected distances of a given attribute over all pairs of instances in a neighborhood. In the NPDR model, the predictor is the attribute distance between neighbors projected onto the attribute dimension, and the outcome is the projected phenotype distance (for quantitative traits) or hit/miss (for case/control) between all pairs of nearest neighbor instances.
• privateEC: Differential privacy for machine learning (2017)      
  a stochastic privacy-preserving machine learning algorithm that uses ReliefF for feature selection and random forest for privacy preserving classification.
• stir: ReliefF on steroid (2018)      
  Precursor of npdr
• treeheatr: Heatmap-integrated decision tree visualizations (2020)      
  treeheatr displays a more interpretable decision tree visualization by integrating a heatmap at its terminal nodes.

Courses and Workshops

• Fundamentals of AI guest lecturer, University of Pennsylvania, Mar 30, 2020      
  I give two 80-minute guest lectures on Information Theory and Stochastic Processes and their roles in artificial intelligence and biomedical applications.
• Machine learning workshop, R Ladies Philly, Dec 2, 2019      
  A brief introduction to machine learning and hands-on exercise of building models to predict the alcohol concentration of beers from a beer review dataset.
• Introduction to R seminar, University of Tulsa, Aug 25, 2017  
  An immersive, “bootcamp” styled seminar designed to rapidly build student proficiency in R programming. The seminar is conducted over a long weekend or similarly condensed timeframe in a computer laboratory setting.
• Precalculus instructor, University of Tulsa, Jan 11, 2016  
  I prepare 30+ students for the study of calculus.
• Calculus I & II teaching assistant, University of Tulsa, Jan 13, 2014  
  I lead Calculus I & II problem-solving sections and design and grade quizzes. I had 200+ students over the course of four semesters.
• Natural science tutors, University of Tulsa, Feb 7, 2011  
  I tutor students (including many student athletes) in math, physics and chemistry. I also worked in Math Lab - a free, walk-in tutor service for students at all levels.

Presentations

• Multilocus risk scores: rethinking genetic risk scores to account for epistasis, International Joint Conference on Biomedical Engineering Systems and Technologies, Feb 25, 2020      
• Detect network interactions and control for confounders and multiple testing, Rocky Mountain Bioinformatics Conference, Dec 6, 2019      
• Multilocus risk scores, 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      
  Transcriptomics of Brain Age Gap Estimate (BrainAGE): association analysis of depressed and healthy individuals
• 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      
  Integrative network analysis of resting-state fMRI and RNA-Seq data for major depressive disorder
• Optimized random forest classification accuracy, International Conference on Integral Methods in Science and Engineering, Jul 25, 2016      
  Optimized random forest classification accuracy by privacy-preserving simulated evaporative cooling feature selection
• Spread of Avian influenza pandemic to USA via air travel, American Mathematics Society Sectional Meeting, 2013      
• Mathematical analysis of the spread of HIV/AIDS using SEAIT model, Research Colloquium, University of Tulsa, 2013      
• Structural and practical identifiability issues of epidemic models, American Institute of Mathematical Sciences Meeting, 2016      
• Structural identifiability issues of epidemiological models, International Conference on Integral Methods in Science and Engineering Special Session, 2015      
• Structural identifiability issues of epidemic models, Joint Mathematics Meetings, 2016      
• Spread of Avian influenza pandemic to USA via air travel, Society for Industrial and Applied Mathematics Meeting, 2013      
• Simulation and identification of synchronization in resting-state fMRI networks, Research Colloquium, University of Tulsa, 2015      

Publications

• Trang T Lê, Zach Osman, D K Watson, Martin Dunn and B A McKinney (2019) Generalization of the Fermi pseudopotential. doi:10.1088/1402-4896/ab0811
• 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
• 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 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
• 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 Study. doi:10.1016/j.bpsc.2018.05.002
• Necibe Tuncer and Trang T. Le (2018) Structural and practical identifiability analysis of outbreak models. doi:10.1016/j.mbs.2018.02.004
• 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, 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
• 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