2016 - 2019: University of Florida, Gainesville, FL
PhD Mechanical Engineering: 3.68/4.00 GPA
Dissertation: Influence of objective functions on the identification of material model parameters from experimental data pdf.
2014 - 2016: Stellenbosch University, Stellenbosch, South Africa
MEng Mechanical Engineering: cum laude
Thesis: Obtaining non-linear orthotropic material models for pvc-coated polyester via inverse bubble inflation https://hdl.handle.net/10019.1/98627 pdf.
2009 - 2013: University of Colorado, Colorado Springs, CO
BSc Mechanical Engineering: 3.72/4.00 GPA with honor
Lawrence Livermore National Laboratory
2020 - Present: Postdoctoral Researcher Staff Member
Build and deploy machine learning models for structural optimization software.
Sandia National Laboratories
2018 - 2020: Research & Development Graduate Intern
Worked in the Verification Validation (VV), Uncertainty Quantification (UQ), Credibility Process group. R&D of statistical methods to estimate extreme tail probabilities with a limited number of samples.
University of Florida
2016 - 2019: Research Assistant / Instructor
Applied optimization to find model parameters that match experimental data, and research on quantifying the difference between experimental data and numerical models. Created and taught a Python Programming course.
UTC Aerospace Systems
2013 - 2014: Manufacturing Engineer
2012: Manufacturing Engineer Intern
Worked directly with all OEM final assembly lines to interface with Product Engineering on issues related to manufacturing. Participated on Integrated Product Development Teams to improve manufacturing processes associated with specialty aircraft seats (pilot, flight attendant, and observer) for commercial
University of Colorado - Colorado Springs
2010 - 2013: Student Assistant IV
All-purpose IT wizard. Graphic design guru.
Peer-reviewed journal articles
- Jekel, C.F., Venter, G., Venter, M.P., Stander, N. and Haftka, R.T., 2018. Similarity measures for identifying material parameters from hysteresis loops using inverse analysis. International Journal of Material Forming, 12(3), 355-378. doi:10.1007/s12289-018-1421-8 pdf
- Jekel, C.F., Venter, G. and Venter, M.P., 2017. Modeling PVC-coated polyester as a hypoelastic non-linear orthotropic material. Composite Structures, 161, pp.51-64. doi:10.1016/j.compstruct.2016.11.019 pdf
- Jekel, C.F., Venter, G. and Venter, M.P., 2016. Obtaining a hyperelastic non-linear orthotropic material model via inverse bubble inflation analysis. Structural and Multidisciplinary Optimization, 54(4), pp.927-935. doi:10.1007/s00158-016-1456-8 pdf
- Jekel, C.F., and Haftka, R.T., 2020. Weaponizing Favorite Test Functions for Testing Global Optimization Algorithms: An illustration with the Branin-Hoo Function. In 2020 AIAA AVIATION FORUM. doi:10.2514/6.2020-3132 pdf
- Jekel, C.F., and Haftka, R.T., 2020. Risk Allocation for Design Optimization with Unidentified Statistical Distributions. In 2020 AIAA Non-Deterministic Approaches Conference. doi:0.2514/6.2020-0415 pdf
- Jekel, C. F., Haftka, R. T., Venter, M. P., and Venter, G. Cross Validation to Select Material Models with Bulge Inflation Tests on PVC-coated Polyester. Structural Engineering, Mechanics and Computation, September 2019. pdf
- Jekel, C. F., Grechuk, B., Zhang, Y., and Haftka, R. Comparison of Chebyshev’s Inequality and Non-parametric B-Basis to Estimate Failure Strength of Composite Open Hole Tension Tests. The World Congress of Structural and Multidisciplinary Optimization, May 2019. pdf
- Jekel, C. F., and Romero, V.J. Bootstrapping and Jackknife Resampling to Improve Sparse-Data UQ Methods For Tail Probability Estimates with Limited Samples, ASME V&V Verification and Validation Symposium May 2019. pdf
- Jekel, C.F., Haftka, R.T., Venter, G. and Venter, M.P., 2018. Lack-of-fit Tests to Indicate Material Model Improvement or Experimental Data Noise Reduction. In 2018 AIAA Non-Deterministic Approaches Conference (p. 1664). doi:10.2514/6.2018-1664 pdf
Technical reports and other non-refereed papers
- Jekel, C.F. and Romero, V.J., Conservative Estimation of Tail Probabilities from Limited Sample Data. Sandia Report SAND2020-2828. March 2020. doi:10.2172/1605343 pdf
- Jekel, C.F. and Haftka, R.T., 2019. Fortified Test Functions for Global Optimization and the Power of Multiple Runs. arXiv preprint arXiv:1912.10575 pdf
- Jekel, C.F. and Venter, G., 2019. pwlf: A Python Library for Fitting 1D Continuous Piecewise Linear Functions. https://github.com/cjekel/piecewise_linear_fit_py pdf
- Jekel, C.F. and Haftka, R.T., 2018. Classifying Online Dating Profiles on Tinder using FaceNet Facial Embeddings. arXiv preprint arXiv:1803.04347 pdf
- A Python library for fitting 1D continuous piecewise linear functions.
- Technologies: Python, NumPy, SciPy, pyDOE, (Optional: TensorFlow).
- Quantify the difference between two curves in space.
- Includes Partial Curve Mapping method, Area between two curves, Discrete Fréchet distance, Dynamic Time Warping (DTW), or Curve Length based similarity measures.
- Discrete Fréchet distance and DTW support N-Dimensional data!
- Technologies: Python, NumPy, SciPy.
- Command line application to build personalized machine learning models for Tinder.
- Build a database as you like and dislike profiles.
- Train a model using computer vision to your database.
- Use the trained model to automatically like and dislike new profiles.
- Technologies: Python, NumPy, Matplotlib, Pandas, imageio, scikit-learn, scikit-image, TensorFlow, FaceNet, (Optional: Docker)
- Dynamic Time Warping (DTW) single header library for C++.
- Compute the DTW distance between two c++ vectors of arbitrary length.
- Supports N-Dimensional data.
- A small Python library for one-sided tolerance bounds and two-sided tolerance intervals.
- Supports two sided tolerance intervals for: Normal and Lognormal distributions
- Supports one sided tolerance bounds for: Normal, Lognormal, Non-parametric, Hanson Koopmans, and Hanson Koopmans CHM methods
- Technologies: Python, NumPy, SciPy, SymPy
2017: Python Programming - 1 credit hour graduate course - Syllabus - Course material
Created and taught the first Python Programming course in the MAE department at the University of Florida. The course covers topics from the basics of Python to the most popular scientific Python libraries in an effort to prepare graduate students to perform research in Python.
Honors and awards
2016: University of Florida GSFA - four year graduate school fellowship
2016: Stellenbosch departmental bursary - three year PhD funding
2016: MEng, obtained cum laude
2014: Wilhelm Frank Trust - research funding (~$50k secured with team)
2013: BSc, obtained with honor - graduated third in class
2010: Reisher Family Scholarship - three year award
2009: Braxton Technologies Scholarship - four year award
2020: Surrogate Based Optimization. Overview presented for LLNL Center Design Optimization. pdf
2020: Fortifying Favorite Test Functions for Testing Global Optimization Algorithms. In 2020 AIAA AVIATION FORUM. Video
2020: Risk Allocation for Design Optimization with Unidentified Statistical Distributions. In 2020 AIAA Non-Deterministic Approaches Conference. Orlando, Florida. pdf
2019: Isotropic and orthotropic parameter identification from full field bulge inflation tests on PVC-coated polyester. The Seventh International Conference On Structural Engineering, Mechanics and Computation, Cape Town, South Africa. pdf
2019: Advances with Reviewing Personalized Tinder Profiles Using FaceNet and Historical Preference. University of Florida Data Science and Informatics Spring Symposium, Gainesville, Florida. pdf
2018: Conservative Estimation of Tail Probabilities from Limited Sample Data. University of Florida Workshop Risk Management Approaches in Engineering Applications, Gainesville, Florida. pdf
2018: Using FaceNet to automatically like Tinder profiles based on individual preference. University of Florida Data Science and Informatics Spring Symposium, Gainesville, Florida.
2018: Lack-of-fit Tests to Indicate Material Model Improvement or Experimental Data Noise Reduction. AIAA Non-Deterministic Approaches Conference, Kissimmee, Florida. pdf
2015: Obtaining Material Models for Inflatable Structures via Inverse Bubble Inflation. Stellenbosch University Mechanical & Mechatronic Engineering Department Research Colloquium, Stellenbosch, South Africa.
2015: Obtaining Material Models for use in Finite Element Analyses of PVC-coated polyester via an Inverse Bubble Inflation Method. CIMNE VII International Conference on Textile Composites and Inflatable Structures, Barcelona, Spain.
2014: An Inverse Method for Generating Polymer Properties for use in Finite Element Analyses via Bubble Inflation Testing. SAImechE Mechanical, Manufacturing, and Materials Engineering Conference, Stellenbosch, South Africa.
- Structural and Multidisciplinary Optimization (SAMO) Journal reviewer (2017, 2018, 2019, 2020, 2021)
- Society for Industrial and Applied Mathematics (SIAM) book review (2020)
- Journal of Composite Materials reviewer (2019, 2021)