Teaching

Teaching#

University Courses#

Department of Statistics and Data Science, Southern Methodist University.

Course

Title

Terms

DS 1300

A Practical Introduction to Data Science

2021, 2022, 2023

DS 7347

Data Science and High-Performance Computing

2022, 2023

DS 7333

Quantifying the World

2024

Earlier laboratory instruction as a graduate student and postdoctoral fellow included the Graduate/Undergraduate Computational Chemistry Laboratory (2009, 2011, 2013), the Graduate/Undergraduate Computer Aided Drug Design Laboratory (2010, 2012), and Undergraduate General Chemistry Laboratory (2010).

Technical Workshops#

More than 150 workshops delivered at SMU since 2015, ranging from two-hour sessions to week-long, full-day intensives.

2025 — O’Donnell Data Science and Research Computing Institute: Distributed Python; Graph Machine Learning Fundamentals.

2024 — O’Donnell Data Science and Research Computing Institute: Introduction to HPC; Parallel Programming in C++.

2023 — Research and Data Science Services Workshop Series: Introduction to HPC; Scaling HPC Workflows; Kubernetes for Beginners.

2022 — Research and Data Science Services Workshop Series: C++ Parallel STL; KOKKOS & RAJA; MPL (Modern C++ MPI); R libraries from C++; Python modules from C++. Also Speed Data-ing.

2021 — Center for Research Computing Spring Workshop Series: ManeFrame II (M2) Introduction; Intel oneAPI HPC Toolkit Overview; Python Workflows on M2; NVIDIA HPC SDK Overview; R Workflows on M2; Introduction to OpenMP and OpenACC; Introduction to MPI; Introduction to Standard C++ Parallel Algorithms.

2020 — Center for Research Computing Fall, Summer, and Spring Workshop Series (25 sessions plus five full-day workshops): M2 introductions and storage workflows; Python, R, and Julia workflows on M2; Docker & Singularity; Introduction to MPI, OpenMP, and OpenACC; Standard C++ Parallel Algorithms; Introduction to LAPACK and BLAS; Text Mining with Python; the HPC Portal; Using GitHub; Portable Accelerator Code with KOKKOS, RAJA, and OCCA; Writing High Performance Python Code; Profiling Applications; Improving Code Vectorization.

2019 — Center for Research Computing Fall, Summer, and Spring Workshop Series (24 sessions plus a week-long, full-day workshop): Introduction to Using M2; Vectorization Using OpenMP; R and Python Workflows on M2; Using Git and GitHub; Hybrid MPI with OpenMP and OpenACC; Machine Learning Toolkits on M2; Parallel Architecture Abstraction via OCCA and RAJA; Docker and Singularity on M2; Using Spack for Development; Accelerated Libraries; Improving Vectorization.

2018 — Center for Scientific Computation Fall and Spring Workshop Series (28 sessions plus a week-long, full-day workshop): ManeFrame II introductions; Parallel R and Parallel Python on M2; Using Spack for Development; OpenMP, OpenACC, and MPI introductions; Using SAS on M2; Introduction to Jupyter Notebooks; Graphical Applications on M2; NVIDIA P100 Nodes; Intel Xeon Phi Nodes; Advanced Slurm Features; Automating Computational Workflows. Also a three-hour MathWorks MATLAB workshop.

2017 — Center for Scientific Computation Fall and Spring Workshop Series (23 sessions plus a week-long, full-day workshop): Migrating to and Introduction to ManeFrame II; Debugging and Parallel Python; Jupyter Notebooks; Porting Applications to MICs and GPUs; Debugging and Profiling Parallel Applications with Allinea DDT and MAP; Introduction to Parallel, Research, and Accelerator Programming; OpenMP, MPI, CUDA, and OpenCL deep dives; Introduction to Vectorization.

2016 — Center for Scientific Computation Fall and Spring Workshop Series (16 sessions plus a week-long, full-day workshop): ManeFrame introductions; GPGPU Development; Introduction to Jupyter; Debugging and Profiling Parallel Applications; Build Automation Development Tools; Introduction to Julia; Python in HPC Environments; Parallel Programming on ManeFrame; GPGPU Programming Overview; OpenCL for HPC; Using R on ManeFrame.

2015 — Center for Scientific Computation Fall Workshop Series (six sessions) plus a week-long, full-day summer workshop: Introduction to Using ManeFrame; Introduction to Parallel Programming; Post-processing Data Using Python; Bash Shell Scripting; Introduction to C++ MPI Programming; Introduction to GPGPU Programming.

2012–2014 — Advanced Python Programming Workshop; Advanced CHARMM Workshop; CATCO URVA Workshop; CATCO Methods Workshop; LaTeX Workshop.

Student Advisement#

Graduate#

  • Robert Ortega, Southern Methodist University — Performance tuning of parallel free energy sampling methods, September 2020 to May 2021

Undergraduate#

  • Gabriel Mongaras, Southern Methodist University — Describing electron density through machine learning models, August 2022 to December 2023

  • Carter Koehler, Southern Methodist University — Describing electron density through machine learning models, August to December 2018; Super Computing 2018 Student Cluster Competition, January to May 2018

  • Ethan Britt, University of Texas at Dallas — Super Computing 2018 Student Cluster Competition, January to May 2018

  • Mauhib Iqbal, University of Texas at Dallas — Super Computing 2018 Student Cluster Competition, January to May 2018

  • Boce Lin, Southern Methodist University — Super Computing 2018 Student Cluster Competition, January to May 2018

  • Rick Simon, Southern Methodist University — Super Computing 2018 Student Cluster Competition, January to May 2018

  • Vyas Nellutla, University of Texas at Dallas — Super Computing 2018 Student Cluster Competition, January to May 2018

  • Moez Janmohammad, Southern Methodist University — Engaged Learning Big iDeas Project, ARM Beowulf cluster prototype, January to May 2016

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