Recordings and write-ups of talks I’ve given on Python performance, scheduling, and research software workflows. Most were originally delivered as SHARCNET and Digital Research Alliance of Canada webinars.
Recorded talks
- Writing More Code with AI Agents — A practical way for researchers to use AI coding agents for tests, checks, and diagnostic work without handing over the scientific decisions.
- Serial Farms: Package Options and When to Switch to Farming — A practical comparison of job arrays and serial-farming tools for running many small jobs on HPC systems.
- Revisiting Cython: Is It Still Effective? — A 2025 reassessment of Cython's performance, workflow, and place beside modern Python libraries and compilers.
- Diagnosing Wasted Resources from User-Facing Portals — A walkthrough of using national cluster portals to investigate wait times, priority, and wasted CPU, memory, and GPU allocations.
- Modern Approaches to Profiling in Python with Scalene — A practical introduction to profiling Python CPU, memory, and GPU use with Scalene on HPC systems.
- Creating and Distributing Python Packages — A 2022 talk about using Cookiecutter to create, structure, and distribute a Python package.
- Conquering the Scheduler — A talk about choosing job configurations and scheduler strategies for responsive HPC workloads.
- Pandas Recipes for New Python Users — A beginner-friendly pandas talk with recipes for working with labeled data in Python.
- Cython: A First Look — A first look at using Cython to recover performance when Python code needs to run faster.
Publications
- Huberty, S., Desjardins, J., Collins, T., Elsabbagh, M., & O’Reilly, C. (2026). PyLossless: A non-destructive EEG processing pipeline. Behavior Research Methods, 58(8), 220. https://doi.org/10.3758/s13428-026-02997-z
- Preprint on bioRxiv (2024): https://doi.org/10.1101/2024.01.12.575323
- Huberty, S., & Collins, T. pyLossless [Software]. Zenodo. https://doi.org/10.5281/zenodo.11507277
More on Google Scholar.