Chris Collazo, M.S.

Programmer and language enthusiast. I enjoy exploring how software can most practically model and affect reality. I enjoy functional languages, especially the Lisp family, and adapting their principles for building software with native-compiled systems languages.

Talks

• The Virtues of Values (NimConf 2026) - https://www.youtube.com/watch?v=Ki4-kbSCnXs
  • Describing how Nim's functional and value semantics enable memory-safe, clean, high-performance programs.

Open Source

• nimgnuplot - https://github.com/nervecenter/nimgnuplot
  • A Nim library for generating gnuplot plots from Datamancer dataframes.
  • Docs: https://nervecenter.github.io/nimgnuplot

Publications

• Collazo, C., Vargas, I., Cara, B., Weinheimer, C. J., Grabau, R. P., Goldgof, D., Hall, L., Wickline, S. A., & Pan, H. (2024). Synergizing Deep Learning-Enabled Preprocessing and Human–AI Integration for Efficient Automatic Ground Truth Generation. MDPI Bioengineering, 11(5), 434. https://doi.org/10.3390/bioengineering11050434
  • Summary: We formulate a “self-improvement” process for a convolutional segmentation model wherein it iteratively normalizes and retrains on its training data, called bootstrapping, improving its accuracy over time.
  • Source code: https://github.com/nervecenter/bsp-experiment
• Collazo, C., Vargas, I., Cara, B., Weinheimer, C. J., Grabau, R. P., Goldgof, D., Hall, L., Wickline, S. A., & Pan, H. (2019). Transferrable Deep Learning Algorithms for Identifying Area At Risk in Acute Myocardial Infarction. Abstract. Biomedical Imaging and Instrumentation, Deep Learning in Microstructural Imaging (Oral), BMES Annual Meeting 2019. https://submissions.mirasmart.com/SecureView/BMESArchive/radhjz5inj2.pdf