Public Works

2024

  • Paper: Gafur, J., “Adversarial Robustness and Explainability of Machine Learning Models,” PEARC24, Accepted (Full Paper).
  • Presentation: Gafur, J., Goddard, S., Tripp, C., “How Lobotomizing Neural Networks Can Improve Performance,” PASC24, Summer 2024.
  • Poster: Gafur, J., Goddard, S., Tripp, C., “The Impact of XAI Features and Magnitudes in Model Pruning,” Jakobsen Conference, Spring 2024.

2023

  • Presentation: Tripp, C., Egan, H., Bensen, E., Perr-Sauer, J., Wimer, N., Nag, A., Zisman, S., Gafur, J., “Green Computing Opportunities & Strategy,” NREL AI Research Group, Fall 2023.
  • Talk: Gafur, J., Lai, W., “Energy-Efficient Neural Network Pruning for Environmentally-Friendly AI/ML”, Escience, Fall 2023.
  • Talk: Gafur, J., “Integrating Adversarial Observation: Enhancing Robustness, Interpretability, and Trustworthiness in Machine Learning Systems”, US-RSE, Fall 2023.

2022

  • Talk: Gafur, J., Lai, W., “Adversarial attack identifies conserved features of enhancer chromatin architecture”, GLBIO Conference, Spring 2023.
  • Review: Research Software Engineering, Organizer, 2023.
  • Review: INTERSECT, Teaching Assistant, 2023.
  • Review: USRSE, Volunteer, Teaching and Education, 2023.
  • Review: NeurIPS, Artifact Reviewer, 2021.

2021

  • Talk: Gafur, J., Bu, L., Crowley, M., “Non-equilibrium Molecular Simulations of Polymers under Flow: Saving Energy through Process Optimization”, EERE Advanced Manufacturing Office (AMO) Conference, Summer 2021.
  • Review: Scipy, Reviewer, 2021.

2020

  • Package: Scipy 2020 Conference: Pyaesar.
  • Talk: Gafur, J., Neill-Asanza, D.H., Manore, C., Fairchild, G., “Pyaesar: A Multi-Node Multi-Processor API”, SciPy Conference 2020.

2019

  • Paper: Beryllium Parameter Study Technical Paper.
  • Code: Particle Swarm Optimization (PSO) and Visualization.
  • Presentation: Beryllium Strength Model Parameter Study Using a Particle Swarm Optimizer.
  • Talk: Gafur, J., Tourange, E., Hickmann, K., Prime, M., “Calibration of Flyer Plate Impact Experiments using Particle Swarm Optimization (PSO) Strategies”, ASME, 01-18-2019.

2018

  • Code: Pyaesar High Performance Computing Python Embarrassingly Parallel Processing.
  • Presentation: Forecasting Dengue in Brazil with Time Series Modeling in Parallel.
  • Talk: Gafur, J., Kempfert, K., “Forecasting Dengue in Brazil with Time Series Modeling in Parallel”, LANL Student Symposium, 08-03-2018.
  • Review: STEM-Trek ScienceSlam, Judge, 2021.

2017

  • Article: 2017 Domestic Nuclear Detection Office Summer Internship Program.
  • Poster: Nuclear Material Particle Analysis Developing a Plugin for the MAMA Software.
  • Talk: Gafur, J., Kempfert, K., “Nuclear Material Analysis: Developing a Plugin for the MAMA software”, LANL Student Symposium, 07-26-2017.