RTO Scientific Software Engineering

The RTO Scientific Software Engineering (SSE) team serves as a technical resource to ASU researchers, assisting in code development, architecture, debugging, profiling, optimization, maintenance and documentation. In its close affiliation with the ASU Research Computing organization, it promotes best practices in exploiting HPC resources, including GPU acceleration.

With a wide portfolio of successfully completed projects from statistical/machine learning on large datasets to large-scale numerical solutions of PDEs, SSE brings current software standards and employs the latest tools and libraries in each new effort. Furthermore, computational research can be scaled to run on large numbers of CPUs or the GPU.  Visualization and workflow development services are also available. In addition, the SSE team:

  • Continuously evaluates new tools and technologies for use in existing and future clusters.
  • Avails researchers of nationally available external resources
  • Develops training materials for instruction, including Software Carpentries certified workshops

To request a consultation with the Scientific Software Engineering team, email rtshelp@asu.edu.

RTO Scientific Software Engineering Team

  • Dr. Gil Speyer, Lead Research Software Engineer 
  • Jason Yalim, Postdoc 
  • Rebecca Belshe, Software Application Analyst 

Training and Workshops 

Research Computing offers a wide variety of educational resources including virtual or in-person workshops and training sessions, hosted virtual “office hours,” and online training materials and user documentation. Below are examples of the training provided to the community.

  • Introduction to HPC and the ASU Research Computing Cluster 

  • Introduction to Python on the ASU Research Computing Cluster 

  • Introduction to R on the ASU Research Computing Cluster 

  • Introduction to Command-Line on the ASU Research Computing Cluster 

  • Introduction to Cryo-EM Processing on the ASU Computing Cluster 

  • Adapting R Applications for HPC and GPU 

  • Adapting Matlab Applications for HPC and GPU 

  • HPC Deep Learning with Python 

  • Data Handling with Python’s NumPy and Pandas on the ASU Research Computing Cluster 

  • Machine Learning and GPUs with Python on the ASU Research Computing Cluster 

  • Neural Nets with Python’s Pytorch and Tensorflow on the ASU Research Computing Cluster 

(Our training team are all Software Carpentry certified.) 

More Information 

For an updated list of Research Computing workshop and training offerings and useful resources, visit our documentation site here. To schedule a training session, contact our training team at rtshelp@asu.edu.  


ASU Research Computing engages in a variety of outreach efforts locally at ASU as well as within the state of Arizona, regionally, and nationally. Examples of our engagements include: 

  • ASU schools and academic departments 

  • Faculty recruits, existing faculty researchers, and researchers from “non-traditional” disciplines 

  • Research Computing Governance Board 

Members of our staff are happy to meet with you and discuss our services, resource offerings, outreach activities, or opportunities to collaborate and partner on research efforts. Contact us at rtshelp@asu.edu or request a personalized consultation using this form