Generative AI in Scientific Software and Coding Workshop Series

Agenda
Agenda Track

More sessions and details for sessions will be added as they become available. 

Session 1 - Wednesday, October 9th

Keynote session by Dr. Tisha Henderson, Ed.D., who directs Microsoft Modern Works for US Academics West. Dr. Henderson will discuss AI fundamentals and history, provide an overview of AI tools, and discuss the future of AI in computational and information systems.

  • Unlocking Potential- The Role of AI in Education & Beyond
    Join this informative session to unlock the potential in innovating, delegating, and creating with Generative AI. The session will start with a brief introduction into AI fundamentals, provide an overview of Microsoft AI tools designed to help with professional tasks, and conclude with a glimpse into what the future could hold for roles and organizations within the academic community.

Following the keynote will be an introduction to GitHub Copilot with Julio Guzman, Microsoft.

Session 2 - Thursday, October 24th

Title: How to Use GitHub Copilot on NCAR Supercomputers (Derecho/Casper)

Speakers: Brett Neuman, Rory Kelly, Ben Kirk

In this session, participants will learn how to effectively use GitHub Copilot on NCAR’s supercomputers, including Derecho and Casper. The session will provide an overview of integrating Github Copilot with popular editors such as VSCode, NeoVim, and Emacs, and demonstrate how to enhance development workflows on NCAR’s HPC systems. 

Session 3 - Wednesday, October 30th

Title: Generative AI: Laws, Ethics, and Best Practices

Speaker: Dr. Nikolaus Klassen (Google)

In this talk, Dr. Nikolaus Klassen will provide an overview of the evolving landscape of AI regulations, ethical guidelines and general best practices. Centered on three critical areas—legal compliance, ethical standards, and research integrity—this presentation will explore the complexities of using generative AI responsibly in research and professional contexts. Dr. Klassen will discuss emerging legislative frameworks focusing on transparency and accountability for high-risk AI models. Additionally, the talk will highlight best practices in mitigating biases, upholding the scientific method when using AI, and avoiding  biases like the "law of the instrument" pitfall. Attendees will gain insights into how to navigate the ethical and legal landscape of AI, fostering innovation that aligns with societal values and high-quality research standards.

Session 4 - Wednesday, November 13th

Title: Debugging Scientific Code with LLMs: Using GitHub CoPilot for Debugging

Speaker: Supreeth Suresh (NSF NCAR)