SHI Collaboration Profiles

Profile pages for Sustainable Horizons Institute SRP 2025-2026 Project Leaders


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Edgar Lobaton

North Carolina State University

Biography

Edgar J. Lobaton is a Professor in the Department of Electrical and Computer Engineering (ECE) at North Carolina State University (NCSU). He joined the department in 2011. Lobaton earned his B.S. in Mathematics and Electrical engineering from Seattle University in 2004. He completed his Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 2009. Lobaton was engaged in research at Alcatel-Lucent Bell Labs in 2005 and 2009. He was awarded the NSF CAREER Award in 2016. He was also awarded the 2009 Computer Innovation Fellows post-doctoral fellowship and conducted research in the Department of Computer Science at the University of North Carolina (UNC) at Chapel Hill from 2009 until 2011. In 2023, he received the William F. Lane Outstanding Teaching from the ECE Department. In 2024, he received the University Faculty Scholars and the Outstanding Teacher Awards from NC State. His research focuses on the integration of AI, and physical and probabilistic modeling applied to cyber-physical systems in areas such as wearable health monitoring, rehabilitation robotics, agriculture and biological imaging.

SRP Project Title

AI-Guided Learning in JupyterHub Environments

NAIRR Project

Providing GPU Resources for Deep Learning at NC State

Topical Areas

Applied Computer Science; Educational Sciences; Electrical, Electronic, and Information Engineering

Abstract

Ready to build the future of coding education? This high-impact research project invites motivated students to integrate Large Language Models (LLMs) into the JupyterHub platform for technical coursework, with the core goal of transforming the LLM from a passive tutor into an active, reflective guide. You'll be responsible for developing and deploying the LLM interface within Jupyter Notebooks, implementing a fine-grained tracking and logging mechanism to capture student-LLM interaction data, and creating prompt engineering strategies that strictly enforce the LLM's role as a "navigator", while offering directional guidance, samples and logic critiques rather than direct solutions. This work lies at the critical intersection of AI, Human-Computer Interaction, and Educational Technology, offering a unique opportunity to directly influence how the next generation of technical professionals learns to code by leveraging AI as a powerful learning partner.

Desired Skills

- Proficiency in Python programming - Familiarity with the use of the API for any LLM (e.g., OpenAI API) - [Desired but not required] Familiarity with Kubernetes

Additional Comments

As part of this project, you will also help with expanding on the features of our existing JupyterHub infrastructure through JetStream2.

Lightning Talk Title

LLMs as Co-Pilots in Scientific Modeling, Coding and Learning

Keywords

Code assistant; LLMs; AI as a guide; Physics Modeling