Recipients of Multidisciplinary Generative AI Research Project Funding Named

The Multidisciplinary Generative AI Research Project Funding attracted nine submissions from five distinct colleges/schools within the SU community during this inaugural call for proposals. These applications were meticulously evaluated by the Project Funding Review Committee according to the established award criteria. Please congratulate the inaugural recipients of the Multidisciplinary Generative AI Research Project Funding.

Project 1

Proposal Title: Eye tracking data improvement for visually guided prosthetic devices

Abstract: The project addresses the challenge of upper extremity paralysis by enhancing webcam-based eye-tracking with generative AI. This approach aims to refine data quality, making gaze-controlled assistive devices more accessible and affordable. By comparing innovative AI techniques with traditional data correction methods, the project seeks to establish a new standard in eye-tracking technology, facilitating the development of assistive devices and broadening the application of eye-tracking across various fields. The anticipated outcome is a significant advancement in assistive technology, offering a cost-effective alternative to complex systems and empowering individuals with motor function impairments.

Team Members

Lisa Milkowski (Computer Science, College of Science and Engineering)
Brittany Heintz Walters (Kinesiology, College of Arts and Sciences)

Project 2

Proposal Title: Exploring the Ability of Large Language Models to Produce Physical Objects

Abstract: This research explores the integration of generative AI, specifically large language models (LLMs), with CAD software to overcome the text-only limitation of LLMs. By pairing LLMs with OpenSCAD, an open-source CAD tool, the project aims to generate 3D models from text prompts. The interdisciplinary team, combining expertise from fine arts and mechanical engineering, will train LLMs to create CAD designs, addressing challenges and evaluating the potential of an AI-driven CAD framework for future academic and creative endeavors.

Team Members

Josh Hamel (Mechanical Engineering, College of Science and Engineering)
Trung Pham (Fine Arts, College of Arts and Sciences)

Project 3

Proposal Title: Facilitating Ethical Legal Technology Development Through Interdisciplinary Collaboration

Abstract: This project seeks to revolutionize legal tech innovation by leveraging Large Language Models (LLMs) to enhance access to justice. It underscores the importance of multidisciplinary collaboration among lawyers, technologists, and educators to overcome communication barriers and create shared resources. By integrating law and computer science through practical experiences like the Access to Justice Tech Fellows program and a legal tech tool by a Computer Science graduate, the initiative aims to cultivate ethical innovation in legal tech. The proposed joint practicum, supported by experts from various fields, will provide graduate students with the necessary framework to ethically integrate AI into legal practice, meeting high legal and ethical standards and addressing the increasing interest in AI within the legal academic community.

Team Members
Margaret Chon (School of Law)
LeighAnne Thompson (School of Law)
Julie Kang (Graduate, Executive, and Professional Education, College of Education)
Steven Hanks (Computer Science, College of Engineering)

The Multidisciplinary Generative AI Research Program, supported by a gift from Trustee Brenda Christensen, fosters collaborative projects between students and faculty to explore innovative uses of emergent generative AI at Seattle University. Annually available to all full-time faculty at Seattle University starting each February, the funding encourages the pursuit of educational and research excellence. Your submissions for the upcoming cycle of the Multidisciplinary Generative AI Research Project are eagerly anticipated.