Ï㽶¸£ÀûÖ±²¥ is one of seven universities that are part of the collaboration

Ï㽶¸£ÀûÖ±²¥ was awarded a grant for $600,000 to aid in Mobilizing the Emerging Diverse AI Talent (MEDAL) through Design and Automated Control of Automated Scientific Laboratories.

The project is a collaboration between Ï㽶¸£ÀûÖ±²¥, the University of Texas at San Antonio, the Florida International University, the Argonne National Laboratory, Bowie State University, Oakland University and the University of Central Florida.

The MEDAL project aims to train faculty, doctoral, graduate, and undergraduate students with high research activity on contemporary artificial intelligence (AI) research relevant to the Department of Energy. This includes topics such as transformers, large language models, pre-trained visual and scientific models, and data-driven control of autonomous scientific labs. The project comprises four distinct tasks that aim to enhance learning outcomes on these topics by catering to diverse learning preferences.

"The mission of the project is to conduct scientific and technical innovations for autonomy in scientific labs as well as train the diverse students in the cutting-edge scientific machine learning and Artificial Intelligence technologies," said Associate Professor of Computer Science Sathish Kumar. "In addition, the project's mission is to create courses in scientific machine learning and contribute to the advanced Artificial Intelligence courses topics such as explaining the ability of deep learning models, the robustness of deep neutral networks and attention based-AI models such as transformers and perceivers.

Kumar explained that one of the reasons he became so intrigued to pursue the grant was conducting state-of-the-art research in scientific AI/ML and training diverse students to research cutting-edge Artificial Intelligence Technologies.

"This includes transformers, large language models, pre-trained visual and scientific models, along with control of autonomous scientific labs," he said. "The rationale for pursuing this project is to conduct outreach activities through summer workshops and creation of asynchronous online AI courses."

The real winners are the students, whom Kumar said he plans to use the grant money to support three  Ph.D. students and two MS students for three years, along with ten undergraduate students for a two-week summer workshop every year for three years.

Kumar also plans to purchase two GPU workstations, five VR/AR headsets, and two web servers and travel to the Argonne National Lab in Illinois.

"Ultimately, this project will really help Ï㽶¸£ÀûÖ±²¥ to pursue follow-up grant funding from the Department of Energy," he said. "Undergraduate students will benefit by attending the two-week summer workshops and getting trained with the cutting-edge Artificial Intelligence and Scientific Machine Learning related content created in the MEDAL program."

Some of the project tasks include:

• The adaptive delivery of video lectures using AI.
• Large language models assisting with automated evaluation and related feedback generation.
• The use of deep reinforcement learning and pre-trained models for autonomy in scientific labs.
• The sustained dissemination of our efforts through outreach through summer workshops and asynchronous online AI classes.

Kumar said by implementing these tasks, the project aims to train students to create a new, diverse workforce capable of contributing to AI engineering and research in line with the technical requirements of the Department of Energy (DOE).