Building a Regional AI Community Through Collaborative Research and Traineeship with Lawrence Berkeley National Laboratory
Dr. Guobin Xu1, Associate Professor; Dr. Lin Deng2, Associate Professor; Dr. Aijuan Dong3, Professor;
Dr. Silvia Crivelli4, Program Manager
Co-PIs: Dr. Jin Guo1, Dr. Wei Yu2, Dr. Cheng Qian3, Dr. Gunther H. Weber4, Dr. Kelly Rowland4
1: Morgan State University, Baltimore, MD 21251
2: Towson University, Towson, MD 21252
3: Hood College, Frederick, MD 21701
4: Lawrence Berkeley National Lab, Berkeley, CA 94720
Abstract
The commitment of the Department of Energy (DOE) to advancing cutting-edge technologies, including artificial intelligence (AI) and high-performance computing (HPC), is critical for maintaining the nation’s competitive edge in science and industry. However, the United States (US) faces significant challenges: many graduating students, particularly those from underrepresented groups, enter the workforce without the necessary skills, hands-on experience, and research expertise in AI and HPC. The lack of adequately trained graduates impedes the nation’s ability to drive innovation and achieve strategic objectives. To address the challenges, this project aims to build a regional AI community through collaborative research and traineeship with Lawrence Berkeley National Laboratory (LBNL), to provide students with comprehensive training in AI with HPC, equipping them with the technical expertise and practical experience needed to excel in these fields. This project has seven key objectives: (i) Establish a regional community for sustainable traineeship collaboration between Maryland institutions and the DOE lab, including shared infrastructure, cross-mentored research projects, and integrated educational resources; (ii) Train and prepare students for the future AI workforce by providing students with hands-on research experience with DOE Lab’s AI projects, fostering practical skills, expertise in real-world applications, and the ability to collaborate effectively within team settings; (iii) Provide students with opportunities to engage in meaningful research projects, guided by experienced faculty and DOE scientists; (iv) Facilitate students’ professional development through workshops, seminars, hackathons, and training sessions that equip students with the latest AI technologies, industry-standard tools, and ethical considerations; (v) Enhance course contents and design new course modules at the participating institutions to reflect the latest advancements in AI and incorporate practical experiences that align with industry needs; (vi) Recruit and support students from underrepresented groups to participate in the program, promoting diversity and inclusivity in the AI field and ensuring a wide range of perspectives in AI development; (vii) Establish long-term research collaborations between students, faculty, and DOE scientists to address critical AI challenges and advance scientific knowledge. This project is anticipated to mentor and support around 27 students over three years. Working in teams, students will collaborate with scientists at LBNL, contributing to studies that advance AI and HPC. The student participants will receive comprehensive financial support throughout the academic year and summer. Faculty and DOE scientists will hold regular mentoring meetings with student research teams. The curriculum at the participating institutions will be improved through collaboration with LBNL scientists, integrating state-of-the-art research and projects to better prepare students for careers in the AI workforce. This sustainable model ensures the long-term continuation of AI education excellence, aligning with the evolving needs in AI and HPC, as well as the DOE’s mission. This project’s broad impacts will contribute to preparing a highly skilled workforce in AI to ensure that the U.S. maintains its global leadership. This project will establish a strong bridge between DOE labs and academic institutions, fostering synergistic collaboration among the academic institutions themselves. Students will learn about DOE labs, internships, and career opportunities, developing the skills and professional connections needed to apply for these opportunities with confidence. The success of this program will enhance student retention by building students’ confidence in conducting AI-related research. The regional AI community model can be replicated and adapted by other institutions and labs, contributing to the broader ecosystem of science education and research.
