Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems
Room: Private Dining
Jalen M. Magee - Savannah State University
Co-Author(s): Antonio Velazquez, Savannah State University, Savannah, GA;Abhinandan Chowdhury, Savannah State University, Savannah, GA
With the surge in artificial intelligence in applications catering to the industry and academia, applications of deep learning are a bastion for advancement in current and future market demands. A headway of Deep Learning in STEM fields, such as engineering and computer sciences, is paramount in academic circles. Minority institutions such as HBCUs have been historically shortening on receiving and experimenting with top-end technologies in Computer Science and Artificial Intelligence (AI). On top of that – and as a result of the pandemic – recruitment rates have currently severely plummeted at HBCUs prompting an urgent need to increase retention and enrollment strategies to raise the numbers. One of these strategical schemes is the development of AI-wise virtualized cyber tools to provide support, assistance, guidance, steering, and even counseling advice to incoming freshmen. Topics of deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks are addressed. A Deep-Learning computational instrument is presented to facilitate and scaffold the entry knowledge acquisition and skill development of STEM newcomer students. A study of diverse neural network architectures (i.e. convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks) will be tested and implemented. A review of natural language processing (NLP) techniques and speech recognition will be also investigated. Special attention is given to math, computer science technology, and engineering technology students at HBCUs, and how this implementation will impact the terminal learning efficiency of entry-level African-American student communities at large.
Funder Acknowledgement(s): National Science Foundation through Historically Black Colleges and Universities Undergraduate Program (HBCU-UP) [NSF 20-559]. Directorate for Education and Human Resources, Division of Human Resource Development. NSF HBCU-UP Targeted Infusion Project in Interdisciplinary Data Analytics (TIP-IDA) Award Number 1719514
Faculty Advisor: Dr. Antonio Velazquez, firstname.lastname@example.org
Role: Approximately 70% of the research is done by the student, 30% by the advisor.