Dewayne A. Dixon

Assistant Professor of Mathematics, School of Science, Hampton University 

Email: dewayne.dixon@hamptonu.edu 

Office Location: Science and Technology Building, Hampton, VA, Hampton Campus 

Academic Background 

Ph.D. in Mathematics – Machine Learning, Bioinformatics, Genetics 
Howard University, Washington, D.C.  

(August 2020 – July 2024) 

M.S. in Mathematics 
Virginia State University, Petersburg, VA  

(December 2018) 

B.S. in Mathematics 
Morehouse College, Atlanta, GA  

(May 2014) 

Research Interests 

Dr. Dixon’s work mainly involves developing Explainable AI with a primary focus on the use of graph neural networks for the analysis of complex and structural data. His work, therefore, using machine learning models, is poised to bridge the gaps between interpretability and high performance, envisaging the applications in other fields of social sciences, social network analysis, among other related STEM disciplines. Dr. Dixon is dedicated to making AI models more interpretable for both researchers and end-users; this would raise trust in AI applications, especially for ethical or highly socially impactful uses. 

Research Projects 

Doctoral Dissertation: Core Epigenetic Module Biomarkers among Various PTSD Subtypes 
Under the leadership of Principle Investigator Dr. Yeona Kang of Howard University and co-PI Dr. Ruoting Yang of Walter Reed Army Institute of Research, Dr. Dixon will apply the workflows to analyze DNA methylation data as part of a multifaceted approach that helps to identify the biological core modules associated with PTSD that can be used in developing biomarkers and personalized treatments. 

Teaching Experience 

Hampton University, Hampton, VA 
Assistant Professor of Mathematics, August 2024-Present 
Classes Taught: College Mathematics, Calculus, Intermediate Algebra, and Differential Equations 

Howard University, Washington, D.C. 
Math Teacher, August 2020 – May 2024 
Teaching Experience: Algebra, Calculus I & II, Topics in AI 
Course Development and delivery: Machine Learning, Deep Learning 
Emphasized the engagements of students and collaboration in both virtual and in-person settings. 

Morehouse College, Atlanta, GA 
Mathematics Adjunct Faculty (August 2019 – June 2020) 
Taught College Algebra to diversified student populations 
Collaborated with faculty on improving student learning 

Professional Experience 

U.S. Department of Defense (DOD) 
Machine Learning Intern, Washington, D.C. (July 2020 – March 2023) 
Investigated in collaboration with the Walter Reed Army Institute of Research 
Developed laboratory research skills, focusing on machine learning applications 

Publications and Presentations 

Contributed Talks 
– Core epigenetic module biomarkers among various subtypes of PTSD 
  – Society for Mathematical Biology Annual Meeting, Columbus, OH (July 2023) 
  – Military Health System Research Symposium, Orlando, FL (August 2024) 

Service 

Founder, “Bridging Education and Mathematics,” Howard University 
President-GSU Howard University’s Society of Applied Mathematics (SIAM) student chapter 

Research Philosophy 

Dr. Dixon’s research philosophy puts novelty at the forefront of the intersection of explainable AI and graph neural networks. He is committed to enhancing the transparency and interpretability of AI models, with special regard to the manipulation of data with complex structures. He is developing models that give insight into their decision-making processes with the hope of contributing to this wider adoption across scientific disciplines, and in particular in the social sciences and other STEM fields, making sure that the AI solutions are ethical and socially responsible. 

Teaching Philosophy 

Dr. Dixon is passionate about crafting new learning methodologies that use AI in Math and Data Science education. He is committed to providing a modern curriculum that bridges traditional mathematical education with state-of-the-art AI and data science, preparing students for leading roles in technological and scientific fields.