Jarrod Mau
Assistant Professor of Mathematics and Computer Science
Belhaven University
We modify neural network structures to improve accuracy and to address problems not yet solved by existing architectures. In our work, neural networks have been used to extract features for diagnosing audiological pathologies based on the brain’s response to auditory stimuli. We further employed modified network structures to enhance classification accuracy through independent ensembling, which does not substantially increase computational or training time.
Discipline: Computer Science
Institutional Profile
John Estes, Ph.D
Professor of Mathematics, Dean of Science and Mathematics
Belhaven University
Estes is a graph theorist with a background in independence, including independence polynomials, backbone colorings, maximal outerplanar graphs, and a generalization of trees known as k-trees. In particular, he has investigated extremal cases of k-trees with regard to many metrics, including Zagreb indices. More recently, he and his students have investigated random walks through Markov chains on graphs, in particular, random walks with absorbing states. He is also interested in investigating machine learning and artificial intelligence, looking at algorithmic graph searches and supervised learning techniques.
Discipline: Mathematics
Institutional Profile
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John Neiswinger, Ph.D.
Professor of Biology
Belhaven University
As DNA sequencing becomes cheaper and more prevalent, databases like ClinVar are a valuable resource for elucidating how genomic variability relates to disease progression. This research will use this database to generate clinically curated kinase mutants in order to determine if a change in kinase activity has occurred. Further analysis will be performed to assess the effect of altered kinase activity on cellular function, especially with respect to disease pathogenicity. Additionally, mutagenesis studies will be performed on kinases to probe the sensitivity of their activity to a variety of types of mutations.
Discipline: Biology
Institutional Profile
Manliang Feng, Ph.D.
Associate Professor of Chemistry
Tougaloo College
Dr. Manliang Feng is an Associate Professor of Chemistry and Chair of the Department of Chemistry and Physics in the School of Natural Sciences at Tougaloo College. His research focuses on the development of polypeptide-based multi-functional drug carriers for targeted and image-guided drug delivery, with the goal of improving cancer therapies by enhancing delivery efficiency and reducing side effects. He also investigates the electron transfer mechanisms of metal enzymes and their roles in biocatalysis. In addition to his research, Dr. Feng is dedicated to undergraduate education and mentorship. He has secured significant external funding, including a National Science Foundation award, to promote student engagement in chemistry through innovative pedagogies such as adaptive learning, Process Oriented Guided Inquiry Learning (POGIL), and Course-Based Undergraduate Research Experiences (CUREs). He also collaborates with faculty in the School of Natural Sciences on comprehensive initiatives designed to strengthen the STEM pathway at Tougaloo College. Dr. Feng is committed to advancing STEM education and preparing the next generation of scientists and health professionals.
Discipline: Chemistry
