Introduction
I am a passionate researcher focused on advancing machine learning and its applications in materials science, computational chemistry, computational physics, and medicine. My work aims to integrate multimodal foundation models with graph-based approaches to enable innovative materials design. Additionally, I am exploring the potential of the multimodal foundation models to create intelligent agents that support physicians in diagnosing and treating Alzheimer’s disease.
A key focus of my research is the application of machine learning techniques to accelerate materials discovery. By leveraging advanced algorithms, I aim to identify novel materials with desirable properties, driving innovation in areas such as energy storage, drug discovery, and catalysis. Additionally, I explore the intricate world of protein structure transition trajectories, using machine learning to uncover the complex mechanisms behind protein folding and dynamics.
I have had the privilege of collaborating with researchers from institutions such as Arizona State University, the University of Texas at Austin, University of South Carolina, Howard University, the City University of New York, Wake Forest University, Kennesaw State University, Brookhaven National Laboratory, Sandia National Laboratory, NASA Jet Propulsion Laboratory, and the Joint School of Nanoscience and Nanoengineering, which comprises the University of North Carolina at Greensboro and North Carolina A&T University.
Despite my demanding teaching schedule, I have been actively involved in disseminating my findings through scholarly publications. To date, I have contributed over thirty papers to esteemed journals and international conference proceedings, including Journal of Chemical Theory and Computation, ACS LANGMUIR, Applied Physics Letters, ACS Journal of Physical Chemistry(b), ACM Multimedia Conference, IEEE Trans. on Multimedia, ACM Trans. on Multimedia Computing, Communications and Applications, Neural Computing and Applications, and IEEE International Conference on Machine Learning and Applications.
I am eager to continue my journey as a researcher, exploring the boundless possibilities at the intersection of machine learning, physical sciences, and medical sciences.