Xiang Wang

Xiang Wang is an Associate Professor in the Department of Pharmaceutical Sciences at Howard University College of Pharmacy, where he also directs the Artificial Intelligence and Drug Discovery Core Laboratory for the District of Columbia Center for AIDS Research (DC CFAR). With approximately 20 years of experience, his work bridges computational methods and pharmaceutical innovation.

Dr. Wang's research focuses on advancing drug discovery through cutting-edge technologies. His expertise includes computer-aided drug design (CADD), machine learning, structure-based drug design (SBDD), high-throughput screening (HTS), and biomolecular simulation. He has been actively integrating virtual reality (VR), augmented reality (AR), and artificial intelligence (AI) into both pharmacy education and research, reflecting a forward-looking interdisciplinary approach.

He has secured over 20 grants from federal, state, university, and international funding bodies and has published around 50 peer-reviewed articles, reviews, book chapters, and patents, along with 190 conference abstracts and invited lectures. His scholarly impact is further amplified by his service as a reviewer for more than 45 major journals, including the Journal of Medicinal Chemistry and Journal of Chemical Information and Modeling.

• National Institutes of Health (NIH)
• National Aeronautics and Space Administration (NASA)
• American Association of Colleges of Pharmacy (AACP)
• Alzheimer’s Drug Discovery Foundation (ADDF)

Dr. Wang has served on review panels for prominent funding agencies such as the NIH, NASA, AACP, and ADDF, contributing to the evaluation and advancement of scientific research in his fields. His leadership in the AI and Drug Discovery Core underscores his role in building research infrastructure and mentoring in a high-impact domain. While specific advisees are not listed, his extensive grant activity and lab direction suggest active student and postdoctoral involvement.

His work in developing immersive technologies for professional pharmacy education highlights a commitment to innovation in teaching. The convergence of AI, VR, and AR in his research program points to a vision of next-generation drug discovery and pedagogy.