Dr. Channa De Silva is a Professor and Department Head of Chemistry & Physics at Western Carolina University, USA. He completed his B.S. degree in Chemistry with First-Class Honors at the University of Kelaniya, Sri Lanka, in 2000 and earned his Ph.D. in Chemistry with a GPA of 4.0 from the University of Arizona, USA, in 2007. From 2008 to 2010, he worked as a Research Associate at the Pacific Northwest National Laboratory, in Materials Science and Engineering at the University of Arizona, and the Bio5 Institute at the University of Arizona, USA. His research focuses on developing metal-based nanomaterials for biotechnological applications and conducting computational studies of materials containing lanthanide and actinide metals.

Dr. De Silva has received numerous teaching and research awards, including the University of North Carolina Board of Governors Award for Excellence in Teaching, USA (2024), the Brinson Honors College’s Faculty and Staff Excellence Award, Western Carolina University (2024), the Chancellor’s Distinguished Teaching Award (2024), Winner, FACULTY 3 Minute Research Talk (3MR), Western Carolina University, USA (2024), Teaching Award from the College of Arts & Sciences at Western Carolina University (2022), Visiting Faculty Program Scholar from the U.S. Department of Energy (DOE) (2021), SoCon Faculty Member of the Year Award (2019), and Innovative Scholarship Award (2017).

In his free time, he enjoys playing music, including Sri Lankan music, northern Indian music, and an American folk genre called Appalachian music.

Abstract Title : Artificial Intelligence in Chemistry Research: Transforming Discovery, Design, and Education

Artificial Intelligence (AI) is rapidly reshaping the landscape of chemical research and education, offering transformative capabilities across molecular design, reaction prediction, process optimization, and teaching. Recent advancements highlight AI’s growing role in both undergraduate and graduate-level chemistry, with applications spanning drug discovery, materials science, and sustainable chemical engineering. AI-driven platforms such as ChemCopilot and IBM RXN are streamlining retrosynthesis planning, reaction yield prediction, and real-time process monitoring. Large Language Models (LLMs), including finetuned systems like GVIM, are being integrated into intelligent research assistants capable of molecular visualization, SMILES string processing, and literature retrieval. These tools not only enhance research productivity but also democratize access to advanced computational methods. Educationally, AI’s integration into chemistry curricula is gaining momentum. Workshops and teacher training programs are fostering Technological Content Knowledge (TCK), preparing educators to bridge the gap between scientific innovation and classroom instruction. The 2024 Nobel Prize in Chemistry, awarded for AlphaFold’s protein structure prediction, underscores AI’s interdisciplinary impact and its relevance to future career pathways. Despite its promise, challenges remain in data quality, model interpretability, and ethical deployment. Addressing these issues is essential to ensure scientifically sound and socially beneficial outcomes. This abstract invite discussion on the strategic incorporation of AI into chemistry research and education, emphasizing its potential to accelerate discovery, enhance pedagogy, and prepare students for AI-driven scientific careers.