Xia Ning

Xia Ning is a Professor jointly appointed in the Department of Computer Science and Engineering, the Division of Medicinal Chemistry and Pharmacognosy (College of Pharmacy), and the Department of Biomedical Informatics at The Ohio State University. She also holds affiliation with the Translational Data Analytics Institute at OSU.

Education:

• Ph.D. in Computer Science & Engineering, University of Minnesota, Twin Cities (2012)
• M.S. in Computer Science, University of Minnesota, Twin Cities
• M.S. in Statistics, University of Minnesota, Twin Cities
• B.S. in Computer Science, Chu Kechen Honors College, Zhejiang University, China

Research Focus: The Ning Lab pioneers data-driven Artificial Intelligence, Machine Learning, and Big-Data analytics with targeted applications in drug discovery, medical informatics, health informatics, and e-commerce. Recent thrusts include generative AI for molecule design, graph neural networks for retrosynthesis, large-language models specialized for chemistry (LlaSMol) and e-commerce (eCeLLM), and reinforcement-learning frameworks for precision-medicine drug selection. The lab’s methodologies are intentionally generalizable, enabling spill-over benefits to domains such as social networks and system monitoring.

Publication Trends: Over the past four years Professor Ning has released a steady stream of high-impact articles spanning retrosynthesis planning, LLM instruction tuning for scientific domains, reinforcement learning for drug discovery, and COVID-19 health-analytics. These works repeatedly integrate cutting-edge AI techniques (deep RL, graph Transformers, large-scale instruction datasets) with rigorous experimental validation in chemistry and biomedicine.

Scientific Awards & Honors:

• Sanofi iDEA-TECH Award (2024)
• 10-Year Highest-Impact Award, International Conference on Data Mining (ICDM, 2020)

Grants & Collaborations: Funding includes the Sanofi iDEA-TECH Award and collaborative grants with Amazon Web Services for COVID-19 knowledge graphs. Her open-source datasets (ECInstruct, SMolInstruct, CTKG) and models (G2Retro, LlaSMol, eCeLLM) are publicly released on HuggingFace and GitHub, fostering broad academic and industrial adoption.

Labs & Teams: Professor Ning heads the Ning Lab at OSU, a multidisciplinary team focusing on AI/ML methodology and translational applications in health and medicine. The lab actively releases code and interactive web portals to accompany each major publication.