Jiye Shi is a Vice President at Eli Lilly and Company, where he oversees Computational Chemistry, Cheminformatics, Structural Biology, and Global Sample Management. Jiye began his career in 2001 with the computational design of antibodies and is credited as a co-inventor of Bimekizumab, as well as the machine learning algorithm that facilitated its design. His responsibilities later expanded to include small molecule drug discovery, leveraging both physics-based and AI/ML approaches.

Jiye earned his PhD in Computational Structural Biology under Prof. Sir Tom Blundell at the University of Cambridge and completed his executive MBA training at the University of Rochester. He has co-authored over 200 scientific papers and holds 11 patents, which have led to two approved drugs on the market. Jiye also serves as an external advisor to the Department of Statistics at the University of Oxford.

Before joining Eli Lilly, Jiye was a NewMedicines Fellow and Global Head of CADD (Computer-Aided Drug Design) at UCB Pharma. Over the past decades, he and his teams have utilized physics, statistics, and AI/ML-based methods to accelerate the discovery of small molecule and antibody therapeutics.

Jiye's work exemplifies the integration of cutting-edge technology with strategic foresight. Under his leadership, Eli Lilly has seen remarkable advancements in computational design and automation platforms, enhancing operational efficiency and expanding the scope of chemical exploration. His commitment to innovation is evident in his efforts to streamline drug discovery pipelines, making them more efficient and effective.

Beyond his technical achievements, Jiye is passionate about graduate training and has helped establish and manage doctoral training centers in the UK. He holds visiting academic appointments in several countries and actively participates in graduate training programs, fostering the next generation of scientists.

Jiye's leadership in integrating artificial intelligence and machine learning with other computational approaches has significantly accelerated the discovery of small molecule drug candidates. These technologies have expanded the capability to design novel molecules, suggest synthesis methods, and improve operational efficiency in testing these molecules. The accelerated learning cycles enabled by AI/ML allow for the exploration of broader chemical space and the pursuit of bolder ideas.

Jiye's vision and dedication have not only propelled scientific progress but also inspired many in the field.