Trained as a biochemist, Tommi White has broad expertise in structural biology, enzymology, analytical imaging and protein design. She studied flavoenzyme structure-function using X-ray protein crystallography, where she was awarded Donald K. Anderson Outstanding Graduate Research Assistant. She was a Cancer Research Training Award recipient at the National Cancer Institute at NIH working towards developing neutralizing antibodies against viral envelope glycoproteins using cryo-electron microscopy.  Prior to joining Bayer Crop Science, Tommi lead the Electron Microscopy Core Research Facility as Director & Research Assistant Professor in Biochemistry at University of Missouri. While there, she significantly improved scientific capabilities, built strong relationships and fostered collaborations while mentoring numerous students, igniting their passion for electron microscopy to study their systems at the nanoscale. During her leadership, she co-authored over 40 publications, culminating in a $32M partnership with electron microscope manufacturer, ThermoFisher Scientific, adding 8 new electron microscopes and establishing University of Missouri's Electron Microscopy Core as the most powerful, cutting-edge electron microscopy facility in the Midwest.   Currently at Bayer Crop Science, Tommi is leading discovery’s molecular characterization of insecticidal and herbicide tolerance traits as the Structure & Mechanism Team Lead. She uses many tools to do this, including in silico folding while developing the Protein Science AI Strategy and driving innovation to implement new technologies. She interfaces with many parts of the organization and continues to build relationships through numerous leadership initiatives both internally and externally. She stays connected to the academic community through the University Mentoring Program by Bayer (B4U) which provides professional development to later stage graduate students and post-doctoral fellows through a year of 1:1 mentoring. Her talk will cover "AI‑Enabled Protein Design for Crop Traits" and how she and colleagues are using AI technologies to design next-gen protein traits for sustainable agriculture.