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BIO Distinguished Lecture: Scott Jackson and Ethan Pickering

About the series

The U.S. National Science Foundation hosted a Distinguished Lecture from Scott Jackson and Ethan Pickering of Bayer Crop Sciences.

This lecture was sponsored by the Directorate for Biological Sciences and the Division of Molecular and Cellular Biosciences.

A recording and transcript file are linked below.

From Art to Empiricism: Bridging AI and Biology in Plant and Animal Breeding
Plant and animal breeding is a long-standing discipline, predating Mendel’s description of inheritance. In recent years, this discipline has evolved rapidly from a scientific ‘art’ to one that is almost entirely empirical and integrates engineering, mathematical modeling, and data sciences. The primary drivers have come in low-cost, high-throughput data collection and low-cost, high-compute resources that, together, have ushered in new modeling frontiers, e.g. Artificial Intelligence (AI), in plant and animal breeding. Often the core tenets of AI modeling and biological sciences appear to oppose each other, prediction versus interpretability, but this need not be the case. Indeed, the flexibility and creativity afforded by AI approaches permits the embedding of biological domain knowledge and stands to maximize both prediction and interpretability. We will argue this case with two examples, resistance-preserving loss functions for disease prediction and Biology-Informed Graph Neural Networks that embed concepts such as gene ontology terms and gene expression into its architecture. While exciting developments, the convergence of AI and Biology has rapidly shifted the talent profile ideal for progress and has reshaped greater opportunities for public-private opportunities. We will discuss our journeys from academic to industry, shifts in the types of science supporting plant/animal improvement and hopefully have a robust discussion.



Scott Jackson, PhD
Dr. Scott Jackson is the Genetic Pipeline Design Lead at Bayer Crop Science. He received his MS and PhD degrees from the University of Wisconsin-Madison followed by a fellowship at the University of Minnesota. He has held faculty positions at Purdue University (2001-2011) and the University of Georgia where he was the Georgia Research Alliance Eminent Scholar in Plant Functional Genomics (2011-2019). He is currently an adjunct professor at the University of Georgia. At the University of Georgia he led the Center for Applied Genetic Technologies and was involved in many campus-wide activities.

Scott’s research has focused on decoding plant genomes to better understand their evolutionary histories and how to better engineer crop plants for the future. He led several genome sequencing efforts (e.g. soybean, peanut, common bean) and has been involved in translating genome sequences into advances in understanding the structure and function of plant genomes with a focus on genome duplications common in plant histories.


Ethan Pickering, PhD
Dr. Ethan Pickering leads the AI Genomics Modeling Team at Bayer Crop Science and is a lecturer at the Massachusetts Institute of Technology (MIT) in mechanical engineering. His work focuses on building novel AI models, architectures, loss functions, and active learning approaches for challenges in genomic design of crops. While he grew up on a family vegetable farm in Ohio, his professional career did not include any biology prior to joining Bayer Crop Science. He was a post-doctoral scholar at MIT in mechanical engineering developing AI to predict rare and extreme events in physics and received his B.S. in mechanical engineering at Case Western Reserve University and a MS and PhD from the California Institute of Technology (Caltech). Returning to his roots in agriculture, he has found a passion in synthesizing an outside mathematical perspective with the modeling challenges facing agriculture and biology

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