Today's problems cannot be solved if we continue to think the way we thought when we created them.
The world's human population is expected to grow past 9.7*10^9 by 2050 , and our global temperature is expected to increase by at least 1.5C in the same time frame relative to preindustrial levels. Our agricultural production is expected to fall short of global demand in the coming years as the global population swells and living standards rise. Agricultural technology must keep pace if we are to sustain 10B people.
I focus on climate impacts on global food security. By developing new statistical theory and computational methods, we have a chance to get ahead of climate change before it makes feeding the planet impossible.
How do we use genomic, sensor, and high throughput phenotype data to build better models and predictions for biological systems? Recent advances in computing, mathematics, molecular and systems biology are enabling the kind of cross-scale, cross-discipline synergy these insights need to emerge.
Here at Davis, I'm building collaborations between plant science, agricultural economics, and statistics to understand where our crops will grow in increasingly unstable environments. Currently, I'm working on simulations of global crop distributions and how these distributions react to different climate scenarios.
Peoples' genomes, their locations, and conversations are all private. This privacy must be respected by practitioners, enforced by government, and watched diligently by third parties. A good primer can be found here. In addition to privacy concerns, considerably more pressing is the proper democratization of new data technologies.