• Answer the growing concern of arthropod vectors that affect livestock across the animal industry, and biosecurity and food security more broadly.

• Provide critically needed training to graduate students that will bridge the gap for veterinary and public health.

• Expand research opportunities (NIH, USDA, DoD, and NBAF) in ticks, mosquitoes and Culicoides (i.e., biting midges), targeting vector species at local, national and international levels.

• Crop plant resistance to arthropod pests is a key global tactic to preserve crop yields and quality. Microbial symbionts often mediate arthropod virulence to plant resistance traits, host plant range of crop pests, and the behavior of beneficial arthropods (indirect plant resistance). Focus on research to help elucidate the complexity to improve crop productivity.
• Insect pollinators, such as bees and butterflies, of crops and wild plants are under threat due to factors such as land use change, pesticides, climate change, and other interacting factors. Conduct more interdisciplinary research on the nature and impacts of key factors affecting pollinator decline.

Be proponents of insects as food, urban food production, etc.

• Pest and pollinator management in urban food systems, expertise to lead educational efforts and research for safe and sustainable food production in urban areas.
• Explore insect farming for food and feed in response to climate change and shrinking food supplies for a growing global population.
• Farming insects for food has the potential to engage interdisciplinary expertise across campus and with industry partners, which could include but not limited to: microbiology, engineering, milling sciences, chemistry, food nutrition, physiology and biology.

We want to incorporate digital entomology and advanced analytics (modeling outbreaks, machine learning, big data, etc.) into all program areas (research, extension, and teaching).

• Advance research skills and teaching curriculum to include computational modeling using big data (e.g., remote sensing, citizen science, public data, sequencing)
• Increase teaching capacity in digital tools (e.g. R-stat, bioinfomatics, image analysis)
• Develop and apply tools using artificial intelligence, machine learning, and Computer Vision for automated data collection, monitoring, and analysis.