Thomas F. Burks, Ph.D., P.E.

Dr. Burks grew up on a 130-acre farm near Fort Knox, Kentucky, where they produced tobacco, corn, poultry and beef. He received his BS in Agricultural Engineering from the University of Kentucky in 1978. Upon completion, he began work with Chief Industries, first as Design Engineer and then as Engineering Manager. His primary responsibility was structural design of grain storage tanks and metal farm buildings.

He returned to UK in 1985 to begin concurrent Master's programs in Agricultural Engineering and Electrical Engineering. His main interests were electronics, control systems, and computer simulation. He completed his MS AE in 1989 with the thesis "Dairy Parlor Labor and Equipment Optimization Simulation Model."

In 1989, he began work with FMC Corporation in Madera, California. His unit at FMC's Food Processing Machinery Division conceived, designed, manufactured, installed and tested fully automated food processing equipment. While at FMC, he participated in the development of the Automated Batch Retort system. He was responsible for the control system development of the fully automated container handling system, which used 3-axis manipulators and palletizers to load and unload food product destined for the sterilizing retort.

In 1992 Dr. Burks returned to UK to finish his MS EE and then continued on as a research assistant, while he completed a PhD in Biosystems and Agricultural Engineering. His dissertation, delivered in 1997, was titled "Classification of Weed Species using Color Texture Analysis and Neural Networks." He stayed at the University of Kentucky until 2000 working as a Post-Doctoral Scholar on the development of a grain combine yield monitor test facility.

Dr. Burks' research interests are on the "machinery, instrumentation and control side of precision agriculture." Specifically, he intends to concentrate on autonomous vehicle applications in precision agriculture, robotic production and harvester applications in both field and green house agriculture. A central interest is machine vision and electrical controls. Since, machine vision gives machinery the flexibility and power to move beyond endless repetition of rigidly structured and ordered tasks, to tackle variable problems in an unstructured environment.

He comes as an assistant professor to our department from the University of Kentucky with a Ph.D. (1997) in Biosystems and Agricultural Engineering.