Jesse Wood

LTC Jesse Wood

Senior Instructor

Electrical Engineering & Computer Science

jesse.wood [at] westpoint.edu
Lieutenant Colonel Jesse Wood was commissioned as a Field Artillery officer in 2004 upon graduation from the University of Kansas with a B.S. in Computer Science. In his first assignment, he served as a Company Fire Support Officer in Charlie Company, 1st Battalion, 72nd Armored Regiment at Camp Casey, Republic of Korea. He then served as an Assistant Logistics Officer, Platoon Leader, and Company Fire Support Officer in the 3rd Battalion, 82nd Field Artillery Regiment at Fort Hood, Texas. After attending the Aviation Captain's Career Course, he served in Hawaii as a Brigade Assistant Fire Support Officer for the 25th Combat Aviation Brigade, Squadron Fire Support Officer for 3rd Squadron, 4th Cavalry Regiment, and Battery Commander of A Battery, 3rd Battalion, 7th Field Artillery Regiment. Following command, he served as the Battalion Operations Officer for 3rd Battalion, 353rd Field Artillery Regiment at Fort Polk, Louisiana. He then transitioned to Functional Area (FA) 24 (now known as 26A), serving as a Network Systems Engineer for 21st Signal Brigade at Fort Detrick, Maryland and as a Joint Test Officer for the Joint Interoperability Test Command, Fort Huachuca, Arizona. Most recently, he earned an M.S. degree in Computer Science from North Carolina State University and was assigned as an instructor at the United States Military Academy. His operational deployments include two tours in support of Operation Iraqi Freedom and one tour in support of Operation Enduring Freedom.

M.S. in Computer Science - North Carolina State University

 

M.S. in Administration (Information Resource Management) - Central Michigan University

 

B.S. in Computer Science - University of Kansas

Research Interests

Computer Vision, Natural Language Processing

Selected Publications

Matsuda, N., Wood, J., Shrivastava, R., Shimmei, M., & Bier, N. (2022). Latent Skill Mining and Labeling from Courseware Content. Journal of Educational Data Mining, 14(2), 1-31.

Matsuda, N., Shimmei, M., Chaudhuri, P., Makam, D., Shrivastava, R., Wood, J., & Taneja, P. (2023). PASTEL: Evidence-based learning engineering methods to facilitate creation of adaptive online courseware. In F. Ouyang, P. Jiao, B. M. McLaren & A. H. Alavi (Eds.), Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology (pp.93-108). New York, NY: CSC Press.

Shafer, E., Wood, J., Street, S., Crow, E., Lu, C. (2023). Social Bias and Image Tagging: Evaluation of Progress in State-of-the-Art Models. In Bebis, G., et al. Advances in Visual Computing. ISVC 2023. Lecture Notes in Computer Science, vol 14362. Springer, Cham.