LTC Scott Hutchison Assistant Professor Electrical Engineering & Computer Science scott.hutchison [at] westpoint.edu About Education Research & Publications LTC Scott Hutchison graduated with an undergraduate degree in Computer Science Texas A&M University. He was branch detailed to the Infantry and served in the First Infantry Division as an infantry platoon leader and company executive officer, deploying to Baghdad, Iraq in support of OIC 06-08. His first assignment as a Signal Corps officer was as a Stryker Battalion S-6 for 1-14 Infantry Regiment, 25th ID. He deployed to Iraq again and took command and of 556th Signal Company for the remainder of his deployment. Upon returning to Hawaii, he relinquished command and worked as the 2nd SBCT Brigade Information Officer. He then served as an operational test officer for the WIN-T increment 2 equipment prior to its fielding across the Army. After earning his M.S. in Cyber Operations from the Air Force Institute of Technology, he served as an Instructor and Assistant Professor in the EECS Department at West Point. Then he served for 3 years in as the Deputy Division G6 for the First Infantry Division, including a 10 month rotation to Poland in support of NATO training and readiness exercises. He then obtained his Ph.D. in Computer Science from Kansas State University and returned as a faculty member in the EECS department at West Point. LTC Scott Hutchison is married to the former Amanda Baker from Deer Park, TX. They have four beautiful children together: Katherine, Thomas, Autumn, and David. Ph.D. in Computer Science - Kansas State University M.S in Cyber Operations - Air Force Institute of Technology B.S. in Computer Science - Texas A&M University Current Research High Performance Computing, Machine Learning, Parallel Programming, Student Cluster Competition Selected Publications Dissertation and Thesis Hutchison, S. (2024). Machine Learning for High Performance Computing Applications [Doctoral Dissertation, Kansas State University]. Krex. https://hdl.handle.net/2097/44307. Hutchison, S. (2015), Distributed Kernelized Locality-Sensitive Hashing for Faster Image Based Navigation [Master’s Thesis, Air Force Institute of Technology]. AFIT Scholar. https://scholar.afit.edu/etd/35.Journal Articles Hutchison, S., Andresen, D., Neilsen, M., Hsu, W., & Parsons, B. (2024). Optimized Hardware Procurement for High Performance Computing Systems. International Journal on Advances in Systems and Measurements, 17, no. 1&2, 46-55. https://www.iariajournals.org/systems_and_measurements/tocv17n12.htmlConference Publications Riffle, D., Andresen, D., Hutchison, S., & Hsu, W. (2024). Parallel Backfill: Improving HPC System Performance by Scheduling Jobs in Parallel. Practice and Experience in Advanced Research Computing 2024: Human Powered Computing, 1-4. https://dl.acm.org/doi/abs/10.1145/3626203.3670610Hutchison, S., Andresen, D., Neilsen, M., Hsu, W., & Parsons, B. (2024). Scheduling for high performance computing with reinforcement learning. Proceeding of OkIP International Conference on Advances in Parallel and Distributed Computing (APDC 2024). https://www.okipublishing.com/book/index.php/okip/catalog/book/40Hutchison, S., Andresen, D., Hsu, W., Neilsen, M., & Parsons, B. (2023). Optimized hardware configuration for high performance computing systems. In Proceedings of the 17th International Conference on Advanced Engineering Computing and Applications in Sciences (ADVCOMP 2023). International Academy, Research, and Industry Association. ISBN 978-1-68558-107-7. https://www.iaria.org/conferences2023/CfPADVCOMP23.html.Hutchison, S., Andresen, D., Neilsen, M., Hsu, W., & Parsons, B. (2022, September). High performance computing queue time prediction using clustering and regression. In International Conference on Parallel Processing and Applied Mathematics (pp. 260-272). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-031-30445-3_22Poster Presentations Hutchison S., Andresen D., & Hsu W (2022). High Performance Computing Scheduler Parameter Optimization using Simulation and Regression. Poster presented at SC22: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2022. https://sc22.supercomputing.org/program/posters/posters-gallery/Shopov, N., Jeong, M., Rude, E., Neseralla, B., Hutchison, S., Mentis, A., & Matthews, S. J. (2018, April). Investigating tensorflow for airport facial identification: poster. In Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security (pp. 1-1).