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Amy Peerlinck



Ph.D., Montana State University, Computer Science, 2023
M.S., Montana State University, Computer Science, 2019
B.A., Karel de Grote College/University, Information Science, 2016
B.A., University of Antwerp, Applied Linguistics, 2013


I was born and raised in Belgium, where I finished two bachelor’s degrees in linguistics and information science. The second of these degrees brought me to Bozeman, MT for an internship in full stack development for a start-up company. Bozeman opened my eyes to the fact that mountains can still be wild and not filled with gondolas and bars (looking at you, Alps). The internship in Bozeman made me decide to pursue a master’s in computer science at MSU, which eventually turned into a Ph.D. As I was working through my graduate degrees, I discovered a love for teaching. Watching a student make sense of an algorithm or a buggy piece of code felt more rewarding than any paper publication. All of that to say, I’m happy to be here at Western!

What most excites you about your field?

I love how much machine learning, and computer science in general, is constantly changing and evolving, allowing for never ending opportunities to learn.

What is your favorite thing about the Gunnison Valley?

The access to the outdoors.

Courses Taught

Fall 2023

  • CS 190 Computer Science I
  • CS 220 Data Analytics
  • CS 235 Networks

Spring 2024

  • CS 120 Professional Computer Skills
  • CS 191 Computer Science II
  • CS 397 Special Topics


  • A. Peerlinck and J. Sheppard. “AdaBoost with Neural Networks for Yield and Protein Prediction in Precision Agriculture,” International Joint Conference on Neural Networks, July 2019.
  • A. Peerlinck, J. Sheppard, J. Pastorino and B. Maxwell. “Optimal Design of Experiments for Precision Agriculture Using a Genetic Algorithm,” Conference on Evolutionary Computation, IEEE, June 2019.
  • E. Pryor, A. Peerlinck, and J. Sheppard. “A study in overlapping factor decomposition for cooperative co-evolution,” Symposium Series on Computational Intelligence, IEEE, 2021.
  • A. Peerlinck, and J. Sheppard. “Multi-Objective Factored Evolutionary Optimization and the Multi-Objective Knapsack Problem,” World Conference on Computational Intelligence, IEEE, July 2022.
  • A. Peerlinck, and J. Sheppard. “Addressing Sustainability in Precision Agriculture via Multi-Objective Factored Evolutionary Algorithms,” Metaheuristics International Conference, July 2022.

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