BIO

I am a PhD student in the Biomedical Engineering Department. I received my undergraduate degree from Oregon State University in Bioengineering where I conducted research in computational chemistry under Dr. Cory Simon. After graduating, I worked at the NIH as a post-bac at the NCI Program for Natural Product Discovery (NPNPD). Here, I worked in an automation lab running, troubleshooting, and programming various robotic equipment and creating computer programs to assist the lab. Outside of academic activities, I like to make music, graphic design, and climb.

Current Work

I am interested in leveraging sophisticated machine learning techniques to understand complex behaviors in animals. My research focuses on applying graph neural networks to two key areas: 1) Mosquito Behavior: Using graph-based models to decode how odors are processed in the mosquito brain, with the goal of facilitating the discovery of effective repellents. 2) Glassfish Schooling Dynamics: Exploring how graph neural networks can analyze schooling fish data to uncover patterns and insights into their collective behavior. By bridging machine learning and neuroscience, I aim to contribute to innovative solutions and deepen our understanding of complex biological systems.

Publications and presentations

Publications

• McConachie, G.D., Duniec, E., Guerina, F.V., Younger, M.A., DePasquale, B. (2026). Low rank adaptation of chemical foundation models generates effective odorant representations. International Conference on Learning Representations (ICLR) 2026. preprint

Presentations

• McConachie, G.D., Duniec, E., Guerina, F.V., Younger, M.A., DePasquale, B. (2025). Learning the Language of Smell: Foundation Models for Protein-Odor Interactions. Frontiers in NeuroAI, Kempner Institute at Harvard University, Cambridge, MA.
• McConachie, G.D., Duniec, E., Guerina, F.V., Younger, M.A., DePasquale, B. (2024). Improved Odor-Receptor Interaction Predictions via Self-Supervised Learning. Neuroscience to Artificially Intelligent Systems (NAISys), Cold Spring Harbor Laboratory, NY. poster
• McConachie, G.D., Younger, M.A., DePasquale, B. (2024). A Graph Neural Network Self Supervised Learning Approach to Generate a Meaningful Chemical Latent Space for Olfactory Tasks. AChems 2024, Bonita Springs, FL.
• McConachie, G.D., Younger, M.A., DePasquale, B. (2024). Graph neural network guided in silico deorphanization technique for olfactory receptors. Cosyne 2024, Lisbon, Portugal. poster