Publications
Yik, W., Sonnewald, M., Clare, M. C. A., Lguensat, R. (2023). Southern Ocean Dynamics Under Climate Change: New Knowledge Through Physics-Guided Machine Learning. NeurIPS Workshop: Tackling Climate Change with Machine Learning. https://arxiv.org/abs/2310.13916
Hom, C., Yik, W., Montanez, G. D. (2023). Finite-Sample Bounds for Two-Distribution Hypothesis Tests. IEEE International Conference on Data Science and Advanced Analytics (DSAA). https://doi.org/10.1109/DSAA60987.2023.10302643
Yik, W., Silva, S. J., Geiss, A., Watson-Parris, D. (2023). Exploring Randomly Wired Neural Networks for Climate Model Emulation. Artificial Intelligence for the Earth Systems (AIES). https://doi.org/10.1175/AIES-D-22-0088.1
Yik, W., Silva, S. J., Geiss, A., Watson-Parris, D. (2022). Exploring Randomly Wired Neural Networks for Climate Model Emulation. NeurIPS Workshop: Tackling Climate Change with Machine Learning. https://www.climatechange.ai/papers/neurips2022/36/paper.pdf
Yik, W., Serafini, L., Lindsey, T., Montanez, G. D. (2022). Identifying Bias in Data Using Two-Distribution Hypothesis Tests. AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES). https://doi.org/10.1145/3514094.3534169
Awards
Department of Energy Computational Science Graduate Fellowship, 2024
American Meteorological Society Graduate Fellowship, 2024
Donn Chamberlin Computer Science Research Award, 2024
National Science Foundation Graduate Research Fellowship (declined), 2024
Finalist, Hertz Fellowship, 2023
Finalist, Computing Research Association Outstanding Undergraduate Researcher Award, 2023
National Oceanic and Atmospheric Administration Ernest F. Hollings Scholarship, 2022