I’m a PhD student in the MIB Lab at Queen’s University.
Previously astrophysics, now machine learning. I study deep learning and neuroevolution with the goal of building more interpretable models for biomedicine.
On the theoretical side, I’m working on ways to discover interactions in complex networks in order to build better models. Can we identify functional subnetworks in a neural network and reuse them? How can we better locate clusters of genes responsible for different diseases?
On the applied side, I’ve built models for a range of applications (time series, graph, CV) using different frameworks (PyTorch, TensorFlow, scikit-learn). I prefer PyTorch but I’ll learn whatever tool makes the most sense.