Regular biography
Siamak Ravanbakhsh is a faculty member in the Department of Computer Science at McGill University. His research focuses on Machine Learning. He can be contacted via email at siamak@cs.mcgill.ca or through his website at https://www.cs.mcgill.ca/~siamak/.
Scholar-generated biography
Siamak Ravanbakhsh is an Associate Professor at McGill University, specializing in AI and Machine Learning. His research focuses on developing deep learning models that are equivariant to transformations, enabling robust and interpretable representations for complex data. He has contributed to areas such as deep sets, point cloud processing, and physics-informed neural networks. His work includes applications in cosmology, galaxy simulations, and NMR spectral analysis, emphasizing the integration of domain knowledge into machine learning frameworks. Ravanbakhsh's research aims to enhance the generalization and efficiency of deep learning models through symmetry-aware design.