Our problems are divided in two groups: applied research, and fundamental research.
Applied research problems are ideal for students looking to develop their expertise in machine learning and deep learning while doing novel work and having a meaningful impact on the world.
Fundamental research problems are ambitious and important problems for which no solution exists today, and which may not even be fully solvable in the near future.
Applied research problemsCardiac MRI Segmentation
Develop a system capable of automatic segmentation of the right ventricle in images from cardiac magnetic resonance imaging (MRI) datasets.Identifying biomedical articles at risk for retraction
Develop a model to analyze the content of new biomedical articles to determine the likelihood of fraud or scientific error.Photorealistic post-processing of rendered 3D scenes
Develop a model (similar to a super-resolution model) capable of enhacing the realism of 3D-rendered scenes.Smart data augmentation with generative models
Use GANs and other generative models to develop better data augmentation techniques for computer vision models.Social media botnet detection and analysis
Analyze political botnet activity on Twitter and develop effective counter-measures.Subpixel CNN in Upsampling Applications
Improve segmentation models and generative models by using a subpixel CNN as the upsampling operation.Chromosome Segmentation
Develop a specialized visual segmentation model to help cytogeneticists conduct research.
Fundamental research problemsLayer-wise supervised incremental training of residual networks
Explore techniques for training supervised residual networks in a layer-by-layer fashion, rather than end-to-end.Machine learning in non-stationary environments
Explore techniques for developing models that can perform well on data that significantly differs from the training data.Multitask and Transfer Learning
Benchmark and build RL architectures that can do multitask and transfer learning.Music generation based on surprise optimization
Use neuroscience and deep learning to generate music that pushes the right buttons in our brains.