Hello there! I'm Jacob Buckman, currently a PhD candidate at MILA advised by Marc Bellemare and Doina Precup.
My primary research areas are deep learning and deep reinforcement learning. I'm especially interested in unifying theoretical reinforcement learning with practical deep-learning-based algorithms. My current work focuses on understanding generalization in neural networks, and how this interacts with computational decision-making.
I graduated from Carnegie Mellon University in 2017 with a Bachelor's in computer science and a Master's in Language Technologies, advised by Graham Neubig. From 2017-2018, I was a Google AI Resident in San Francisco.
I love to teach. If you want to learn about deep learning, get some guidance on a project, or just chat about AI in general, I'd be happy to help. Please schedule a meeting on BookTime.
Website template stolen with love from Desh.
My primary research areas are deep learning and deep reinforcement learning. I'm especially interested in unifying theoretical reinforcement learning with practical deep-learning-based algorithms. My current work focuses on understanding generalization in neural networks, and how this interacts with computational decision-making.
I graduated from Carnegie Mellon University in 2017 with a Bachelor's in computer science and a Master's in Language Technologies, advised by Graham Neubig. From 2017-2018, I was a Google AI Resident in San Francisco.
I love to teach. If you want to learn about deep learning, get some guidance on a project, or just chat about AI in general, I'd be happy to help. Please schedule a meeting on BookTime.
Website template stolen with love from Desh.