Mohamed Elsayed
Dept. of Computing Science, University of Alberta
I am a PhD student at the RLAI lab working with Rupam Mahmood and affiliated with Amii. I develop general mechanisms for continual learning, focusing on enabling deep reinforcement learning methods to learn from continuous streams of experience, particularly for resource-constrained embodied agents.
Prior to this, I completed my master's degree from the University of Alberta and I completed my bachelor's degree in Communication and Information Engineering from Zewail City of Science and Technology, Egypt.
Taking photos is something I enjoy doing when I have some free time. You can check out the world as I see it from here. I also love observing how animals behave and interact with their environments, especially those intelligent ravens.
news
| Oct 18, 2024 | I am excited to share that our paper on streaming deep reinforcement learning is now released! You can check the code from here. |
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| Sep 25, 2024 | Our paper led by Gautham Vasan on deep policy gradient methods without batch updates, target networks, or replay buffers is accepted at NeurIPS 2024. |
| May 15, 2024 | Our paper on the role of weight clipping for deep continual and reinforcement learning is accepted at RLC 2024. |
| May 1, 2024 | Our paper on revisiting scalable Hessian diagonal approximations for applications in reinforcement learning is accepted at ICML 2024. |
| Jan 16, 2024 | Our paper on loss of plasticity and catastrophic forgetting is accepted at ICLR 2024. |
| Sep 1, 2022 | Started my PhD in continual representation learning. |
| May 13, 2022 | Defended my MSc thesis on online representation search. |
| Dec 31, 2020 | Finished my internship at Huawei, Edmonton (see this NeurIPS workshop paper for a summary) |
| May 1, 2020 | Started my internship at Huawei, Edmonton. |