Mohamad H. Danesh

PhD student, McGill University

Joined

July 2020

Names

Mohamad H. Danesh (Preferred)

Mohamad Hosein Danesh

Emails

****@oregonstate.edu (Confirmed)

****@gmail.com (Confirmed)

****@mail.mcgill.ca (Confirmed)

****@mila.quebec (Confirmed)

Personal Links

Homepage

Google Scholar

DBLP

Career & Education History

PhD student

McGill University (mcgill.ca)

2023 – Present

MS student

Oregon State University (oregonstate.edu)

2019 – 2021

Advisors, Relations & Conflicts

PhD Advisor

Hsiu-Chin Lin

2023 – Present

Expertise

Robotics

2023 – Present

Planning

2021 – Present

Reinforcement learning

robustness

2020 – Present

Reinforcement learning

interpretability

2019 – Present

Reinforcement learning

2018 – Present

Publications

YRC-Bench: A Benchmark for Learning to Coordinate with Experts
Mohamad H. Danesh, Khanh Xuan Nguyen, Tu Trinh, Benjamin Plaut
- Accepted by TMLR
- Readers: Everyone
Contractive Diffusion Policies
Amin Abyaneh, Charlotte Morissette, Mohamad H. Danesh, Anas Houssaini, David Meger, Gregory Dudek, Hsiu-Chin Lin
- ICLR 2026 Poster
- Readers: Everyone
Mitigating Distribution Shifts: Uncertainty-Aware Offline-to-Online Reinforcement Learning
Mohamad H. Danesh, Maxime Wabartha, Joelle Pineau, Hsiu-Chin Lin
- Submitted to ICLR 2025
- Readers: Everyone
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad Hosein Danesh, Cyril Roumegous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João Guilherme Madeira Araújo, Guorui Quan, Daniel Chee Hian Tan, Timo Klein, Rujikorn Charakorn, Mark Towers et al. (13 additional authors not shown)
- Submitted to NeurIPS 2024 Track Datasets and Benchmarks
- Readers: Everyone
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning
Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
- AAAI 2024
- Readers: Everyone
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad H. Danesh, Cyril Roumégous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João G. M. Araújo, Guorui Quan, Daniel Tan, Timo Klein, Rujikorn Charakorn, Mark Towers et al. (13 additional authors not shown)
- CoRR 2024
- Readers: Everyone
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions
Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Fuxin Li
- CoRR 2024
- Readers: Everyone
Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning
Guy Azran, Mohamad Hosein Danesh, Stefano Albrecht, Sarah Keren
- GenPlan'23
- Readers: Everyone
Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning
Guy Azran, Mohamad Hosein Danesh, Stefano V Albrecht, Sarah Keren
- PRL 2023 IJCAI Withdrawn Submission
- Readers: Everyone
Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning
Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
- CoRR 2023
- Readers: Everyone

View all 21 publications

Co-Authors

View all 61 co-authors