Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
Published:
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Restoring Noisy Demonstration for Imitation Learning With Diffusion Models
Published in IEEE Transactions on Neural Networks and Learning Systems, 2026
Most imitation learning methods assume perfect expert demonstrations, yet real data is often noisy. We propose a filter-and-restore framework that isolates clean samples and uses conditional diffusion models to recover noisy demonstrations. Experiments on robot arm manipulation, dexterous manipulation, and locomotion show consistent improvements over existing methods, with ablations confirming robustness to diverse noise types and levels.
Less Tuning, Better Planning: Simplifying Offline Model-Based Planning
Published in ICML 2026 workshop on Decision-Making from Offline Datasets to Online Adaptation: Black-Box Optimization to Reinforcement Learning, 2026
Offline model-based planning can adapt policies at test time, but performance depends on a planning horizon and action proposer that are often tuned online. We propose SHARP (Soft Horizon AggRegation for Planning), which weights multi-horizon returns by ensemble dynamics uncertainty to avoid fixed-horizon tuning. SHARP-BC pairs this with a simple behavior-cloning action proposer, matching or beating baselines with less hyperparameter search.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.