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
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Blog Post number 4
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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
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Blog Post number 2
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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
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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
Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video
We present Video2Sim2Real, a full-stack framework for learning dexterous robot skills from a single human manipulation video. The system reconstructs a simulator-ready digital twin, extracts object-centric keyframes and motion priors, optimizes robot configurations in simulation, and bridges the sim-to-real gap through imitation learning, residual reinforcement learning, and collision-aware motion planning. Across everyday manipulation tasks, Video2Sim2Real improves simulated success, safety, trajectory coherence, and real-world transfer over prior approaches.
Going with the Flow: Koopman Behavioral Models as Pseudo Planners for Visuo-Motor Dexterity
We introduce Unified Behavioral Models (UBMs), a framework for representing dexterous visuo-motor skills as coupled dynamical systems between visual flow and robot action flow. Our first instantiation, Koopman-UBM, models these behavioral dynamics as a structured latent linear system, enabling smooth long-horizon execution, efficient inference, and online replanning when observed visual flow deviates from prediction. Across simulated and real-world dexterous manipulation tasks, the method matches or outperforms strong diffusion- and transformer-based baselines while offering faster and more coherent execution.
Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory
Accepted by ACL 2026.
AI memory is increasingly important for long-term interactions with large language models, but existing RAG and Graph-RAG methods mainly rely on similarity-based retrieval. We propose Mnemis, a dual-route memory framework that combines fast System-1 similarity search with a System-2-style global selection mechanism over hierarchical memory graphs. By jointly retrieving semantically and structurally relevant memories, Mnemis improves long-term memory reasoning and achieves state-of-the-art performance on LoCoMo and LongMemEval-S benchmarks.
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
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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.