Yilun Hao

I am a second year graduate student in the Department of Aeronautics and Astronautics at MIT working in REALM lab led by Prof. Chuchu Fan. My research interest lies in the area of foundation models and robotics.

Previously I received my M.S. in Computer Science with Distinction in Research from Stanford University. I worked with Prof. Dorsa Sadigh at ILIAD and Prof. Jiajun Wu at SVL on robotics and machine learning.

I received my B.S. in Computer Science and a minor in Mathematics from University of California San Diego, where I worked on Hyperdimensional Computing supervised by Prof. Tajana Rosing

Email / CV / Linkedin / Google Scholar / Github

Recent Research (Foundation Models and Robotics)

	Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming Yilun Hao, Yang Zhang, Chuchu Fan Under review Website /arXiv
	Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools Yilun Hao, Yongchao Chen, Yang Zhang, Chuchu Fan Under review Website /arXiv
	PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Preference Alignment Yongchao Chen, Jacob Arkin, Yilun Hao, Yang Zhang, Nicholas Roy, Chuchu Fan Empirical Methods on Natural Language Processing (EMNLP Main), 2023 Oral (3.4%) Website /arXiv
	Gesture-Informed Robot Assistance via Foundation Model Li-Heng Lin, Yuchen Cui, Yilun Hao, Fei Xia, Dorsa Sadigh Proceedings of the 7th Conference on Robot Learning (CoRL), 2023 Website /arXiv
	NOIR: Neural Signal Operated Intelligent Robot for Everyday Activities Ruohan Zhang, Sharon Lee, Minjune Hwang, Ayano Hiranaka, Chen Wang, Wensi Ai, Jin Jie Ryan Tan, Shreya Gupta, Yilun Hao, Gabrael Levine, Ruohan Gao, Anthony Norcia, Li Fei-Fei, Jiajun Wu Proceedings of the 7th Conference on Robot Learning (CoRL), 2023 Website /arXiv
	Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations Yilun Hao, Ruinan Wang, Zhangjie Cao, Zihan Wang, Yuchen Cui, Dorsa Sadigh Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023 Website /arXiv
	A Dual Representation Framework for Robot Learning with Human Guidance Ruohan Zhang, Dhruva Bansal, Yilun Hao, Ayano Hiranaka, Jialu Gao, Chen Wang, Roberto Martín-Martín, Li Fei-Fei, Jiajun Wu Conference on Robot Learning (CoRL), 2022* Website /arXiv
	Weakly Supervised Correspondence Learning Zihan Wang, Zhangjie Cao, Yilun Hao, Dorsa Sadigh International Conference on Robotics and Automation (ICRA), 2022 Website / arXiv
	Learning Feasibility to Imitate Demonstrators with Different Dynamics Zhangjie Cao, Yilun Hao, Mengxi Li, Dorsa Sadigh Conference on Robot Learning (CoRL), 2021 Website / arXiv

Previous Research (Hyperdimensional Computing)

Stochastic-HD: Leveraging Stochastic Computing on the Hyper-Dimensional Computing Pipeline
Justin Morris, Yilun Hao, Saransh Gupta, Behnam Khaleghi, Baris Aksanli, Tajana Rosing
Frontiers in Neuroscience, 2022
arXiv

Stochastic-HD: Leveraging Stochastic Computing on Hyper-Dimensional Computing
Yilun Hao, Saransh Gupta, Justin Morris, Behnam Khaleghi, Baris Aksanli, Tajana Rosing
IEEE 39th International Conference on Computer Design (ICCD), 2021
arXiv

Multi-label HD Classification in 3D Flash
Justin Morris, Yilun Hao, Saransh Gupta, Ranganathan Ramkumar, Jeffrey Yu, Mohsen Imani, Baris Aksanli, Tajana Rosing
IFIP/IEEE 28th International Conference on Very Large Scale Integration (VLSI-SOC), 2020
arXiv

Locality-Based Encoder and Model Quantization for Efficient Hyper-Dimensional Computing
Justin Morris, Roshan Fernando, Yilun Hao, Mohsen Imani, Baris Aksanli, Tajana Rosing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020
arXiv

Thanks Jon Barron for the template!