Ruihan Gao (高睿晗)

I am a 2nd-year PhD Student at Carnegie Mellon University, advised by Prof. Jun-Yan Zhu and Prof. Wenzhen Yuan. My research interests lie in the intersection of machine learning, tactile sensing, and haptic-rendering.

I received B.Eng.(Hons) in Electrical and Electronic Engineering from Nanyang Technological University, Singapore in 2020. After graduation, I joined A*STAR Institute for Infocomm Research (I2R) as a Research Engineer. I am grateful for Prof. Zhiping Lin who led me into academic research and I have spent great time working with Dr. Yan Wu and collegues at A*STAR on robotic tactile sensing projects.

I envision robots interacting with humans naturally and aspires to realize it with multi-modal perception and rendering powered by machine learning.

Email  /  CV  /  Github  /  Google Scholar  /  Linkedin

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Selected Publication
Controllable Visual-Tactile Synthesis
Ruihan Gao, Wenzhen Yuan, Jun-Yan Zhu,
ICCV, 2023
Webpage / Paper / Code / Data

We synthesize visual appearance and tactile geometry of different materials, given a handcrafted or DALL⋅E 2 sketch, and render the multi-modal output on a haptic screen called TanvasTouch.

Investigating Vision Foundational Models for Tactile Representation Learning
Ben Zandonati, Ruohan Wang, Ruihan Gao, Yan Wu,
arxiv, 2023

On Explainability and Sensor-Adaptability of a Robot Tactile Texture Representation Using a Two-Stage Recurrent Networks
Ruihan Gao*, Tian Tian*, Zhiping Lin, Yan Wu,
IROS, 2021

Supervised Autoencoder Joint Learning on Heterogeneous Tactile Sensory Data: Improving Material Classification Performance
Ruihan Gao, Tasbolat Taunyazov, Zhiping Lin, Yan Wu,
IROS, 2020

Fast Texture Classification Using Tactile Neural Coding and Spiking Neural Network
Tasbolat Taunyazov, Yansong Chua, Ruihan Gao, Harold Soh, Yan Wu,
IROS, 2020

Towards a Programming-Free Robotic System for Assembly Tasks Using Intuitive Interactions
Nicolas Gauthier, Wenyu Liang, Qianli Xu, Fen Fang, Liyuan Li, Ruihan Gao, Yan Wu, Joo Hwee Lim
ICSR, 2021.

Classification of Non-tumorous Facial Pigmentation Disorders Using Generative Adversarial Networks and Improved SMOTE
Jiawei Peng, Ruihan Gao, Steven Thng, Weimin Huang, Zhiping Lin,
IEEE Engineering in Medicine & Biology Society (EMBC), 2021.

Runtime-safety-guided policy repair
Weichao Zhou, Ruihan Gao, Kim BaekGy, Eunsuk Kang, Wenchao Li,
RV, 2020

Biomedical image classification based on a feature concatenation and ensemble of deep CNNs
Long D. Nguyen, Ruihan Gao, Dongyun Lin, Zhiping Lin,
Journal of Ambient Intelligence and Humanized Computing, 2019.

Classification of Non-Tumorous Facial Pigmentation Disorders using Deep Learning and SMOTE
Ruihan Gao, Jiawei Peng, Nguyen Long, Yunfeng Liang, Steven Thng, Zhiping Lin,
ISCAS, 2019.

Classification of Non-Tumorous Facial Pigmentation Disorders Using Improved SMOTE and Transfer Learning
Jiawei Peng, Ruihan Gao, Nguyen Long, Yunfeng Liang, Steven Thng, Zhiping Lin,
ISCAS, 2019.

* denotes equal contribution

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