Guanya Shi 石冠亚

I am a G2 PhD student at the Department of Computing and Mathematical Sciences in Caltech, advised by Prof. Soon-Jo Chung and Yisong Yue. I am also a member of the Center for Autonomous Systems and Technologies. I also collaborate with Prof. Anima Anandkumar and Joel Burdick. Currently I am working on intersection of machine learning and control theory, and their applications on robotics.

I did my bachelors at Tsinghua University. In summer 2016, I was fortunate enough to be selected into Stanford UGVR program and worked with Prof. Sindy Tang. I've also spent time at Sensetime as deep learning research intern, supervised by Jianping Shi.

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News: Our work on Neural Lander was presented in Physics Workshop at NeurIPS 2018.

Research

I'm interested in machine learning, control theory, aerial robotics and bio-inspired systems.

Neural Lander: Stable Drone Landing Control using Learned Dynamics
Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
submitted to International Conference on Robotics and Automation (ICRA), 2019
[Highlighted by Import AI]

We present a novel deep-learning-based robust nonlinear controller for stable quadrotor control during landing. Our approach blends together a nominal dynamics model coupled with a DNN that learns the high-order interactions, such as the complex interactions between the ground and multi-rotor airflow. To the best of our knowledge, this is the first DNN-based nonlinear feedback controller with stability guarantees that can utilize arbitrarily large neural nets. [Video]

Drag Reduction in a Natural High-Frequency Swinging Micro-Articulation: Mouthparts of the Honey Bee
Guanya Shi, Jianing Wu, Shaoze Yan
Journal of Insect Science, 2017

My undergraduate work about biomechanics. I studied how a honeybee drinks water and showed that honeybee's drinking strategy is optimal.

How to dip nectar: optimal time apportionment in natural viscous fluid transport
Jianing Wu, Guanya Shi, Yiwei Zhao, Shaoze Yan
Journal of Physics D: Applied Physics, 2018

It is also my undergraduate work about biomechanics and bio-inspired robotics.


Course Projects
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Teaching Mario to Play Mario: Reinforcement Learning on Super Mario Bros.
Guanya Shi, Botao Hu, Yan Wu


Final project of Caltech CS 159. We present a deep learning model to successfully learn control policies from high-dimensional input data using reinforcement learning. The model is based on the idea of Deep Q-Network (DQN), with convolutional neural network trained by Q-learning algorithm, whose input is tile representation of the screen and output is a value estimation function. Also, replay buffer, target network and double Q-learning are applied to lower data dependency and approximate real gradiant descent.


Hobbies

I love playing basketball, soccer and MOBA games. I am also very interested in photography, hiking, travelling and cooking. Here are some pictures by me.

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Winter Tsinghua Santa Monica, California
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Beijing National Stadium Taipei
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Wudaokou, Beijing Tokugawaen, Nagoya, Japan
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Odaiba, Tokyo Yosemite, California


Based on this website.