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Pages
➣ Hi, this is Charles!
About me
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Posts
blogs
experience
➣ Teaching Assistant
Mathematics, Statistics and Computer Science Department, Macalester College, Spring 2020 - PRESENT 2020
Teaching Assistant(Preceptor) in COMP 394 Reinforcement Learning, MATH 378 Complex Analysis, COMP 128 Data Structure, STAT/COMP 112 Intro to the Data Science at Macalester College
➣ Computer Vision Research Intern
Research and Development Department, Thorough Images, Spring 2021
Full time research internship for learning, understanding, developing, and optimizing computer vision models to complete intelligent solutions for pathological images at Thorough Images.
➣ Computer Vision Research Intern
Research and Development Department, Thorough Images, Spring 2021
Full time research internship for learning, understanding, developing, and optimizing computer vision models to complete intelligent solutions for pathological images at Thorough Images.
➣ Geometric Measure Theory Researcher
Mathematics, Statistics and Computer Science Department, Macalester College, Summer 2021
Summer research with professor Lisa Naples at Macalester College.
➣ DRL Research Intern
PRIOR Group, Allen Institute for Artificial Intelligence (AI2), Fall 2021 - Spring2022
Research Intern at AI2 mentored by Luca Weihs
honors
notes
➣ Baselines Experiments and Tutorials in AllenAct
      
 </p>
Contribute codes for baseline experiments and pretrained models of various of MuJoCo environments to the project of AllenAct, and provide a Tutorial.
</article> </div>
➣ Notes for Generative Adversarial Imitation Learning (GAIL)
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Notes For Paper Generative Adversarial Imitation Learning (GAIL)
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➣ Configure Dual-Boot Linux (Manjaro) to the Laptop (Blade 15 2022) for Everything
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It is crazy to configure Linux to a latest released laptop, especially for a newbie to the hardware and system (like me), so I would like to share my major configurations journal here for others (and just in case I need to rebuild everything if it is crashed in the future…)
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projects
➣ Design and Optimization of Comb Drive Accelerator for High Frequency Oscillation
      
 COMSOL</p>
This project is mentored by Albert Chen at UCLA and the final paper was published.
In this work, using COMSOL and MATLAB, a finite element code was used for the design, optimization and visualization of a comb drive accelerator.
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➣ Mathematical Modeling for Drone Light Show
      
 MATLAB</p>
This is the final paper for the 20th Annual High School Mathematical Contest in Modeling (HiMCM), problem A.
Using MATLAB, I built models to determine the required number of drones and every drone’s initial location during the process. Any simple pictures or icons could be designed for the drone show by my MATLAB program.View PDF
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➣ House Price Prediction
      
 Python</p>
This is the first practice for machine learning and for Kaggle competition: House Prices: Advanced Regression Techniques. Using Ridge, Lasso, LGBM, XGB, Stacking CV Regressor, and etc, to reach Score(mean absolute error): 11977.59807; 13th place out of 19,465 teams (0.06%) For more information, please see my project directly or visit my Github Repository.
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➣ Area Coverage with Unmanned Aerial Vehicles Using Reinforcement Learning
       Python</p>
2020 Summer Research with professor Esra Kadioglu Urtis, and students Aaron Gould, Elisabeth Landgren, and Fan Zhang at Macalester College. We developed and implemented reinforcement learning based algorithms with simulations and a gym environment for coverage path planning for multiple drones using Actor Critic using Kronecker-Factored Trust Region (ACKTR) deep reinforcement learning method provided by Stable Baselines(OpenAI) in Python(My Reseaerch Report, My Github Repository).
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➣ The Power of Topological Data Analysis for Machine Learning
       Python</p>
This is the project for the capstone course MATH 471 Topology at Macalester College, discussing the power of topological data analysis for machine learning. Due to the time limit, the test for methodology was only on the MNIST dataset. Digital Artifact Notebook, GitHub Repo
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➣ IHC HER-2 Automated Scoring
       Python</p>
Full time research internship for learning, understanding, developing, and optimizing computer vision models to complete intelligent solutions for pathological images at Thorough Images(the GitHub Repo is hidden for publication so far).
</article> </div>
➣ Baselines Experiments and Tutorials in AllenAct
       Python</p>
Contribute codes for baseline experiments and pretrained models of various of MuJoCo environments to the project of AllenAct, and provide a Tutorial.
</article> </div>
publications
➣ The Problem and Generalization of Locus about Fixed Point and Fixed Line Moving to Magnify and Shrink
Published in Mathematical Study and Research Vol 19, 2017
(Euclidean geometry) was as dazzling as first love. — Bertrand Russell. As a high schooler, This Euclidean geometry paper(in Chinese) is for mathematical Olympics competitions published in Chinese Periodical Mathematical Study and Research
Browse here
➣ Design and Optimization of Comb Drive Accelerator for High Frequency Oscillation
Published in Modern Mechanical Engineering Vol.8 No.1, February, 2018
As a high schooler, this is my first research experience mentored by Albert Chen at UCLA
Browse here
➣ Characterization of Rectifiable Measures that are Carried by Lipschitz Curves
Published in Preprint, 2021
Paper wrote in summer research with Lisa Naples about geometric measure theory.
Browse here
➣ Automated Scoring System of HER2 in Pathological Images under the Microscope
Published in arXiv, 2021
Paper wrote in my research intern for learning, understanding, developing, and optimizing computer vision models to complete intelligent solutions for pathological images at Thorough Images.
Browse here
rl
➣ Chapter 2 Multi-armed Bandits
       </p>
“Reinforcement Learning: An Introduction” by Richard Sutton & Andrew Barto, 2nd Ed
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➣ Chapter 3 Finite Markov Decision Processes
       </p>
“Reinforcement Learning: An Introduction” by Richard Sutton & Andrew Barto, 2nd Ed
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➣ Chapter 4 Dynamics Programming
       </p>
“Reinforcement Learning: An Introduction” by Richard Sutton & Andrew Barto, 2nd Ed
</article> </div>
➣ Chapter 5 Monte Carlo Methods
       </p>
“Reinforcement Learning: An Introduction” by Richard Sutton & Andrew Barto, 2nd Ed
</article> </div>
➣ Chapter 6 Temporal-Difference Learning
       </p>
“Reinforcement Learning: An Introduction” by Richard Sutton & Andrew Barto, 2nd Ed
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