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\documentclass{resume} % Use the custom resume.cls style
\usepackage[hidelinks]{hyperref}
\usepackage{fancyhdr}
\usepackage[english]{babel}
\usepackage{tabularx}
\usepackage{fontawesome}
\usepackage{graphicx}
\usepackage{xcolor}
\usepackage{changepage} % For the adjustwidth environment
\input{glyphtounicode}
\usepackage[left=0.75in,top=0.6in,right=0.75in,bottom=0.6in]{geometry} % Document margins
\newcommand{\vb}[1]{\vrule\hspace{1pt}}
\newcommand{\tab}[1]{\hspace{.2667\textwidth}\rlap{#1}}
\newcommand{\itab}[1]{\hspace{1em}\rlap{#1}}
\newcommand{\email}{\href{mailto:yl307@rice.edu}{yl307@rice.edu}}
\newcommand{\linkedin}{%
\href{https://www.linkedin.com/in/yu-cheng-eric-liao/}{\faLinkedinSquare\hspace{0.2em}Yu-Cheng Liao}%
}
\newcommand{\Address}[2]{%
\parbox{\textwidth}{%
\begin{center}
#1 $\vert$ #2 $\vert$ \faEnvelope{} \email $\vert$ \linkedin
\end{center}
}%
}
\name{Yu-Cheng Liao}
% Your phone number and email
\begin{document}
\Address{(+1)346 628-2020}{Houston, TX}
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% EDUCATION SECTION
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\begin{rSection}{Education}
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{\bf Rice University} \hfill {\em Aug. 2023 - Present}
\\ Master of Computer Science\hfill { Houston, TX, USA }\\
{\bf National Tsing Hua University} \hfill {\em Sept. 2018 - Jan. 2023}
\\ Bachelor of Science in Computer Science\hfill { Hsinchu, Taiwan }
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\end{rSection}
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% EXPERIENCE SECTION
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\begin{rSection}{Skills}\begin{itemize}
\item {Programming}: {\bfseries Javascript}, {\bfseries Java}, {\bfseries C}, {\bfseries C++}, Python(PyTorch, Numpy), Shell Script, Verilog
\item {Frameworks/Technologies}: {\bfseries Node.js}, {\bfseries React.js}, {\bfseries Git, Linux}, {\bfseries PostgreSQL}, Docker, {\bfseries AWS}
\end{itemize}
\end{rSection}
\begin{rSection}{Experience}
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{\bf Institute of Information Science, Academia Sinica}\\
{Research Intern} \hfill {\em Jul, 2022 – Aug, 2022}
\begin{itemize}
\item Fine-tuned {\bfseries YOLOv4}, a well-known one-stage object detection model to predict the locations of remaining unlabeled tomb
\item Transformed real-world coordinates of tombs into object detection trainable datasets
\item Built dataset for Nanshan gravesite, one of the most representative, ancient gravesites in Taiwan
\end{itemize}
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{\bf National Tsing Hua University Vision and Learning lab}\\{Undergraduate research student} \hfill {\em Nov, 2020 – Nov, 2021}
\begin{itemize}
\item Introduced {\bfseries Mask2Hand} (\textcolor{cyan}{\href{https://arxiv.org/abs/2205.15553}{paper link}}), a deep network that predicts 3D hand pose and shape from a 2D binary mask of hand silhouette without relying on RGB or depth information.
\item Achieved comparable performance to {\bfseries state-of-the-art} RGB-based and depth-based methods, despite the more challenging input setting
\item With the parametric hand model and differentiable rendering technique, the self-supervised mechanism is integrated into the end-to-end training process without the need for human annotations
\item Conducted experiments with other states of the art method with the same binary images input
\end{itemize}
\end{rSection}
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% PROJECTS
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\begin{rSection}{Selected Projects}
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{\bf Time Management Secretary}
\begin{itemize}
\item{Built a scheduling system (\textcolor{cyan}{\href{https://youtu.be/_AxEMolYK6M}{demo link}}) that helps people manage their time automatically by using {\bfseries React}, {\bfseries Redux} and {\bfseries JavaScript} for front-end, {\bfseries Node.js} and {\bfseries Express} for back-end and {\bfseries PostgreSQL} as database}
\item{Deployed the system by using {\bfseries Amazon Web Service} and established version control with {\bfseries Git}}
\item{Used {\bfseries OAuth 2.0} to enable third-party login services such as Google, Facebook}
\item{Implemented auto time scheduling algorithm with considerable parameters in this algorithm}
\end{itemize}
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\end{rSection}
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% ACTIVITIES
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\begin{rSection}{Courses}
Software Engineering, Software Studio, Operating Systems, Design and Analysis of
Algorithms, Data Structures, Introduction to Multimedia
\end{rSection}
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% SKILLS SECTION
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\end{document}----------------------------