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% Please build with lualatex | ||
% VS Code -> LaTeX Workshop extension settings: | ||
% { | ||
% "latex-workshop.latex.recipes": [ | ||
% { | ||
% "name": "lualatex", | ||
% "tools": ["lualatex"] | ||
% } | ||
% ], | ||
% "latex-workshop.latex.tools": [ | ||
% { | ||
% "name": "lualatex", | ||
% "command": "lualatex", | ||
% "args": [ | ||
% "-synctex=1", | ||
% "-interaction=nonstopmode", | ||
% "-file-line-error", | ||
% "-output-directory=%OUTDIR%", | ||
% "%DOC%" | ||
% ], | ||
% "env": {} | ||
% } | ||
% ], | ||
% "latex-workshop.linting.chktex.enabled": true | ||
% } | ||
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\documentclass[11pt]{article} | ||
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\newcommand\HUGE{\fontsize{26}{39}\selectfont} | ||
\fancyhead[C]{ | ||
% Title name | ||
\textbf{\HUGE Yuchen Zhang} \\ | ||
\textbf{\HUGE{Yuchen Zhang}} \\ | ||
\vspace{0.05in} | ||
\href{mailto:[email protected]}{[email protected]} | | ||
\href{mailto:[email protected]}{[email protected]} | | ||
% Phone | ||
\href{tel:13238688380}{(323) 868-8380} \\ | ||
% Personal website (disabled for now) | ||
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@@ -23,35 +47,18 @@ | |
} | ||
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\begin{document} | ||
\myHeading{EDUCATION} | ||
\subsection*{University of Southern California{\normalfont, \textit{Los Angeles, CA} \hfill May 2022}} | ||
\noindent | ||
Master of Science, Applied Data Science | ||
\hfill | ||
CGPA: 3.78/4.0 | ||
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%\vspace{0.1in} | ||
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\subsection*{University of California, Los Angeles{\normalfont, \textit{Los Angeles, CA} \hfill August 2020}} | ||
\noindent | ||
Bachelor of Science, Applied Mathematics with a minor in Statistics | ||
\hfill | ||
CGPA: 3.86/4.0 | ||
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\vspace{0.1in} | ||
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\myHeading{SKILLS} | ||
\vspace{0.05in} | ||
\begin{compactdesc} | ||
\item[Topics] Natural Language Processing (NLP), Machine Learning, Data Mining/Big Data, Data Science, Statistics | ||
\item[Programming Languages] 3+ years: Python | Basic knowledge: Java, R, C\texttt{++}, Bash, etc. | ||
\item[Database Management] SQLite, MySQL, MongoDB, Amazon DynamoDB, Firebase, Hadoop HDFS | ||
\item[Tools] PyTorch, TensorFlow, scikit-learn, GitHub, Pandas, PySpark, Distributed Systems, MapReduce, Algorithms, etc. | ||
\end{compactdesc} | ||
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\vspace{0.1in} | ||
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%% WORK EXPERIENCE %% | ||
\myHeading{WORK EXPERIENCE} | ||
\subsection*{CAD Software Developer Engineer{\normalfont, Qualcomm Technologies, Inc., | ||
\textit{CA} \hfill | ||
July 2022-Present}} | ||
\begin{compactitem} | ||
\item Revitalizing verification tools for VLSI front end design | ||
\item Developing automation scripts for generating SystemVerilog files | ||
\item Conceptualizing documentation generation tools for Engineers | ||
\end{compactitem} | ||
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\subsection*{Student Worker{\normalfont, USC Institute for Creative | ||
Technologies, | ||
\textit{CA} \hfill | ||
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@@ -80,14 +87,14 @@ \subsection*{Course Producer{\normalfont, USC Viterbi School of Engineering, | |
\end{compactitem} | ||
%\vspace{0.1in} | ||
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\subsection*{Research Internship{\normalfont, CarmaCam, \textit{Remote} \hfill May 2021-August 2021}} | ||
\begin{compactitem} | ||
\item Upgraded the existing Machine Learning Scoring website with a new UI using Django and Celery | ||
% \item Re-designed the CarmaCam web app using Parallel Agile\textregistered\xspace CodeBot\textregistered | ||
% \item Aggregated API calls and integrated the website with Node.JS | ||
\item Migrated the database of the ML scoring website from SQLite to MongoDB | ||
\item Improved the database schema of CodeBot using EA Architect | ||
\end{compactitem} | ||
% \subsection*{Research Internship{\normalfont, CarmaCam, \textit{Remote} \hfill May 2021-August 2021}} | ||
% \begin{compactitem} | ||
% \item Upgraded the existing Machine Learning Scoring website with a new UI using Django and Celery | ||
% % \item Re-designed the CarmaCam web app using Parallel Agile\textregistered\xspace CodeBot\textregistered | ||
% % \item Aggregated API calls and integrated the website with Node.JS | ||
% \item Migrated the database of the ML scoring website from SQLite to MongoDB | ||
% \item Improved the database schema of CodeBot using EA Architect | ||
% \end{compactitem} | ||
%\vspace{0.1in} | ||
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%\subsection*{Emergency Data Relief Internship (QA track){\normalfont, BroadStreet.io, \textit{Remote} \hfill September 2020-December 2020}} | ||
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@@ -102,20 +109,23 @@ \subsection*{Research Internship{\normalfont, CarmaCam, \textit{Remote} \hfill M | |
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\vspace{0.1in} | ||
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%% ACADEMIC PROJECTS %% | ||
\myHeading{ACADEMIC PROJECTS} | ||
\subsection*{Title: Data Mining on the Yelp Dataset \hfill {\normalfont January 2022-April 2022}} | ||
\subsection*{Data Mining on the Yelp Dataset \hfill {\normalfont{January 2022-April 2022}}} | ||
\noindent | ||
Goal: To implement algorithms and build recommendation systems on a large dataset. | ||
Goal: To implement algorithms and build recommendation systems on a large dataset | ||
\begin{compactitem} | ||
\item 200k+ reviews. Code containing 12 files totaling around 1800 LOC (lines of code) using PySpark and MapReduce | ||
\item Implemented Locality Sensitive Hashing, and different types of collaborative-filtering recommendation systems: Item-based CF, Model-based CF, and Hybrid recommendation system. Fine-tuned Model-based CF with XGBoostRegressor | ||
\item Implemented Locality Sensitive Hashing, and different types of collaborative-filtering recommendation systems: Item-based CF, Model-based CF, and Hybrid recommendation system. | ||
\item Fine-tuned Model-based CF with XGBoostRegressor | ||
\item Community detection based on GraphFrames and based on Girvan-Newman Algorithm on an RDD level | ||
\end{compactitem} | ||
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\subsection*{Title: The Influence of Pre- \& Post-processing on Document Summarization \hfill {\normalfont August | ||
2021-December 2021}} | ||
\subsection*{The Influence of Pre- \& Post-processing on Document Summarization \hfill {\normalfont{August | ||
2021-December 2021}}} | ||
\noindent | ||
\href{https://github.com/Anthonyive/csci-544-project.git}{\faIcon{github}} \href{https://www.youtube.com/watch?v=oVIVtOPeWEs}{\faIcon{youtube}} \href{https://arxiv.org/abs/2112.01660}{\textbf{arXiv}} Goal: To improve the existing long document summarization model's performance. | ||
% \href{https://github.com/Anthonyive/csci-544-project.git}{\faIcon{github}} \href{https://www.youtube.com/watch?v=oVIVtOPeWEs}{\faIcon{youtube}} \href{https://arxiv.org/abs/2112.01660}{\textbf{arXiv}} | ||
Goal: To improve existing long document summarization models' performance\hfill\textit{arXiv}: \href{https://arxiv.org/abs/2112.01660}{https://arxiv.org/abs/2112.01660} | ||
\begin{compactitem} | ||
\item Implemented extractive-based baseline (e.g. TextRank) and Google's T5 text-to-text transformer model | ||
% \item Inspired team members to implement GPT-3 and XLNet models | ||
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@@ -124,14 +134,15 @@ \subsection*{Title: The Influence of Pre- \& Post-processing on Document Summari | |
\end{compactitem} | ||
%\vspace{0.1in} | ||
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\subsection*{Title: Mapping Uncanny Valley \hfill {\normalfont September | ||
2020-May 2021}} | ||
\subsection*{Mapping Uncanny Valley \hfill {\normalfont{September | ||
2020-September 2022}}} | ||
\noindent | ||
\href{https://github.com/Anthonyive/Research-Mapping-Uncanny-Valley.git}{\faIcon{github}} Goal: To help answer what makes text creepy. | ||
% \href{https://github.com/Anthonyive/Research-Mapping-Uncanny-Valley.git}{\faIcon{github}} | ||
Goal: To help answer what makes text creepy\hfill \textit{arXiv}: \href{https://arxiv.org/abs/2211.05369}{https://arxiv.org/abs/2211.05369} | ||
\begin{compactitem} | ||
\item Best Project Achievement Award and Best Data Science Open and | ||
\item Received Best Project Achievement Award and Best Data Science Open and | ||
Sharing Practices Award | ||
\item Best Cyberphysical Data Science Team Award for a team of six people | ||
\item Received Best Cyberphysical Data Science Team Award for a team of six people | ||
in DataFest Fall 2020 | ||
\item Conducted DNN/RNN model with accuracy up to 96\% and implemented | ||
multiple NLP techniques | ||
|
@@ -141,9 +152,10 @@ \subsection*{Title: Mapping Uncanny Valley \hfill {\normalfont September | |
\end{compactitem} | ||
%\vspace{0.1in} | ||
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\subsection*{Title: Walmart Product Search \hfill {\normalfont January 2021-May 2021}} | ||
\subsection*{Walmart Product Search \hfill {\normalfont{January 2021-May 2021}}} | ||
\noindent | ||
\href{https://github.com/Anthonyive/DSCI-551-Project.git}{\faIcon{github}} Goal: To build a full-stack Walmart product search UI. | ||
% \href{https://github.com/Anthonyive/DSCI-551-Project.git}{\faIcon{github}} | ||
Goal: To build a full-stack Walmart product search UI | ||
\begin{compactitem} | ||
\item Leveraged MongoDB as a backend to store 6000 paginated pages from Walmart | ||
Affiliate API | ||
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@@ -177,4 +189,31 @@ \subsection*{Title: Walmart Product Search \hfill {\normalfont January 2021-May | |
% club activities | ||
%\end{compactitem} | ||
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\vspace{0.1in} | ||
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%% EDUCATION %% | ||
\myHeading{EDUCATION} | ||
\subsection*{University of Southern California{\normalfont, \textit{Los Angeles, CA} \hfill May 2022}} | ||
\noindent | ||
Master of Science, Applied Data Science | ||
% \hfill | ||
% CGPA\@ 3.78/4.0 | ||
|
||
\subsection*{University of California, Los Angeles{\normalfont, \textit{Los Angeles, CA} \hfill August 2020}} | ||
\noindent | ||
Bachelor of Science, Applied Mathematics with a minor in Statistics | ||
% \hfill | ||
% CGPA\@ 3.86/4.0 | ||
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||
\vspace{0.1in} | ||
|
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%% SKILLS %% | ||
\myHeading{SKILLS} | ||
\vspace{0.05in} | ||
\begin{compactdesc} | ||
\item[Topics] Software Development, Natural Language Processing (NLP), Machine Learning, Data Science, Statistics | ||
\item[Programming Languages] Strong knowledge: Python | Basic knowledge: Perl, Java, R, C\texttt{++}, Bash, etc. | ||
\item[Database Management] SQLite, MySQL, MongoDB, Amazon DynamoDB, Firebase, Hadoop HDFS | ||
\item[Tools] PyTorch, TensorFlow, scikit-learn, GitHub, Pandas, PySpark, Distributed Systems, MapReduce, Algorithms, etc. | ||
\end{compactdesc} | ||
\end{document} |