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resume.tex
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%-------------------------
% Resume in Latex
% Author : Ran Cheng
% Adapted from: Indu dwivedi, Sourabh Bajaj
% License : MIT
%------------------------
\documentclass[letterpaper,10pt]{article}
\usepackage{latexsym}
\usepackage[empty]{fullpage}
\usepackage{titlesec}
\usepackage{marvosym}
\usepackage[usenames,dvipsnames]{color}
\usepackage{verbatim}
\usepackage{enumitem}
\usepackage[pdftex, hidelinks]{hyperref}
\usepackage{fancyhdr}
\usepackage[charter]{mathdesign} % Bitstream Charter
% \usepackage{newpxtext,newpxmath} % Palatino
\usepackage{longtable}
\usepackage{graphicx}
\usepackage{array}
\usepackage{multirow}
\usepackage{xcolor}
\usepackage{bibentry}
\pagestyle{fancy}
\fancyhf{} % clear all header and footer fields
\fancyfoot{}
\renewcommand{\headrulewidth}{0pt}
\renewcommand{\footrulewidth}{0pt}
% bibtex for publication
\bibliographystyle{plain}
\nobibliography{resume.bib}
% Adjust margins
\addtolength{\oddsidemargin}{-0.50in}
\addtolength{\evensidemargin}{-0.50in}
\addtolength{\textwidth}{1in}
\addtolength{\topmargin}{-.5in}
\addtolength{\textheight}{1.0in}
% Define colors
\definecolor{linkblue}{RGB}{111, 153, 222}
\definecolor{titleblue}{RGB}{46, 116, 181}
\urlstyle{same}
\raggedbottom
\raggedright
\setlength{\tabcolsep}{0in}
% Sections formatting
\titleformat{\section}{
\vspace{-6pt}\scshape\raggedright\large
}{}{0em}{}[\color{black}\titlerule \vspace{-5pt}]
%-------------------------
% Custom commands
\newcommand{\resumeItem}[2]{
\item\small{
\textbf{#1}{: #2 \vspace{-2pt}}
}
}
\newcommand{\resumeItemNoBullet}[2]{
\item[]\small{
\hspace{-9pt}\textbf{#1}{: #2 \vspace{-6pt}}
}
}
\newcommand{\resumeSubheading}[4]{
\vspace{-1pt}\item[]
\begin{tabular*}{0.98\textwidth}{l@{\extracolsep{\fill}}r}
\hspace{-10pt}\textbf{#1} & #2 \\
\hspace{-10pt}\textit{\small#3} & \textit{\small #4} \\
\end{tabular*}\vspace{-5pt}
}
\newcommand{\resumeSubItem}[2]{\resumeItem{#1}{#2}\vspace{-4pt}}
\renewcommand{\labelitemii}{$\circ$}
\newcommand{\resumeSubHeadingListStart}{\begin{itemize}[leftmargin=*]}
\newcommand{\resumeSubHeadingListEnd}{\end{itemize}}
\newcommand{\resumeItemListStart}{\begin{itemize}}
\newcommand{\resumeItemListEnd}{\end{itemize}\vspace{-5pt}}
% custom commands
\newcommand{\shorterSection}[1]{\vspace{-10pt}\section{#1}}
%-------------------------------------------
%%%%%% CV STARTS HERE %%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{document}
%----------HEADING-----------------
% you can generate your own qr code here: https://www.the-qrcode-generator.com/
% and convert the svg image you exported to pdf here: https://cloudconvert.com/svg-to-pdf
% then import the graph in the title like this:
\begin{table}[]
\begin{tabular*}{\textwidth}{lc@{\extracolsep{\fill}}r}
\begin{tabular}{l}
\textbf{\huge \textcolor{titleblue}{Ran Cheng}} \\
\\
An Intelligent Robotics Researcher
\end{tabular} & & \begin{tabular}{@{}rr@{}} \textcolor{titleblue}{\includegraphics[width=0.017\linewidth]{imgs/location(1).pdf}} MLL 411, McGill University, Montreal, Canada & \multirow{3}{*}{\includegraphics[width=0.096\linewidth]{imgs/githubpage.pdf}} \\
\includegraphics[width=0.017\linewidth]{imgs/email(1).pdf} [email protected] & \\
\includegraphics[width=0.017\linewidth]{imgs/home(1).pdf} \href{http://rancheng.github.io}{rancheng.github.io} & \\
\includegraphics[width=0.017\linewidth]{imgs/phone(1).pdf} 774-823-4304 &
\end{tabular} \\
\end{tabular*}
\end{table}
\vspace*{-10mm}
%-----------EDUCATION-----------------
\shorterSection{\textcolor{titleblue}{Education}}
\resumeSubHeadingListStart
\resumeSubheading
{McGill University, Computer Science}{Montreal, Canada} {Master of Science in Computer Science}{Expected May 2020}{
% \resumeItemNoBullet{Thesis}{Guided Robust Visual Navigation with Deep Learning}
\resumeItemNoBullet{Relevant Coursework}{Intelligent Robotics, Reinforcement Learning, Applied Machine Learning}
}
\resumeSubheading
{Coursera}{Online} {Honored Degrees \& Long-term Community Contributor}{Aug 2015 - Aug 2017}{
\resumeItemNoBullet{Completed Courses}{Neural Network for Machine Learning (UToronto), Robotics: Specialization (UPenn), Machine Learning (Stanford)}
}
\resumeSubheading
{Tongji University, School of Software Engineering}{Shanghai, China} {Bachelor of Engineer, Software Engineering; GPA: 3.89/4.0}{Aug 2011 - Aug 2015}{
\resumeItemNoBullet{Honors and Awards}{Outstanding Diploma thesis, National Aspiration Fellowship, Second Class Prize Fellowship, Social Activism Award, IBM
Outstanding Contribution Award, Microsoft Imagine Cup, FTC (First Tech Challenge, a Robot Competition Conference) Technician}
}
\resumeSubHeadingListEnd
% %-----------ACADEMIC PROJECTS AND INTERNSHIPS-----------------
% \shorterSection{Academic Projects and internships}
% \resumeSubHeadingListStart
% \small
% \item{
% \textbf{Languages}{: Python, C++, SQL, Java, Swift}
% \hfill
% \textbf{Technologies}{: GCP, AWS, GitHub, GitLab, Docker}
% }
% \vspace{-5pt}
% \item{
% \textbf{Libraries}{: TensorFlow, PyTorch, Keras, Scikit-Learn, Numpy, Pandas, Spark, Jupyter, OpenCV, PIL, OpenCL, OpenGL, CUDA}
% }
% \resumeSubHeadingListEnd
%-----------EXPERIENCE-----------------
\shorterSection{\textcolor{titleblue}{Experience}}
\resumeSubHeadingListStart
\resumeSubheading
{Mobile Robotics Lab, McGill University}{Montreal, Canada}
{Research Assistant, Supervisor: \textbf{Gregory Dudek}}{Sep 2017 - Now}
\resumeItemListStart
\resumeItem{Deep Monocular VO}
{ Designed a semi-supervised monocular depth estimator for video using sparse bundle adjustment in a sliding window, achieved 0.117 (top5) RMSE in \textbf{NYU v2} and 2.981 (top10) RMSE in \textbf{Kitti eigen-split}. backbone is Unet+CSPN, trained with semi-dense map point tracked by VO, implemented with \textbf{PyTorch}. }
\resumeItem{NavGuideNet}
{A \textbf{synthesized hierarchical neural network} for autonomous navigation in complex environment and variant landscapes (tested in field/underwater environments). Backbone \textbf{encoder} is \textbf{Resnet18}, \textbf{latent code} was concaternated with control signals and \textbf{decoder} is \textbf{de-convolution network} (transposed convolution)}
\resumeItem{Deep RL Auto Driving (Sim2Real)}
{Re-implemented CAD2RL in python and extended to multiple policy gradient based backends \textbf{(A3C+LSTM)} in continuous action space, simulator is \textbf{Microsoft AirSim}, tested on RC car and UAV.
}
\resumeItemListEnd
\resumeSubheading
{iLab Tongji/University of South California}{Shanghai, China, Los Angeles, USA}
{Research Assistant, Supervisor: \textbf{Jianwei Lu, Laurent Itti}}{Apr 2015 - Jul 2017}
\resumeItemListStart
\resumeItem{SLAM Fusion}
{Vision (monocular) LiDar fusion with direct method (jointly optimize optical flow with Sparse Bundle Adjustment on ORB features) extra constraint from LiDar helps eliminating depth from null space. }
\resumeItem{Visual SLAM with Saliency}
{ joint optimizing the graph (G2O) with salient voting as extra binary edges.}
\resumeItemListEnd
\resumeSubheading
{UCLA}{Los Angeles, USA}
{Research Assistant, Supervisor: \textbf{Yi Xing}}{Jul 2015 - Jan 2016}
\resumeItemListStart
\resumeItem{Code Parallelization}
{optimized their RNA analysis tool, [stable release (\href{http://rnaseq-mats.sourceforge.net/rmats3.0.9/}{\textcolor{linkblue}{rMATS 3.0.9}})], binding the large matrix calculations with C11 (SSE/AVX vectorization, Intel) and CUDA (cuBLAS , Nvidia) }
\resumeItemListEnd
\resumeSubHeadingListEnd
%-----------PROJECTS/SKILLS-----------------
\shorterSection{\textcolor{titleblue}{Projects}}
\resumeSubHeadingListStart
\resumeSubItem{Visual SLAM}
{
Comprehensively \textbf{re-implemented} \href{https://github.com/rancheng/dso_understands}{\textcolor{linkblue}{DSO}} and annotated with exhaustive explains.
}
\resumeSubItem{Deep Monocular Dense 3D Reconstruction}{Dense 3D reconstruction with \textbf{monodepth2} initialized Visual Odometry, leveraging traditional photometric consistancy, occlusion discrepancy, and local geometrical-smooth assumptions to \textbf{optimize depth estimation} (\textbf{LM} method) and \textbf{register} 3D map point clouds.}
\resumeSubItem{Abstraction Augmented Deep RL}
{Abstract rgb image with Unet shaped network to digest image in latent representation, and learn from latent inputs, average convergence time increased 27.3\%, maximum reward (10M iterations) is 1.21 times than baseline model without abstraction augmentation, experiments conducted under self-collected dataset from AirSim simulator (\href{https://github.com/rancheng/AirSimProjects}{\textcolor{linkblue}{github}})}
\resumeSubItem{Forgetting Model for BP}
{Introduced forgetting model for back propagation as in gradient dynamic routine, inspired from forgetting curve, I invented forgetting factor to regulate delta weights updates (\href{https://rancheng.github.io/forgetting-model/}{\textcolor{linkblue}{math proof}})}
\resumeSubItem{LOAM}{extended LOAM (LiDAR Odometry and Mapping) with co-visibility check, optimized with Ceres optimizer and asynchronous threading}
\resumeSubHeadingListEnd
%-----------Addtional Experience & Achievements-----------------
\shorterSection{\textcolor{titleblue}{Publications}}
\resumeSubHeadingListStart
\small
\item{Navigation in the Service of Enhanced Pose Estimation, Travis Manderson, \textbf{Ran Cheng}, David Meger and Gregory Dudek, \textbf{ISER 2018}, \href{http://www.cim.mcgill.ca/~travism/authors/ran-cheng/}{\textcolor{linkblue}{paper}}}
\vspace{-5pt}
\item{Vision-Based Autonomous Underwater Swimming in Dense Coral for Combined Collision Avoidance and Target Selection, T. Manderson, \textbf{R. Cheng}, D. Meger, G. Dudek, \textbf{IROS 2018}, \href{http://www.cim.mcgill.ca/~travism/authors/ran-cheng/}{\textcolor{linkblue}{paper}}}
\resumeSubHeadingListEnd
%-------------------------------------------
\end{document}