Timeline.tex

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\begin{document}
Figure \ref{fig:timeline} depicts a high level overview of the significant milestones achieved to date, accompanied by the milestones currently undergoing to reach the final milestone (PhD defence) marking the completion of the PhD thesis.


\begin{figure}[h]
	\begin{minipage}{0.8\linewidth}
		\fontsize{10pt}{0.7em}
		\color{gray}
		\rule{1.2\linewidth}{1pt}
		\ytl{9/2013}{\bf{PhD Starting point}}
		\ytl{1/2014 - 10/2015}{{\bf Infosys '17}\\ \emph{Crowdsourcing Emergency Data in Non-Operational Cellular Networks}}
		\ytl{11/2014 - 8/2015}{{\bf TKDE '16}\\ \emph{Distributed In-Memory Processing of All k Nearest Neighbor Queries}}
		\ytl{2/2015}{{\bf Mobisocial '15}\\ \emph{Rayzit: An Anonymous and Dynamic Crowd Messaging Architecture}}
    	\ytl{12/2015}{{\bf PhD Comprehensive Exam}}
		\ytl{1/2016}{{\bf ICDE '16}\\ \emph{Distributed In-Memory Processing of All k Nearest Neighbor Queries (Extended Abstract)}}
		\ytl{10/2016}{{\bf ICDE '17}\\ \emph{SPATE: Compacting and Exploring Telco Big Data}}
		\ytl{10/2016}{{\bf ICDE '17}\\ \emph{Efficient Exploration of Telco Big Data with Compression and Decaying}}
		\ytl{8/2017}{{\bf BIRTE '17}\\ \emph{Towards Real-Time Road Traffic Analytics using Telco Big Data}}
		\ytl{\color{orange}12/2017}{\bf PhD Thesis proposal}
		\ytl{\color{teal}1/2018}{{\bf MDM '18}\\ \emph{Predicting Call Drops by applying Deep Learning on Telco Big Data}}
		\ytl{\color{teal}1/2018}{{\bf LNBIP}\\ \emph{Real-time road traffic analytics using Telco Big Data}}
		\ytl{\color{teal}5/2018}{\bf PhD Defense}
		\bigskip
		\rule{1.2\linewidth}{1pt}%
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	\caption{Timeline of PhD Thesis.}
	\label{fig:timeline}
\end{figure}

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