This template builds on the beamer document class and the following packages, already wired up in the preamble:
amsmathamssymbgraphicxbooktabs
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\documentclass{beamer}
\usetheme{Boadilla}
\usecolortheme{whale}
\usepackage{amsmath,amssymb}
\usepackage{graphicx}
\usepackage{booktabs}
% ── LOGO CONFIGURATION ──────────────────────────────────────────────────
% Appears on every slide (bottom-right corner):
% \logo{\includegraphics[height=0.7cm]{university-logo.png}}
%
% Appears only on the title slide:
% \titlegraphic{\includegraphics[height=1.5cm]{university-logo.png}\hspace{1cm}\includegraphics[height=1.5cm]{lab-logo.png}}
%
% HOW TO USE:
% 1. Put your logo file (PNG/PDF/EPS) in the same folder as your .tex
% 2. Remove the % from the lines above
% 3. Adjust height= to fit your logo
% ────────────────────────────────────────────────────────────────────────
% Placeholder logo (delete once you add a real logo):
\titlegraphic{\fbox{\parbox[c][1.2cm][c]{3cm}{\centering\tiny University Logo\\(replace me)}}}
\title[Short Title]{Full Title of Your Research}
\subtitle{Conference Name $\cdot$ City, Month Year}
\author[Your Name]{Your Full Name}
\institute[Dept.]{%
Department of XYZ\\
University Name\\[0.2em]
\texttt{you@university.edu}
}
\date{\today}
\begin{document}
\begin{frame}
\titlepage
\end{frame}
\begin{frame}{Outline}
\tableofcontents
\end{frame}
\section{Introduction}
\begin{frame}{Motivation}
\begin{itemize}
\item<1-> Why is this problem important?
\item<2-> What gap does this work address?
\item<3-> Our key contributions:
\begin{itemize}
\item Novel method for [X] with theoretical guarantees
\item Empirical validation on [benchmark]
\end{itemize}
\end{itemize}
\end{frame}
\section{Method}
\begin{frame}{Problem Formulation}
\begin{block}{Setup}
Given input $\mathbf{x} \in \mathbb{R}^d$, we minimize the objective:
\end{block}
\[
\mathcal{L}(\theta) = \frac{1}{n}\sum_{i=1}^n \ell(f_\theta(\mathbf{x}_i), y_i)
+ \lambda \|\theta\|_2^2
\]
where $\lambda > 0$ controls regularisation.
\end{frame}
\begin{frame}{Algorithm}
\begin{columns}[T]
\begin{column}{0.55\linewidth}
\textbf{Key steps:}
\begin{enumerate}
\item Initialise $\theta_0$
\item For each mini-batch $\mathcal{B}$:
\[
\theta_{t+1} = \theta_t - \alpha \nabla_{\mathcal{B}} \mathcal{L}(\theta_t)
\]
\item Evaluate on validation set
\end{enumerate}
\end{column}
\begin{column}{0.40\linewidth}
\begin{block}{Complexity}
$O(n \log n)$ per epoch\\
Memory: $O(d)$
\end{block}
\end{column}
\end{columns}
\end{frame}
\section{Results}
\begin{frame}{Experimental Results}
\begin{table}
\centering
\begin{tabular}{lcc}
\toprule
Method & Accuracy & Time (s) \\
\midrule
Baseline & 88.4\% & 12.3 \\
Method X & 91.2\% & 10.7 \\
\textbf{Ours} & \textbf{94.7\%} & \textbf{8.9} \\
\bottomrule
\end{tabular}
\end{table}
\vspace{0.5em}
\begin{alertblock}{Key result}
Our method achieves \textbf{+6.3\%} accuracy with \textbf{28\%} less compute.
\end{alertblock}
\end{frame}
\section{Conclusion}
\begin{frame}{Conclusion \& Future Work}
\begin{columns}
\begin{column}{0.5\linewidth}
\textbf{What we showed:}
\begin{itemize}
\item Novel method for [X]
\item State-of-the-art on [benchmarks]
\item Theoretical convergence guarantee
\end{itemize}
\end{column}
\begin{column}{0.5\linewidth}
\textbf{Future work:}
\begin{itemize}
\item Extend to [larger scale]
\item Apply to [new domain]
\item Open-source release
\end{itemize}
\end{column}
\end{columns}
\vspace{1em}
\centering{\Large\bfseries Thank you! Questions?}\\[0.5em]
\small\texttt{you@university.edu}
\end{frame}
\end{document}