commit 984e39437fb51402105caabe745ae827508d6399
parent fdec1b97ff83d286a9b4e524bd5399c16b480316
Author: Silas Brack <s174433@student.dtu.dk>
Date: Wed, 4 Jan 2023 11:53:12 +0100
Fixed quotation marks.
Diffstat:
| M | cvs/full.tex | | | 100 | ++++++++++++++++++++++++++++++++++++++++---------------------------------------- |
1 file changed, 50 insertions(+), 50 deletions(-)
diff --git a/cvs/full.tex b/cvs/full.tex
@@ -5,12 +5,12 @@
\heading{Silas Brack}
{
- Copenhagen, Denmark
- $\mid$
+ Copenhagen, Denmark
+ $\mid$
\href{https://linkedin.com/in/silasbrack/}{linkedin.com/in/silasbrack/}
- $\mid$
+ $\mid$
\href{mailto:silasbrack@gmail.com}{silasbrack@gmail.com}
- $\mid$
+ $\mid$
\href{https://github.com/silasbrack/}{github.com/silasbrack/}
}
@@ -30,11 +30,11 @@
% - Independent
\newtopic
- {Data scientist (Student assistant)}
- {Sep 2021 -- Present}
- {Saxo Bank A/S -- Department of Predictive Modelling and Client Research}
- {Copenhagen, Denmark}
- {\begin{accomplishments}
+{Data scientist (Student assistant)}
+{Sep 2021 -- Present}
+{Saxo Bank A/S -- Department of Predictive Modelling and Client Research}
+{Copenhagen, Denmark}
+{\begin{accomplishments}
% \item Full-stack data science in Python, databases and data engineering, data cleaning, modelling, and visualising and presenting results under an agile framework.
\item Trained LightGBM models using Spark and DataBricks for processing and training on data in Kafka, Microsoft Azure Data Lake, and Microsoft SQL Server databases containing hundreds of gigabytes of data.
\item Defined and implemented MLOps infrastructure involving CI/CD, automated training, testing and deployment with Docker, Kubernetes and Airflow. Implemented model monitoring, outlier detection and data drift detection for time series.
@@ -44,59 +44,59 @@
\end{accomplishments}}
\newtopic
- {Software developer (Student assistant)}
- {Apr 2018 -- Aug 2021}
- {MAN Energy Solutions SE -- Department of Master Data and Management}
- {Copenhagen, Denmark}
- {
+{Software developer (Student assistant)}
+{Apr 2018 -- Aug 2021}
+{MAN Energy Solutions SE -- Department of Master Data and Management}
+{Copenhagen, Denmark}
+{
\begin{accomplishments}
\item Automated data engineering tasks and data pipelines with ETL jobs using SSIS and Microsoft SQL Server, being responsible for 15-20 daily and weekly jobs.
\item Accelerated data cleansing process by developing automated analytical data cleansing algorithms, saving an estimated 1000 man-hours of manual cleansing work. Increased fraction of cleansed data from 25\% to 50\%.
\item Improved technical strategy planning with teams of manual data cleansers during work trip abroad. % More specific, demonstrate soft skills
\item Created and maintained over 20 tools for data manipulation and visualisation using C\#, VBA, and Power BI.
\end{accomplishments}
- }
+}
\newsection{Projects}
\newtopic
- {\href{https://github.com/silasbrack/metric-laplace-approximation}{Uncertainty in image retrieval with Laplace approximation}}
- {Feb 2022 -- May 2022}
- {Supervised by Frederik Warburg and Søren Hauberg}
- {Copenhagen, Denmark}
- {\begin{accomplishments}
+{\href{https://github.com/silasbrack/metric-laplace-approximation}{Uncertainty in image retrieval with Laplace approximation}}
+{Feb 2022 -- May 2022}
+{Supervised by Frederik Warburg and Søren Hauberg}
+{Copenhagen, Denmark}
+{\begin{accomplishments}
\item Implemented Hessian calculations for metric learning losses for use for Laplace approximation in Bayesian neural networks (BNNs).
\item Evaluated uncertainty estimates of trained models using metric Laplace approximation.
% \item Published a paper to ICLR 2022.
\end{accomplishments}}
\newtopic
- {\href{https://github.com/silasbrack/approximate-inference-for-bayesian-neural-networks}{Approximate inference for Bayesian neural networks}}
- {Feb 2022 -- May 2022}
- {Supervised by Michael Riis Andersen}
- {Copenhagen, Denmark}
- {\begin{accomplishments}
+{\href{https://github.com/silasbrack/approximate-inference-for-bayesian-neural-networks}{Approximate inference for Bayesian neural networks}}
+{Feb 2022 -- May 2022}
+{Supervised by Michael Riis Andersen}
+{Copenhagen, Denmark}
+{\begin{accomplishments}
\item Implemented Bayesian inference methods for Bayesian neural networks, such as variational inference, deep ensembles, MultiSWAG, and the Laplace approximation.
\item Evaluated on MNIST, Street View House Numbers (SVHN), and MURA datasets.
\item Performed active learning for BNNs with different inference methods and acquisition functions.
\end{accomplishments}}
\newtopic
- {\href{https://github.com/silasbrack/normalizing-flows}{Variational inference using normalizing flows}}
- {Sep 2021 -- Dec 2021}
- {Supervised by Michael Riis Andersen}
- {Copenhagen, Denmark}
- {\begin{accomplishments}
+{\href{https://github.com/silasbrack/normalizing-flows}{Variational inference using normalizing flows}}
+{Sep 2021 -- Dec 2021}
+{Supervised by Michael Riis Andersen}
+{Copenhagen, Denmark}
+{\begin{accomplishments}
\item Implemented variational inference for different normalizing flows in PyTorch and Pyro and evaluated performance using the Evidence lower bound and Pareto-Smoothed Importance Sampling (PSIS) diagnostic.
\item Evaluated the performance of different flows as a function of the number of parameters and analysed the effect of high-dimensional data on VI.
\end{accomplishments}}
\newtopic
- {\href{https://github.com/silasbrack/sota-neural-translation}{State-of-the-art neural translation}}
- {Oct 2020 -- Dec 2020}
- {Supervised by Valentin Liévin, Ole Winther}
- {Copenhagen, Denmark}
- {\begin{accomplishments}
+{\href{https://github.com/silasbrack/sota-neural-translation}{State-of-the-art neural translation}}
+{Oct 2020 -- Dec 2020}
+{Supervised by Valentin Liévin, Ole Winther}
+{Copenhagen, Denmark}
+{\begin{accomplishments}
\item Implemented German-to-English machine translation seq2seq and transformer models with attention in Python.
\item Benchmarked against Bert2bert using BLEU score.
\end{accomplishments}}
@@ -104,22 +104,22 @@
\newsection{Education}
\newtopic
- {M.Sc. Mathematical modelling and computation}
- {Sep 2020 -- Present}
- {Technical University of Denmark}
- {Copenhagen, Denmark}
- {\begin{accomplishments}
+{M.Sc. Mathematical modelling and computation}
+{Sep 2020 -- Present}
+{Technical University of Denmark}
+{Copenhagen, Denmark}
+{\begin{accomplishments}
% \item \textsc{Gpa}: 8.7 / 12.
\item Specialisation in \emph{Machine learning and signal processing}.
\item Thesis: ``Effortless Bayesian Deep Learning: Tapping into the Potential of Modern Optimizers'' Advisor: Søren Hauberg.
\end{accomplishments}}
\newtopic
- {B.Sc. General engineering}
- {Sep 2017 -- Jun 2020}
- {Technical University of Denmark}
- {Copenhagen, Denmark}
- {\small\begin{accomplishments}
+{B.Sc. General engineering}
+{Sep 2017 -- Jun 2020}
+{Technical University of Denmark}
+{Copenhagen, Denmark}
+{\small\begin{accomplishments}
% \item \textsc{Gpa}: 9.8 / 12.
\item Completed 35 ECTS of graduate-level courses in machine learning, statistics, mathematics, physics and econometrics.
\item Specialisation in cyber materials.
@@ -128,17 +128,17 @@
\newsection{Skills} % Should have all of these in your experience / projects
\begin{tabular}{lp{15.5cm}}
- \textbf{Languages} & Python, R, SQL, C\#, Java \\
- \textbf{Technologies} & Spark, Docker, Kubernetes, Airflow, Azure, SSIS, Power BI \\
- \textbf{Models} & Gradient-boosted trees (LightGBM), neural networks (PyTorch), collaborative filtering
+ \textbf{Languages} & Python, R, SQL, C\#, Java \\
+ \textbf{Technologies} & Spark, Docker, Kubernetes, Airflow, Azure, SSIS, Power BI \\
+ \textbf{Models} & Gradient-boosted trees (LightGBM), neural networks (PyTorch), collaborative filtering
% \textbf{Other} & Relational databases \& indexing, machine learning operations, unit \& integration testing%, honestly just fill with whatever keywords are in job posting
\end{tabular}
\newsection{Certificates}
\begin{accomplishments}
-\item Certificate of Proficiency in English (CPE), Cambridge English -- Grade: \textsc{A}
-\item Prémio "Melhor Aluno" Dr. António Cláudio -- Yearly Best Student Award (7x)
+ \item Certificate of Proficiency in English (CPE), Cambridge English -- Grade: \textsc{A}
+ \item Prémio ``Melhor Aluno'' Dr. António Cláudio -- Yearly Best Student Award (7x)
\end{accomplishments}
\end{document}
