Laurent Smeets

Accra, Ghana · laurent.smeets@live.nl

Hello! Welcome on my online resume. I am life-long traveller with a dream to visit every country in the world and a passion for all things data. I am an adventurer, always ready for a challenge and looking for new things to explore. Currently, I am working as a Data Scientist, for the Ghana Statistical Service (placed as an ODI fellow). I have experience in creating products (and solutions) from a wide field of data sources, spanning from GPS and satellite data to medical and legislative text data. In addition to a passion for all things data and visualization, I thrive travelling and my life goal is to visit all countries in the world. Besides my MSc. I hold a LL.M. in China Studies from Peking University.

For my recent blogpost and work please see wwww.Ghanadatastuff.com, my personal blog

This website is still very much under development and will be improved upon in the future.

Coding and Skills

Adobe Creative Suite
Markdown
Microsoft Office
Python
R
R shiny
SPSS
SQL


Languages

Dutch
English
Mandarin
Spanish

Education

Utrecht University

M.Sc. (Res) in Methodology and Statistics for the Behavioural, Biomedical and Social Sciences.
- Thesis topic: Automatic Transport Mode Prediction in a National Travel Survey, available: https://www.cbs.nl/nl-nl/achtergrond/2019/51/geautomatiseerde-voorspelling-van-vervoermiddel
- Concurrently completed the EU accredited European Master in Official Statistic (EMOS).
- Successfully completed the Utrecht University Honours Programme for graduate students.
- Focus on Bayesian statistics and applied machine learning.
2017 - 2019
GPA: 8.3 (cum laude)

Yenching Academy of Peking University

LL.M. in China Studies
- Admitted as inaugural Yenching Scholar on a full scholarship.
- Focus on contemporary Chinese domestic economic challenges and foreign policy.
- Awarded a Dean’s Research Grant.
2015 - 2017
GPA: 91/100

Leiden University

B.SC. in International Relations and Affairs
- Thesis topic: Contagious Democracy: The role of Trading Partners in the Democratization Process of Undemocratic Countries.
- Simultaneously completed the Honours Academy Faculty of Social Sciences for undergraduate students.
- Focus on International Political Economy and statistical analysis.
2012 - 2015
GPA: 8.2 (cum laude)

McGill University

Exchange Programme
- 6 months Exchange Programme taking courses in political economy democratization theories, Middle Eastern Politics, and Economics.
2014
GPA 3.85/4

Experience

Data Scientist

Ghana Statistical Service (GSS)

I am placed as an 2019-2021 ODI Fellow. I assist in modernizing and digitizing the collection, calculation, quality assurance, and dissemination of price statistics (predominantly consumer inflation). This work requires both project management skills and technicalskills for the translation of legacy code systems to R and Python and to create a Reproducible Analytical Pipeline(RAP) for the monthly CPI statistics. For Ghana’s 2021 Population and Housing Census, I am creating fuzzy matching algorithms and machine learning techniques to match data from the main census to data collected in the post-enumeration survey, as well as to estimate coverage errors of the census. This matching task consists of an automated matching stage, implemented in R, and a Computer Assisted Manual Matching Stage in the form of an R shiny application. Within the Sustainable Development Goals Secretariat of the GSS, I advise on projects related to the use of citizen-generated data, satellite data, and other data science solutions to fill data gaps on gender-based violence, solid waste management, deforestation, and access to public transport.Finally, I assist and train various departments within the GSS on how to use open-source and free software solutions (R, Python, and certain JavaScript libraries), to transition GSS away from proprietary software. This enables GSS to reduce the turnaround time of data analysis and to produce high-quality data visualizations both in print and interactive ones for the web.

2019 - 2021
Accra, Ghana

Research Intern

Statistics Netherlands (CBS)

As a Research Intern I worked on automatic transport mode classification from GPS data, using machine learning. I was responsible for the feature engineering and machine learning prediction models. These data are collected as part of a pilot study by CBS to see if the traditional diary based transport survey can be automated by logging the location estimates of respondents' smartphone. More information on the project can be found here and the used code is available on my GitHub page.

2018 - 2019
The Hague, the Netherlands

Research Assistant

Utrecht University

As a research assistant, I developed over twenty tutorial and online teaching material on Bayesian analyses for prof Rens van der Schoot. I also authored the online materials for a book on multilevel modelling . Furthermore, I organized the biweekly MSDSlab meetings on big data analysis and methods. Finally, I assisted in writing and optimizing code to analyse data for a Utrecht University Hospital’s (UMC) project that uses virtual reality glasses to better predict complications of stroke patients.

2017 - 2019
Utrecht, the Netherlands

Teaching Assistant

Utrecht University

As a teaching assistant, I organised undergraduate courses in statistics and assisted in summer schools in Introduction to Multilevel Analysis, Advanced Multilevel Analysis, A Gentle Introduction to Bayesian Statistics, and Bayesian Structural Equation Modelling.

2017 - 2019
Utrecht, the Netherlands

Think Tank Member

Denkkracht Utrecht

At Denkkracht Utrecht, 24 other selected young professionals from different backgrounds and areas of expertise and I gathered monthly to help organizations in and around the city of Utrecht with solving their societal questions.

2018
Utrecht, the Netherlands

Intern

Embassy of the Kingdom of the Netherlands

Writing a report on the business climate in Rwanda and working on private sector development and analysing investment opportunities for Dutch companies in Rwanda.

2016 - 2017
Kigali, Rwanda

Participant

Netherlands-Asia Honours Summer School (NAHSS)

As a participant, of the Netherlands-Asia Honours Summer School (NAHSS), I completed courses at Fudan University, Shanghai and conducted research for the Dutch Ministry of Foreign Affairs on the Belt and Road initiative.

2016 - 2017
Shanghai, China

Student Assistant

Leiden University

Assisting the university in designing a strategy to attract more students from Delft University to the Leiden Leadership Programme

2014 - 2015
Leiden, the Netherlands

Projects

This is a selection of the statistics and data science projects I worked on.

Transport Mode Prediction from GPS Data

For my Master's thesis I worked on machine learning solutions to transport mode prediction from GPS data collected in a national travel survey.

Read more..

Plausible Parameter Space, a R Shiny App

This Shiny App is designed to help users define their priors in a linear regression with two regression coefficients. Users are asked to specify their plausible parameter space and their expected prior means and uncertainty around these means.

Read more..

Tutorials

This is a selection of the statistics tutorials I wrote, most of them for prof. Rens van de Schoot.

- Bayesian Regression in Blavaan (Using Stan)

This tutorial provides the reader with a basic tutorial how to perform a regression in Blavaan.

January 2019

- WAMBS Blavaan Tutorial (Using Stan)

In this tutorial you follow the steps of the WAMBS checklist in Blavaan (using Jags)

January 2019

- Bayesian Regression in Blavaan (Using Jags)

This tutorial provides the reader with a basic tutorial how to perform a regression in Blavaan.

November 2018

- Regression in Lavaan

This tutorial provides the reader with a basic tutorial how to perform a regression in Lavaan

November 2018

- WAMBS Blavaan Tutorial (Using Jags)

In this tutorial you follow the steps of the When-to-Worry-and-How-to-Avoid-the-Misuse-of-Bayesian-Statistics - checklist in Blavaan (using Jags)

November 2018

- BRMS Tutorial: Applying the WAMBS checklist

In this tutorial you follow the steps of the When-to-Worry-and-How-to-Avoid-the-Misuse-of-Bayesian-Statistics - checklist for a multilevel model in BRMS

September 2018

- BRMS tutorial: the Influence of Priors

This tutorial shows how to specify different priors in a multilevel model in BRMS

September 2018

- Building a Bayesian Multilevel Model in BRMS Tutorial: Popularity Data

This tutorial shows how you can replicate the popularity data multilevel models from the book Multilevel analysis: Techniques and applications' in a Bayesian method

September 2018

- LME4 Tutorial: Popularity Data

This tutorial shows how you can replicate the popularity data multilevel models from the book Multilevel analysis: Techniques and applications

September 2018

- HLM Tutorial: Popularity Data

This tutorial shows how you can replicate the popularity data multilevel models from the book Multilevel analysis: Techniques and applications in HLM

September 2018

- Mplus Tutorial: Popularity Data

This tutorial shows how you can replicate the popularity data multilevel models from the book Multilevel analysis: Techniques and applications in Mplus

September 2018

- Bayesian Regression in Mplus

This tutorial provides the reader with a basic tutorial how to perform a Bayesian regression in Mplus.

August 2018

Wait! There's more..

Click here for more Tutorials!

Publications

Not that many yet

But here is a nice little map of all the places I visited, busy not writing Publications:

Example image

You can find the code I used making this plot here

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- Spatial distribution of artisanal goldmining in Ghana: Using machine learning and Google Earth Engine to quantify conversion of vegetation to gold mines

Abigail Barenblitt, Amanda Payton, David Lagomasino, Temilola Fatoyinbo, Kofi Asare, Kenneth Aidoo, Hugo Pigott, Charles Som, Omar Seidu, Laurent Smeets, al., Earth and Space Science Open Archive (2020)

November 2020

- Automatic Travel Mode Prediction in a National Travel Survey

Laurent Smeets, Peter Lugtig, Barry Schouten, CBS discussion paper (2019)

December 2019

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Click here for more Publications!