Simon Ress

Simon Ress

Research Assistant

Ruhr-Universität Bochum

Biography

I am a PhD candidate at the chairs of Comparative Politics & Social Science Data Analysis, Ruhr-Universität Bochum. My main research interests are labour market policies and their effects on individual health and interest groups and lobbyism. I have published articles on interest groups and prevention policies.

Download my CV.

Interests
  • Modern Causal Analysis
  • Machine Learning
  • R & Python
  • Social Policy
  • Labour Market
  • Social Epidemiology
Education
  • M.A. in Methods of Social Research, 2019

    Ruhr-Universität Bochum

  • B.A. in Social Science, 2016

    Ruhr-Universität Bochum

Skills

R

4 years

Python

1 year

Statistics / ML

6 years

Modern Causal Analysis

3 years

Data Visualization

4 years

Automated reporting

3 years

Experience

 
 
 
 
 
Ruhr-Universität Bochum - Chair for Social Science Data Analysis
Research Assistant
Ruhr-Universität Bochum - Chair for Social Science Data Analysis
Jul 2019 – Present Bochum

Responsibilities include:

  • Analysing
  • Modelling
  • Deploying Web Apps
 
 
 
 
 
Ruhr-Universität Bochum - Chair for Comparative Politics
Research Assistant
Ruhr-Universität Bochum - Chair for Comparative Politics
Jul 2018 – Present Bochum

Responsibilities include:

  • Web-Scraping
  • Deploying Desktop Apps
  • Analysing
  • Teaching
 
 
 
 
 
Ruhr-Universität Bochum - Chair for Health Policy
Student Assistant
Ruhr-Universität Bochum - Chair for Health Policy
Jul 2016 – Mar 2018 Bochum

Responsibilities include:

  • Data acquisition
  • Data preparation
  • Analysing
  • Participation in scientific projects
 
 
 
 
 
Ruhr-Universität Bochum - Chair for Social Policy and Public Economics
Student Assistant
Ruhr-Universität Bochum - Chair for Social Policy and Public Economics
Feb 2012 – Mar 2018 Bochum

Responsibilities include:

  • Data preparation
  • Analysing
  • Participation in scientific projects

Accomplish­ments

This course uses causal graphs as a remarkably simple, yet general and powerful framework to describe and discuss a large set of problems that empirical social scientists need to tackle. How can I communicate my assumptions effectively to others, and can I test them? How can I tell correlation from causation? How do I choose control variables for my regression models? After discussing how DAGs can be used to answer these foundational questions, the course also covers basics of causal mediation, instrumental variables, nonresponse/selection bias (and adjustments for it), and panel data analysis from a ‘graphical’ perspective.
See certificate
Data Science is the interdisciplinary science of the extraction of interpretable and useful knowledge from potentially large datasets. Due to the rapid surge of digital trace data (often as “Big Data”) in a wide range of application areas, Data Science is also increasingly utilized in the social sciences and humanities. In contrast to empirical social science, Data Science methods often serve purposes of exploration and inductive inference. In this course, we aim to provide an introduction into Data Science for practitioners. In particular, we want to impart basic understanding of the main methods and algorithms and understand how these can be deployed in practical application scenarios, focusing on the analysis of digital behavioral data found on the Web. We cover aspects of data collection, preprocessing, exploration, visualization and machine learning using basic Python and key packages like pandas, numpy and scikit- learn.
See certificate
Estimating causal effects is the central concern of quantitative social research. In research practice, however, only non-experimental data are often available that make causal conclusions difficult due to non-random selection and heterogeneity of individuals. Modern causal analysis is an effective tool to address these problems and to develop solutions. This workshop therefore first introduces its basics and discusses problems of conventional regression analysis. Based on this, in an application-oriented introduction, methods of propensity score matching (including longitudinal data as differences-from-differences propensity score matching), instrument variable estimates, regression discontinuity designs and selection correction models are presented and practiced in statistical programs.
See certificate
GESIS
Kausale Mediationsanalyse
The investigation of causal relationships often goes hand in hand with the question of the processes and mechanisms underlying these relationships and thus potential mediators. The more recent literature on causal inference shows that causal diagrams and the counterfactual conceptualization of direct and indirect causal effects are crucial tools for making transparent the conditions under which causal mediation analysis allows valid conclusions about direct and indirect effects. Procedures that provide information on how strongly the results can be influenced by violating individual assumptions regarding content are also dealt with (i.e., sensitivity analysis).
See certificate

Teaching

Leadership in formal education settings

Ruhr-Universität Bochum

Political Science Section

  • (Master) Health policy in international comparison – Instructor (Summer ‘21) Link / Eval.
  • (Master) International comparison of labour market policies. Why do they differ? What impact does the EU have? – Instructor (Winter ‘20) Link / Eval.
  • (Master) Erklärung unterschiedlicher Gesundheitspolitiken in Europa - Instructor(Summer ‘20) Link
  • (Bachelor) Arbeitsmarktpolitik im Vergleich – Instructor (Winter ‘19) Link / Eval.
  • (Bachelor) Gesundheitspolitik im Vergleich – Instructor (Summer ‘19) Link / Eval.
  • (Bachelor) Methoden der Vergleichenden Politikwissenschaft - Instructor (Winter ‘18) Link

Ruhr-Universität Bochum

Methodenzentrum

  • (Workshop) Working with Strings in R (Winter ‘21) Slides
  • (Workshop) Web-Scraping in R (Winter ‘21, Summer ‘21) Slides
  • (Workshop) (Web-)Apps with R-Shiny (Winter ‘21, Summer ‘21) Slides
  • (Workshop) Introduction to R (Summer ‘21, Winter ‘20, Summer ‘20) Slides
  • (Workshop) Moderne Kausalanalyse. Rubin Causal Model und Directed Acyclic Graphs (Winter ‘18) Link

Ruhr-Universität Bochum

Social Policy & Social Economy Section

  • (Bachelor) Postkeynesianische Wirtschaftspolitik als Alternative zur ökonomischen Orthodoxie? – Instructor (Summer ‘16)

Ruhr-Universität Bochum

Romanic Seminar

  • (Bachelor) Einführung in die Wirtschafts und Sozialpolitik für L.E.A. Studierende – Instructor (Winter ‘18)
  • (Bachelor) Einführung in die Wirtschafts und Sozialpolitik für L.E.A. Studierende – Instructor (Winter ‘17)
  • (Bachelor) Einführung in die Wirtschafts und Sozialpolitik für L.E.A. Studierende – Instructor (Winter ‘16)

Projects

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Recent & Upcoming Talks

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