Quant Center

We don't want to leave Webster Vienna students hanging when they hit a snag in their math or stats courses, and that's why the Quant Center exists. So, if you need help, you're not alone! From Fall 2019, students seeking mathematics or statistics guidance may approach any of the faculty members listed in the table below during their office hours. The method of instruction may be affected by regulations put in place in response to the current COVID-19 pandemic (e.g. meetings may take place via Zoom). 

What To Expect

You can approach a Quant Center faculty member if you...

… are having trouble understanding a math or statistics assignment.
… are looking for guidance or study tips for an upcoming math or statistics exam.
… have a math or statistics question related to your thesis project or research. (See "Areas of Expertise" in the table below)

Quant Center Faculty Members

Faculty listed below are available during their office hours for drop-in appointments. This table will be updated when office hours change.

Name Office Areas of Expertise (Research Methodology) Office Hours in Fall 2020
Dr. Nikolaos Antonakakis 1.04 • Time Series Econometrics: OLS, IV, GMM, ARMA, Cointegration, (S)VAR, GARCH-type models
• Cross-Section Econometrics: OLS, GLS, IV, 2SLS, 3SLS, Dif-in-Dif (DD)
• Panel Data Econometrics: Static & Dynamic models
• Spatial Econometrics
Tuesday &
Dr. Meng Chen 2.16 • Experimental design
• Surveys
• Quantitative content analysis
• Network analysis
• Semantic analysis
• T-test, ANOVA, Regression, Structural Equation Modeling
Monday &
Dr. Ronald Hochreiter 3.26 • Contemporary Statistics and Statistical Learning using R
• Data Science (Machine Learning, Deep Learning, Statistical AI) using R and Python
• Decision Science (Optimization under Uncertainty, Stochastic and Robust Programming)
• Heuristic Optimization (including nature-inspired algorithms)
Tuesday by appointment.
Thursday 10:00-11:00.
Appts. pref. by Zoom
Dr. Marc Mehu 3.19 • Research design (experimental / non-experimental)
• Nonverbal behavior analysis / Social perception
• Descriptive statistics
• Inferential statistics: General Linear Model (correlation, regression, ANOVA, t-test, factor analysis)
• Non-parametric statistics
• Categorical data analysis (log-linear analysis, Chi square)
Fall 1
Monday &

Fall 2
Tuesday &
Dr. Anatoly Reshetnikov 2.06 • (Visual) Discourse analysis
• Ethnographic methods: interview, participant observation, digital ethnography
in Fall 1: