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Vinícius Ferraz

Data and A.I. Products Specialist

Researcher in Machine Learning applied to economics and business problems

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I am a researcher specializing in computational and experimental economics, working at the intersection between economics and computer science. My academic contributions primarily focus on developing and applying computational models to address complex business and economic challenges.

Parallel to my academic pursuits, I hold the position of Chief Data and AI Officer at ILI.DIGITAL AG, leading the Data and AI products team. My professional path has been marked by roles in data science, digital strategy, and product development, with former positions at Ernst & Young (EY), Trivago, and Deutsche Telekom.

This website is designed to collect my scholarly work and public engagements, including scientific papers, code repositories, articles, and more.

Research Interests

My research interests are focused on the computational modeling of economics and business problems. This includes studies of decision behavior, economic experiments, game theory, agent-based simulation models, machine learning, and Generative AI.



Analyzing the Impact of Strategic Behavior in an Evolutionary Learning Model Using a Genetic Algorithm. Comput Econ 63, 437–475 (2024)

with T. Pitz

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Working Papers

Trust in the Machine: How Contextual Factors and Personality Traits Shape Algorithm Aversion and Collaboration (2023)

with L. Houf, T. Pitz, C. Schwieren& J. Sickmann


Understanding Dark Personality Traits and Strategic Choices in an Inspection Game: Insights from Machine Learning and Causal Inference (2023)

with L. Houf, T. Pitz & C. Schwieren



Stationary Equilibria in Behavioral Game Theory: An Experimental Analysis of Inspection Games (2022)

with T. Pitz, W. Gardian, D. Kayar & J. Sickmann


Motivated Sampling of Information: Analysis With Experimental Data and Agent-Based Modeling in a Bayesian Framework (2023)

with L. Houf

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Work in Progress

Here you can find an overview of project I am currently working on 

A Large Scale Prediction of Behavior in Completely Mixed Games: A Machine-Learning-based approach

with R. Nagel

Description: This project involves a machine learning analysis of 2x2 game frameworks, using data from multiple experimental studies. The approach employs a feature-engineered dataset to glean insights into the anatomy of these game scenarios, as reported in existing literature. The objective is to uncover the factors that significantly impact observed behavior.

Exploring Gender Differences in Interpreting Feedback Through LLM-Driven Simulations in Professional Settings

with C. Scwieren & L. Houf

Description: This research project analyzes gender differences in the interpretation of feedback and confidence levels within a business environment. We use large language models (LLMs) as simulated agents to mimic interactions in a company setting, aiming to understand how gender influences feedback reception and self-assurance in professional contexts.



Heidelberg University
Doctor of Philosophy (Ph.D.) in Computational & Experimental Economics

2020 - 2023

Rhine-Waal University

Master of Science (M.Sc.) in Economics and Finance

2015 - 2017



Current Position
Chief Data and AI Officer


2018 - Present

Previous Positions

Consulting, Product Management, and Data Science at

Deutsche Telekom, EY, Trivago, and Mazda Motor Europe.

Overall Industry Experience

Throughout my career, I have worked in business strategy and management consulting, helping clients optimize their operations. I later shifted my focus to product management, leading the development of digital products using agile methodologies. My career expanded into data science, working technically in data analytics and eventually leading efforts in the design, development, and deployment of AI-powered products and platforms.

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