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Prof. Gabriela Alves Werb, Ph.D.

Professorship for Business Information Systems

Prof.
Gabriela Alves Werb, Ph.D.
Building BCN (City Gate), Room 301

LinkedIn

https://orcid.org/0000-0002-7724-2871

Focus Areas

  • Digital Transformation
  • Information Systems Management
  • Data Science
  • Sustainable Finance

About

Gabriela Alves Werb holds the Professorship for Business Information Systems at Frankfurt University of Applied Sciences. She teaches in the Business Informatics B.Sc. and M.Sc. degree programs.

She is a founding member of the Sustainable Finance Research Lab (SuFiRe), an interdisciplinary and cross-departmental research group dedicated to topics in sustainable finance. The group's activities include research projects with academic and industry partners, research seminars, courses, and thesis supervision. She is also a member of the U!REKA Center of Expertise Transition to Circular Society. U!REKA is a European alliance of universities of applied sciences and regional partners working together to address a wide range of future societal challenges.

Since the winter semester 2022/2023, she has held an Innovation Professorship funded by the Federal Ministry of Education and Research (BMBF). In this role, she leads the Sustainability Monitor project. The project aims to close existing gaps in sustainability-related data using artificial intelligence. This step is crucial for increasing transparency regarding corporate sustainability performance and driving the transition toward a sustainable economy. The current prototype and further details are available at www.sustainabilitymonitor.org. 

Furthermore, she is a Data Science Expert at the Research Data and Service Centre (RDSC) of the Deutsche Bundesbank. The RDSC is part of the German Data Forum (RatSWD) network and integrates data from various internal and external sources to provide high-quality microdata for academic research projects.

Previously, Gabriela Alves Werb conducted research as a doctoral candidate at Goethe University Frankfurt and the Leibniz Institute for Financial Research SAFE.

She earned her degree in Engineering from the Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio). She completed her M.Sc. and Ph.D. in Management within the doctoral program of the Graduate School of Economics, Finance, and Managemen (GSEFM). GSEFM is a joint graduate school of Goethe University Frankfurt, Johannes Gutenberg University Mainz, and Technical University of Darmstadt, offering quantitative, research-oriented doctoral programs. She graduated summa cum laude in 2020 (first supervisor Prof. Dr. Bernd Skiera, second supervisor Prof. Guido Friebel, Ph.D.).

In her free time, Gabriela Alves Werb is actively involved in social projects that promote the integration of children and young adults with a migration background through education, and empower women and girls in STEM careers.

Research
HAYS
  • Award for Business Development 
  • Award for Goal-Oriented Business Development 
  • Top #5 Fee Maker in Brazil
  • Top #3 for New Business Deals in Brazil
IBM
  • IBM Global Financing Hero Award
  • Thanks! Award (Contributions to the Latin America Pricing Team)
  • Thanks! Award (Teamawork)
  • Thanks! Award (Implementation of the LA Business Partner Report)
Press Articles

 

Interviews / Digital Content

 

Talks
  • Euro20+ Event Series, Frankfurt (Nov 2025): Data is an anchor of our democracy – How can we protect it?
  • Data Science Forum Rhein-Main 2025, Darmstadt (May 2025): German Data Science Days Regional Group Rhein-Main. Beneath the Tip of the Climate Data Iceberg: The Potential of Unstructured Data.
  • 42nd TDWI Roundtable Frankfurt (Feb 2025): The Data Warehousing Institute. Innovation in Climate-Related Data: Leveraging Unstructured Data to Close Data Quality Gaps.
  • Climate Risks and Central Banks Seminar Series, Online (Apr 2023): Machine Learning and Artificial Intelligence for Sustainability.
  • Hessenhub Impulse Series, Online (Apr 2023): Artificial Intelligence: Current Developments and Implications for Higher Education.
  • Mentoring Hessen Panel Discussion, Challenges in Academic Careers, Online (Apr 2023): Mobility, Flexibility, and Possible Career Paths.
  • Expert Panel on Machine Learning, Artificial Intelligence and Big Data, Online (Nov 2022): Machine Learning and Artificial Intelligence for Sustainability.
  • Research Day, Frankfurt UAS (Nov 2022): Sustainability Monitor @ FRA-UAS.
  • STEM Lecture Series at Carl-Schurz-Schule, Frankfurt (Nov 2022): Business Informatics and Interdisciplinarity: How do algorithms, digital marketing, and sustainability fit together?
  • Climate Change Seminar Series, Online (Oct 2022): Artificial Intelligence for Sustainability.
  • SEACEN Data Analytics for Macroeconomic Surveillance Workshop, Online (Sep 2022): Deep Learning: An Overview of Methods and Applications.
  • SEACEN Data Analytics for Macroeconomic Surveillance Workshop, Online (Nov 2021): Predictive Modeling: Ensemble Methods for Response Modeling. Shedding Light on the Black Box of Ensemble Methods.
  • 50th Anniversary Ceremony of Frankfurt UAS (Sep 2021): Can we still find the shop around the corner?
  • Hessen Technikum University Day, Online (Jan 2021): Machine Learning in Everyday Life – Applications and Live Examples.
  • ITCS Summit, Frankfurt (Dec 2019): Towards Algorithmic Transparency: Shedding Light on the Black Box.
  • Science Slam, Mainz (Nov 2019): A Journey to the Stars.
  • Interdisciplinary Forum Method Center 2019 Data Science (Jun 2019): Machine Learning: Practice and Research-Oriented Applications.
  • Keynote Speech, Dean's List Event, Faculty of Business and Law (May 2019): The "Ins and Outs" of an Academic Career.
  • Spot on Marketing-Science, Marketing Club Frankfurt (Dec 2018): The Value of Organic Search Visibility.
  • E-Finance Lab Spring, Frankfurt (Feb 2018): Leveraging Multiple Data Sources to Measure a Firm's Risk in Organic Search.
  • Science Slam for Female Researchers, Frankfurt (Dec 2017): Death by Invisibility.
Courses and Workshops
  • Workshop for members of the Center for Latin American Monetary Studies (CEMLA) and Central Bank employees in Latin America (Sep/2026, Sep/2025, Aug/2024): Machine Learning and Central Banking
  • Workshop for members of the Center for Latin American Monetary Studies (CEMLA) and Central Bank employees in Latin America (Mar/2025, Sep/2024, Apr/2023, Sep/2022, Mar/2021, Nov/2020): Introduction to Machine Learning.
  • Workshop for Central Bank employees worldwide (Mar 2023, Jul 2022, Mar 2021): Introduction to Machine Learning.
  • Workshop for practitioners and researchers, 82nd VHB Annual Conference, Frankfurt (Mar 2020): Towards Interpretable Machine Learning: An Overview of Current Techniques to Shed Light on the Black Box.
  • Workshop for practitioners and researchers, E-Finance Lab Spring Conference, Frankfurt (Feb 2018): Text Mining with R.

Research

In her research, Gabriela Alves Werb focuses on projects at the intersection of marketing, finance, and business informatics aimed at solving relevant practical problems for consumers, investors, and industry decision-makers.

Her empirical research relies on diverse data sources—including corporate, stock market, and search engine data, as well as unstructured content. She analyzes these using established econometric methods as well as machine learning and artificial intelligence techniques.

Within the international academic community, Gabriela Alves Werb is active in organizing workshops and serving as a reviewer for academic conferences such as the European Conference on Information Systems (ECIS) and the International Conference on Information Systems (ICIS). 

Her research projets were (among others) supported by the Deutsche Forschungsgemeinschaft (DFG), the Bundesministerium für Bildung und Forschung, the  E-Finance Lab and the Vereinigung von Freunden und Förderern der Goethe-Universität.

Topics
  • Digital Markets
  • Stock Markets
  • Sustainability Reporting
  • Climate-related Risks
  • Leveraging Unstructured Data
Methods
  • Machine Learning
  • Deep Learning
  • Natural Language Processing / Large Language Models (LLM)
  • Time Series
  • Natural Experiments
  • Monte Carlo Methods
  • Econometrics
Refereed Publications and Conference Proceedings

Doll, H.C., Kormanyos, E., Walter, S., und Alves Werb, G. (Forthcoming). Beneath the Climate Data Iceberg: Enabling Financial Regulators to Uncover Hidden Insights with Artificial Intelligence. In Bonnie G. Buchanan & Helen Packard (Eds.), Understanding Artificial Intelligence and Finance. Cheltenham, UK: Edward Elgar Publishing.

Yüksel, A., Thiem, G., Walter, S., Felka, P., Werb, G. A., & Habernal, I. (2026). MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics, San Diego, California, United States, 2026, pp. 14790-14814, 10.18653/v1/2026.acl-long.674/

Doll, H.C., Kormanyos, E., Walter, S., und Alves Werb, G. (2026). The Climate Data Iceberg – A Depth of Information to Integrate. IFC Bulletin (Vol. 66). Bank for International Settlement, pp. 1076-1105, 

Alves Werb, G., Felka, P., Reichenbach, L., Walter, S., und Yalcin-Roder, E. (2024). Geospatial Data and Multimodal Fact-Checking for Validating Company Data. 2024 IEEE International Conference on Big Data (BigData), Washington, DC, USA, 2024, pp. 3329-3332, https://doi.org/10.1109/BigData62323.2024.10825029

Doll, H. C., & Alves Werb, G. (2023). Innovation for Improving Climate-Related Data—Lessons Learned from Setting Up a Data Hub. AStA Wirtschafts-und Sozialstatistisches Archiv, 17(3), 355-380. doi.org/10.1007/s11943-023-00326-w

Doll, H. C., Fehr, M., Yalcin-Roder, E., and Werb, G. A. (2023). Measuring the Emission Profile of Self-Proclaimed Sustainable Exchange-Traded Funds. IFC Bulletin (Vol. 58). Bank for International Settlements.

Alves Werb, G. and Schmidberger, M. (2021), "Predictive Modeling in Marketing: Ensemble Methods for Response Modeling", Die Unternehmung – Swiss Journal of Business Research and Practice, 75(3), 376-396. doi.org/10.5771/0042-059X-2021-3-376

 

Working Papers

Alves Werb, G. and Skiera, B. (2022), "Visibility-at-Risk: Measuring Firms’ Risk of Visibility Losses in Organic Search Results", Working paper.

Alves Werb, G. (2020), "The Google Effect: Linking Organic Search Visibility to Shareholder Value", Working paper.

Alves Werb, G.,and Paul, T. (2020), "In Reviews We Trust: The Dark Side of Review Incentive Programs", Working paper.

 

Management-oriented Publications

Alves Werb, G. and Skiera, B. (2019), "Visibility in Organic Search: Why Should Managers and Investors Care about It?", E-Finance Lab Quarterly 03/2019, EFL - The Data Science Institute.

 

  • Data Science Forum Rhein-Main 2025 - German Data Science Days Regionalgruppe Rhein-Main. Unter der Spitze des Klimadaten-Eisbergs: Das Potenzial unstrukturierter Daten (Darmstadt, Mai/2025)

  • 2. Conference on Data Innovation for Future of Regulation - Financial Conduct Authority, UK. Innovation for Improving Climate-Related Data. (London, Jul/2024).

  • efl Annual Conference 2023 - Goethe Universität Frankfurt. Harnessing AI to Reshape the Sustainability Data Landscape (Frankfurt, Nov/2023)

  • German Data Science Days 2023 - LMU München. Data Orchestration: Bringing Together Economics and Data Science (Munich, Mar/2023)

  • 16th Symposium on Statistical Challenges in Electronic Commerce Research (Madrid, Jun/2020 – online)

  • Finance Brown Bag Seminar (Frankfurt, Mai/2020)

  • 49th Annual Conference of The European Marketing Academy (Budapest, Mai/2020 – conference cancelled)

  • 82nd Annual Business Researcher Conference (Frankfurt, Mar/2020)

  • 30th Workshop on Information Systems and Economics (Munich, Dez/2019)

  • Marketing Research Seminar (Riezlern, Sep/2019)

  • E-Finance Lab Jour Fixe (Frankfurt, Sep/2019)

  • 6th Marketing Strategy Meets Wall Street Conference (Fontainebleau, Jun/2019)

  • 2019 INFORMS Marketing Science Conference (Rome, Jun/2019)

  • 48th Annual Conference of The European Marketing Academy (Hamburg, Mai/2019)

  • Marketing Research Seminar (Riezlern, Sep/2018)

  • 2018 ISBM Academic Conference (Boston, Aug/2018)

  • 2018 INFORMS Marketing Science Conference (Philadelphia, Jun/2018)

  • 15th Symposium on Statistical Challenges in Electronic Commerce Research (Rotterdam, Jun/2018)

  • 16th ZEW Conference on the Economics of Information and Communication Technologies (Mannheim, Jun/2018)

  • 9th Theory + Practice in Marketing Conference (Los Angeles, Mai/2018)

  • 47th Annual Conference of The European Marketing Academy (Glasgow, Mai/2018)

  • Finance Brown Bag Seminar (Frankfurt, Apr/2018)

Teaching

The thesis is an important milestone in your studies, and it is crucial that you approach this process well prepared.

Based on experience, my supervision capacity is already exhausted before the start of the semester. Therefore, you should contact me at least one month before the start of the semester if you would like me to supervise your thesis. Furthermore, we must discuss your desired topic in detail before I can agree to supervise your thesis.

Please read through my guidelines for writing final theses. This document contains further information on formulating your topic/research question and additional steps for completing your thesis.

You will be working intensively on your thesis, so the research question should be engaging for you. My suggestion is that you read up on a topic that interests you, or try to identify current problems and questions through discussions with others (e.g., at your workplace).

Afterwards, please briefly address (approx. one DIN A4 page) the following questions:

  1. Which problem would you like to solve or which research question would you like to investigate?
  2. Why is your research question or problem interesting and non-trivial (or: why is the answer to this question not obvious)?
  3. How do you plan to address this research question or solve this problem (e.g., based on which data, empirical studies, or methods)?
  4. How does your approach compare to existing attempts to solve this problem?

We will use this initial draft as the basis for our first discussion.

Note on topics related to ERP systems: A system migration/implementation can provide a good opportunity for a scientific study. However, you should avoid having your thesis become a purely descriptive text about the migration or the system itself. From a scientific perspective, this is not interesting and is insufficient for a thesis. While many of the questions that arise during an ERP implementation are important operational questions, they are difficult to examine systematically within the scope of an academic thesis. Therefore, please consider which specific aspects of the new system, the adapted business processes, or the overall migration would be well-suited for a systematic investigation.

Exposé

Preparing an exposé requires a certain amount of effort, but it is an important preparatory step to ensure you can approach your thesis in a structured manner. Please expect that it usually takes a few feedback iterations until your exposé is "fine-tuned" for the official thesis registration. You will benefit greatly from this during the actual writing phase.

Once we have agreed on your exposé, you can use this document to look for a second reviewer. This person can also come from industry (e.g., for theses conducted with a practice partner), provided they satisfy the requirements of your degree program's examination regulations and examination office.

Language of the Thesis

You can write your thesis in German or English. If you are enrolled in a German-taught degree program, you will need approval from the examination committee to write your thesis in English. You can request this informally with a JIRA ticket to your responsible examination office.

Registration and Submission

You are responsible for registering and submitting your thesis on time and in accordance with the formal requirements of your examination office. Registration forms and further information for Department 2 students can be found at the following link.

Execution

You can find the execution time for your thesis in the confirmation email sent by the examination office upon registration. As a general rule, you have 9 weeks for Bachelor's theses and 22 weeks for Master's theses.

During the processing period, we will meet at regular intervals to discuss your progress and any open questions. You have the freedom, but also the responsibility, to arrange these appointments with me independently. Please note that I will only read your thesis in full after submission. There will be no step-by-step "approval" or pre-reading of individual chapters or the entire draft.

After submission, we will grade your thesis and schedule a date for your colloquium within a few weeks. During the colloquium, you will present your work and answer our questions.

The total duration of the colloquium and its weighting towards your overall thesis grade can be found in your degree program's examination regulations. Please plan for a presentation time of approximately 20 minutes, followed by a Q&A session.

During the presentation, you should provide an overview of your thesis covering the following points:

  • Research Question (what problem do you want to solve)
  • Existing Approaches / Literature (previous attempts to solve this problem)
  • Proposed Methodology
  • Data Collection (if applicable)
  • Evaluation (e.g., data analysis)
  • Results
  • Implications (what can we learn from your findings?)
  • Limitations
  • Conclusion
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last updated on: 10.06.2026