Ronald Hochreiter

Vienna, Austria // ron@hochreiter.net

Algorithmic Finance. Computational Finance. Quantitative Finance. Analytics in Banking and Finance. Risk Management.
Optimization under Uncertainty and Decision Science. Data Science and Machine Intelligence (Machine Learning and Deep Learning). AI.

Activities

Founding Partner

Trace Health Science GmbH

Revolutionizing Medicine and Health using Artificial Intelligence and Data Science.

since June 2024

Department Head

SFU Sigmund Freud Private University Vienna

Heading the Department of Artificial Intelligence and Health within the SFU Institut für digitale Transformation und künstliche Intelligenz.

since February 2025

Research Consultant

University for Applied Sciences Wiener Neustadt

Building up Expertise in Cybersecurity and Artificial Intelligence for the Institute of Security Research.

since December 2023

Guest Professor

University for Continuing Education Krems

Bringing Artificial Intelligence to Business Management - both in research and teaching.

since Winter 2022

Senior Partner

algorithmic.finance

Creating bespoke Quantitative Asset Management Solutions.

since January 2006

Managing Director

Hochreiter Consulting & Holding GmbH / hochreiter.net

Consulting Advanced Analytics, Artificial Intelligence and (Big) Data Science Projects in the area of Management. Designing in-house education and hands-on, use-case-based lecture series as well as organizational implementation strategies.

since May 2000

Positions and Memberships

Positions
  • President and CEO of the Academy of Data Science in Finance (since 2017)
Advisory Councils
  • Member of the Regulatory Sandbox Beirat (Bundesministerium für Finanzen, since 2020)
  • Member of the Public Value Beirat (KommAustria, since 2020)
Memberships
  • Senior Member of the Association for Computing Machinery (ACM)
  • Member of the Austrian Society of Operations Research (OeGOR)
  • Member of the Austrian Statistical Society (OSG)

Previous Projects

Positions at Universities
  • WU Vienna University of Economics and Business (2009-2025) - Assistant Professor (until 2015), Docent (2015-2025)
  • Webster Vienna Private University (2019-2022) - Associate Professor of Finance, Member of Senate
  • University of Bergamo (2008-2017) - Visiting Guest Professor
  • University of Vienna (2001-2009) - (Post-Doc) Researcher
Positions at Societies
  • Vice-President of the Austrian Society of Operations Research (2013-2023)
Advisory Councils
  • Member of the Jury of the Wiener Stadtwerke FTI Innovationsfonds (2020-2024)

Research

Research Grants

  • Exective Board Member and Work Package Leader (AI in Finance) - EU Horizon Europe MSCA Doctoral Networks - 2024-2027 - DIGITAL - Industrial Doctoral Network on Digital Finance
  • Technical Coordinator and Member of the Core Group - EU COST - 2020-2024 - Fintech and Artificial Intelligence in Finance - Towards a Transparent Financial Industry
  • WP-Leader Quality Control and Monitoring - EU Erasmus+ - 2018-2022 - ADA: Curriculum Development Advanced Analytics in Business.
  • Member of the Executive Board, WP-Co-Leader RegTech Workshops & Country Coordinator Austria - EU H2020 - 2019-2021 - FIN-TECH: A FINancial supervision and TECHnology compliance training programme.
  • Principal Investigator - FFG ASAP - 2017-2019 - ReKlaSat 3D - Deep Learning from High-Resolution Satellite Imagery.
  • Principal Investigator - FFG Bridge - 2012-2014 - ALSOpt - Data Mining Analysis of Geo-Laserscan-Data.
  • Country Coordinator - EU TEMPUS - 2010-2013 - Curriculum Development - Master Studies in Applied Statistics in Serbia.
  • Principal Investigator - Austrian National Bank Jubiläumsfonds - 2007-2009 - Models for the valuation of complex credit portfolios using Coupled Markov Chains.

Editorial Boards

  • Frontiers in Artificial Intelligence - AI in Finance / Associate Editor
  • Mendel - Soft Computing Journal / Editorial Advisory Board

Publications

See also Google Scholar or Orcid.

  1. C. Lesa and R. Hochreiter. Cryptocurrency Pair Trading. April 2023. Available at SSRN.
  2. I-E. Tellez-Leon, S. Martinez-Jaramillo, L. Escobar-Farfan, R. Hochreiter. How are network centrality metrics related to interest rates in the Mexican secured and unsecured interbank markets? Journal of Financial Stability. 2021.
  3. S. Bachhofner, A.M. Loghin, J. Otepka, N. Pfeifer, M. Hornacek, A. Siposova, N. Schmidinger, K. Hornik, N. Schiller, O. Kähler, R. Hochreiter. Generalized Sparse Convolutional Neural Networks for Semantic Segmentation of Point Clouds Derived from Tri-Stereo Satellite Imagery. Remote Sensing 12(8): 1289. April 2020.
  4. R. Puchner, A. Vavrovsky, H. Pieringer, R. Hochreiter, K.P. Machold. The Supply of Rheumatology Specialist Care in Real Life. Results of a Nationwide Survey and Analysis of Supply and Needs. Frontiers in Medicine 7: 16. January 2020.
  5. R. Hochreiter and C. Waldhauser. Zombie politics: evolutionary algorithms to counteract the spread of negative opinions. Soft Computing 24(1): 591–601. January 2020.

  1. C. Waldhauser and R. Hochreiter. Shaking the trees: Abilities and Capabilities of Regression and Decision Trees for Political Science. ITM Web of Conferences 14: 9. November 2017.
  2. R. Puchner, R. Hochreiter, H. Pieringer, A. Vavrovsky. Improving patient flow of people with rheumatoid arthritis has the potential to simultaneously improve health outcomes and reduce direct costs. BMC Musculoskeletal Disorders 18(1): 7. January 2017.
  3. G. Kieselbach, A. Vavrovsky and R. Hochreiter. Real life data of intravitreal injections in Austria in 2013. Spektrum der Augenheilkunde Volume 30(3): 106-110. June 2016.
  4. L. Vana, R. Hochreiter and K. Hornik. Computing a journal meta-ranking using paired comparisons and adaptive lasso estimators. Scientometrics 106(1): 229-251. January 2016.
  5. R. Hochreiter. Modeling multi-stage decision optimization problems. Lecture Notes in Economics and Mathematical Systems 682: 209-214. January 2016.
  6. R. Hochreiter. Computing trading strategies based on financial sentiment data using evolutionary optimization. Advances in Intelligent Systems and Computing 378: 181-191. June 2015.
  7. R. Hochreiter and C. Waldhauser. Evolving Accuracy: A Genetic Algorithm To Improve Election Night Forecasts. Applied Soft Computing 34: 606–612. June 2015.
  8. R. Hochreiter. An Evolutionary Optimization Approach to Risk Parity Portfolio Selection. Lecture Notes in Computer Science 9028: 279-288. March 2015.
  9. G. Kodydek, R. Hochreiter, and E.A. Ochome. Students’ Ethical Judgment and Moral Intentions toward Business Ethics: Kenya versus Austria. Academy of Management Proceedings 2014(1): 17409. 2014.
  10. G. Kodydek and R. Hochreiter. The influence of personality characteristics on individual competencies of work group members. Organizacija 46(5): 196-204. October 2013.
  11. C. Waldhauser, R. Hochreiter, J. Otepka, N. Pfeifer, S. Ghuffar, K. Korzeniowska and G. Wagner. Automated classification of airborne laser scanning point clouds. In: Solving Computationally Expensive Engineering Problems. Springer Proceedings in Mathematics & Statistics 97: 269-292. September 2014.
  12. R. Hochreiter and C. Waldhauser. Data Mining Cultural Aspects of Social Media Marketing. Lecture Notes in Computer Science 8557: 130-143. July 2014.
  13. R. Puchner, R. Hochreiter, A. Vavrovsky. Improving patient flow of people with rheumatoid arthritis has the potential to simultaneously improve health outcomes and reduce direct costs. Wiener Klinische Wochenschrift 126(S5): P05.07. 2014.
  14. A. Vavrovsky and R. Hochreiter. COPD: Abschätzung der Zusatzkosten einer Therapie mit Heimsauerstoff. JATROS - Pulmologie & HNO 2014(2): 12-14. 2014.
  15. A. Vavrovsky and R. Hochreiter. A novel approach to assessing the total costs of obstructive sleep apnoea in Austria: using population attributable fractions of the most commonly associated disorders. Pneumologie 68(S01): V322. March 2014.
  16. A. Vavrovsky and R. Hochreiter. Estimating the incremental costs of home oxygen therapy for chronic obstructive pulmonary disease (COPD) in Austria using a microsimulation approach. Pneumologie 68(S01): P309. March 2014.
  17. R. Hochreiter and C. Waldhauser. A stochastic simulation of the decision to retweet. Lecture Notes in Computer Science 8176: 221-229. November 2013.
  18. J. Otepka, S. Ghuffar, C. Waldhauser, R. Hochreiter and N. Pfeifer. Georeferenced Point Clouds: Data Model, Features and Management. ISPRS International Journal of Geo-Information 2(4): 1038-1065. November 2013.
  19. H. Kasper, G. Kodydek, S. Schilcher and R. Hochreiter. Keeping the Best - Human Resources in Subsidiaries of Sino-European Multinational Companies located in P.R. China. Volume 44 of Advances in Intelligent Systems Research: 112-115. August 2013.
  20. R. Hochreiter and C. Waldhauser. Solving Dynamic Optimisation Problems with Revolutionary Algorithms. International Journal of Innovative Computing and Applications 5(3): 143-151. August 2013.
  21. R. Hochreiter and G. Krottendorfer. Robust Estimation of Vector Autoregression (VAR) Models Using Genetic Algorithms. Lecture Notes in Computer Science 7835: 223-233. April 2013.
  22. D. Wozabal and R. Hochreiter. A Coupled Markov Chain Approach to Credit Risk Modeling. Journal of Economic Dynamics and Control 36(3): 403-415. March 2012.
  23. J. Dang, D. Edelman, R. Hochreiter and A. Brabazon. Swarm Intelligence-based Stochastic Programming Model for Dynamic Asset Allocation. IEEE CEC 2010: 1-8. July 2010.
  24. R. Hochreiter and D. Wozabal. A multi-stage stochastic programming model for managing risk-optimal electricity portfolios. Handbook of Power Systems II. Energy Systems, Volume 4: 383-404. Springer, May 2010.
  25. R. Hochreiter and D. Wozabal. Evolutionary Estimation of a Coupled Markov Chain Credit Risk Model. Studies in Computational Intelligence 293: 31-44. 2010.
  26. D. Wozabal, R. Hochreiter, and G. Ch. Pflug. A D.C. Formulation of Value-at-Risk constrained optimization. Optimization 59(3): 377-400. May 2010.
  27. R. Hochreiter. Evolutionary multi-stage financial scenario tree generation. Lecture Notes in Computer Science 6025: 182-191. 2010.
  28. R. Hochreiter. Algorithmic aspects of scenario-based multi-stage decision process optimization. Lecture Notes in Computer Science 5783: 365–376. 2009.
  29. R. Hochreiter and D. Wozabal. Evolutionary approaches for estimating a Coupled Markov Chain model for Credit Portfolio Risk Management. Lecture Notes in Computer Science 5484: 193-202. 2009.
  30. R. Hochreiter, C. Wiesinger, and D. Wozabal. Discussion of ‘The evolution of web-based optimisation: From ASP to e-Services’. Decision Support Systems 47(1): 72-73. 2009.
  31. H. Schabauer, R. Hochreiter, and G. Ch. Pflug. Parallelization of pricing path-dependent financial instruments on bounded trinomial lattices. Lecture Notes in Computer Science 5102: 408-415. 2008.
  32. R. Hochreiter. Evolutionary stochastic portfolio optimization. Studies in Computational Intelligence 100: 67-87. 2008.
  33. W. Wiesemann, R. Hochreiter, and D. Kuhn. A Stochastic Programming Approach for QoS-Aware Service Composition. IEEE CCGRID 2008: 226-233. 2008.
  34. R. Hochreiter, G. Ch. Pflug, and V. Paulsen. Design and management of unit-linked life-insurance contracts with guarantees. Handbook of Asset and Liability Management, Volume 2. Chapter 14: 627-662. Elsevier/North-Holland. 2008.
  35. R. Hochreiter. An evolutionary computation approach to scenario-based risk-return portfolio optimization for general risk measures. Lecture Notes in Computer Science 4448: 199-207. 2007.
  36. R. Hochreiter and G. Ch. Pflug. Financial scenario generation for stochastic multi-stage decision processes as facility location problems. Annals of Operations Research 152(1): 257-272. 2007.
  37. R. Hochreiter and G. Ch. Pflug. Polynomial algorithms for pricing path-dependent interest rate instruments. Computational Economics 28(3): 291-309. 2006.
  38. R. Hochreiter, G. Ch. Pflug, and D. Wozabal. Multi-stage stochastic electricity portfolio optimization in liberalized energy markets. IFIP Advances in Information and Communication Technology 199: 219-226. 2006.
  39. R. Hochreiter. Audible convergence for optimal base melody extension with statistical genre-specific interval distance evaluation. Lecture Notes in Computer Science 3907: 712-716. 2006.
  40. S. Hochrainer, R. Hochreiter, and G. Ch. Pflug. An algorithm for calculating steady state probabilities of $M|E_r|c|K$ queueing systems. Central European Journal of Operations Research 13(1): 1-13. 2005.
  41. R. Hochreiter, C. Wiesinger, and D. Wozabal. Large-Scale Computational Finance Applications on the Open Grid Service Environment. Lecture Notes in Computer Science 3470: 891-899. 2005.
  42. C. Wiesinger, D. Giczi, and R. Hochreiter. An open grid service environment for large-scale computational finance modeling systems Lecture Notes in Computer Science 3036: 83-90. 2004.

Theses

  • R. Hochreiter. Financial Decision Optimization and Risk Management Methodology and Applications. Habilitation Thesis. WU Vienna University of Economics and Business. 2013.
  • R. Hochreiter. Computing Optimal Management Decisions - The Case of Stochastic Programming for Financial Management. Ph.D. Thesis. Supervisor: Georg Ch. Pflug. University of Vienna. 2005.
  • R. Hochreiter. Optimierung und Visualisierung von Finanzrisken. Masters Thesis (in German). Supervisor: Georg Ch. Pflug. University of Vienna. 2001.

Selected Conference Proceedings

Unpublished Manuscripts

Editorial

  1. P. Giudici, R. Hochreiter, J. Osterrieder, J. Papenbrock, and P. Schwendner. Frontiers in Artificial Intelligence - Artificial Intelligence in Finance Volume 2: 25. November 2019: P. Giudici, R. Hochreiter, J. Osterrieder, J. Papenbrock, and P. Schwendner. Editorial - AI and Financial Technology.
  2. C. Erlwein-Sayer and R. Hochreiter. Computational Management Science Volume 15, Number 2: 135-137. June 2018: C. Erlwein-Sayer and R. Hochreiter. Twenty-five years of Applied Mathematical Programming and Modelling. Computational Management Science 15(2): 135-318. 2018.
  3. R. Hochreiter. ITM Web of Conferences Volume 14: 1-9. November 2017: R. Hochreiter. Applied Mathematical Programming and Modelling 2016. ITM Web of Conferences 14: 1. 2017.
  4. G. Ch. Pflug and R. Hochreiter. Annals of Operations Research Volume 193, Number 1: 1-289. March 2012: G. Ch. Pflug and R. Hochreiter. Applied Mathematical Programming and Modelling 2008. Annals of Operations Research 193(1): 1-2. 2012.
  5. R. Hochreiter and D. Kuhn. Computational Management Science Volume 9, Number 1: 1-160. February 2012: R. Hochreiter and D. Kuhn. Optimal Decision Making under Uncertainty. Computational Management Science 9(1): 1-2. 2012.
  6. R. Hochreiter and G. Ch. Pflug. Optimization Volume 59, Number 3: 321-445. May 2010: R. Hochreiter and G. Ch. Pflug. 11th International Conference on Stochastic Programming. Optimization 59(3): 321-322. 2010.
  7. R. Hochreiter and G. Ch. Pflug. Computational Management Science Volume 6, Number 2: 115-267. May 2009: R. Hochreiter and G. Ch. Pflug. Introduction to the special issue on computational optimization under uncertainty. Computational Managament Science 6(2): 115-116. 2009.

Teaching

Teaching

Ronald is currently taking a break from active undergraduate and graduate teaching, mainly to focus on the preparation of his forthcoming textbook. He is still teaching Executive Education programs and various lectures as Guest Professor.

WU Vienna University of Economics and Business

  • Summer 2023 - 5351 Data Science: Access to Specialisation in Business Administration
  • Summer 2023 - 5065 Data Science V: Industry Lab
  • Winter 2022 - 1108 Data Science: Access to Specialisation in Business Administration
  • Winter 2022 - 1657 Data Science V: Industry Lab
  • Winter 2022 - 1540 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Summer 2022 - 5484 Data Science: Access to Specialisation in Business Administration
  • Summer 2022 - 5159 Data Science V: Industry Lab
  • Winter 2021 - 1720 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2021 - 1854 Data Science V: Industry Lab
  • Summer 2021 - 5273 Data Science V: Industry Lab
  • Winter 2020 - 1957 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2020 - 1352 Data Science II: Data Analytics
  • Winter 2020 - 2120 Data Science II: Data Analytics
  • Winter 2020 - 2117 Data Science V: Industry Lab
  • Winter 2020 - 1372 Data Science: Access to Specialisation in Business Administration
  • Summer 2020 - 5426 Data Science V: Industry Lab
  • Summer 2020 - 5926 Data Science: Access to Specialisation in Business Administration
  • Winter 2019 - 0678 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2019 - 1083 MSc Marketing - Advanced Marketing Research Methods
  • Winter 2019 - 2072 Finance V: Quantitative Methods in Finance
  • Winter 2019 - 1636 Data Science II: Data Analytics
  • Winter 2019 - 1848 Data Science V: Industry Lab
  • Winter 2019 - 1661 Data Science: Access to Specialisation in Business Administration
  • Summer 2019 - 4969 MSc Marketing - Advanced Marketing Research Methods
  • Summer 2019 - 4701 Finance V: Quantitative Optimization Methods in Finance
  • Summer 2019 - 5568 Data Science II: Data Analytics
  • Summer 2019 - 5588 Data Science V: Industry Lab
  • Summer 2019 - 5516 Data Science: Access to Specialization in Business Administration
  • Winter 2018 - 0678 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2018 - 1083 MSc Marketing - Advanced Marketing Research Methods
  • Winter 2018 - 2072 Finance V: Quantitative Methods in Finance
  • Winter 2018 - 1636 Data Science II: Data Analytics
  • Winter 2018 - 1848 Data Science V: Industry Lab
  • Winter 2018 - 1661 Data Science: Access to Specialisation in Business Administration
  • Summer 2018 - 5053 MSc Marketing - Advanced Marketing Research Methods
  • Summer 2018 - 4751 Finance V: Quantitative Optimization Methods in Finance
  • Summer 2018 - 5756 Data Science II: Data Analytics
  • Summer 2018 - 5781 Data Science V: Industry Lab
  • Summer 2018 - 5687 Data Science: Access to Specialisation in Business Administration
  • Winter 2017 - 0722 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2017 - 1175 MSc Marketing - Advanced Marketing Research Methods
  • Winter 2017 - 1834 Data Science II: Data Analytics
  • Winter 2017 - 2098 Data Science V: Industry Lab
  • Winter 2017 - 1864 Data Science: Access to Specialisation in Business Administration
  • Summer 2017 - 4815 Finance V: Quantitative Optimization Methods in Finance
  • Summer 2017 - 6037 Data Science II: Data Analytics
  • Summer 2017 - 5955 Data Science: Access to Specialisation in Business Administration
  • Winter 2016 - 1293 MSc Marketing - Advanced Marketing Research Methods
  • Winter 2016 - 0782 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2016 - 2197 Data Science II: Data Analytics
  • Winter 2016 - 2230 Data Science: Access to Specialisation in Business Administration
  • Summer 2016 - 6095 PhD - Financial Decision Science
  • Summer 2016 - 4882 Finance V: Quantitative Optimization Methods in Finance
  • Winter 2015 - 0820 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2015 - 0945 Finance V: Quantitative Methods in Finance
  • Summer 2015 - 4944 Finance V: Quantitative Optimization Methods in Finance
  • Summer 2015 - 4967 Management III: Operative Grundlagen des Managements
  • Summer 2015 - 4968 Management III: Operative Grundlagen des Managements
  • Winter 2014 - 0901 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2014 - 1047 Finance V: Quantitative Methods in Finance
  • Winter 2014 - 0184 Management III: Operative Grundlagen des Managements
  • Winter 2014 - 1028 Management III: Operative Grundlagen des Managements
  • Summer 2014 - 5066 Finance V: Quantitative Optimization Methods in Finance
  • Summer 2014 - 5094 Management III: Operative Grundlagen des Managements
  • Summer 2014 - 5095 Management III: Operative Grundlagen des Managements
  • Winter 2013 - 1168 Finance V: Quantitative Methods in Finance
  • Winter 2013 - 1883 MSc Information Systems - Data Mining and Decision Support Systems
  • Winter 2013 - 1012 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2013 - 0208 Management III: Operative Grundlagen des Managements
  • Winter 2013 - 1148 Management III: Operative Grundlagen des Managements
  • Summer 2013 - 4017 Statistik
  • Summer 2013 - 5337 Finance V: Quantitative Optimization Methods in Finance
  • Summer 2013 - 5377 Management III: Operative Grundlagen des Managements
  • Winter 2012 - 2261 MSc Information Systems - Data Mining and Decision Support Systems
  • Winter 2012 - 1310 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2012 - 1494 Finance V: Quantitative Methods in Finance
  • Summer 2012 - 0017 Statistik
  • Summer 2012 - 1737 Finance V: Quantitative Optimization Methods in Finance
  • Winter 2011 - 0827 Statistik
  • Winter 2011 - 1684 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2011 - 1942 Finance V: Quantitative Methods in Finance
  • Summer 2011 - 0018 Statistik
  • Summer 2011 - 2327 Finance V: Quantitative Optimization Methods in Finance
  • Winter 2010 - 0998 Statistik
  • Winter 2010 - 2154 MSc Quantitative Finance - Industry Lab: Hedge Funds
  • Winter 2010 - 2486 Finance V: Quantitative Methods in Finance
  • Summer 2010 - 0024 Statistik
  • Summer 2010 - 0052 Statistik

WU Executive Academy

  • February 2023 - The Future of Data Analytics (PMBA Data Science 6)
  • January 2023 - Data Analytics (LL.M. Digital Tax Law)
  • December 2022 - Advanced Data Analytics (PMBA Data Science 6)
  • October 2022 - Introduction to Data Analytics (PMBA Data Science 6)
  • February 2022 - The Future of Data Analytics (PMBA Data Science 5)
  • January 2022 - Data Analytics (LL.M. Digital Tax Law)
  • December 2021 - Advanced Data Analytics (PMBA Data Science 5)
  • October 2021 - Introduction to Data Analytics (PMBA Data Science 5)
  • July 2021 - Hot Topics in Finance (PMBA Finance)
  • February 2021 - The Future of Data Analytics (PMBA Data Science 4)
  • December 2020 - Data Analytics (LL.M. Digital Tax Law)
  • November 2020 - Advanced Data Analytics (PMBA Data Science 4)
  • October 2020 - Introduction to Data Analytics (PMBA Data Science 4)
  • February 2020 - The Future of Data Analytics (PMBA Data Science 3)
  • November 2019 - Advanced Data Analytics (PMBA Data Science 3)
  • October 2019 - Introduction to Data Analytics (PMBA Data Science 3)
  • January 2019 - The Future of Data Analytics (Data Science 2)
  • November 2018 - Advanced Data Analytics (Data Science 2)
  • September 2018 - Introduction to Data Analytics (Data Science 2)
  • March 2018 - The Future of Data Analytics (Data Science 1)
  • December 2017 - Advanced Data Analytics (Data Science 1)
  • October 2017 - Introduction to Data Analytics (Data Science 1)
  • September 2017 - Data-based Management (Executive MBA)
  • February 2015 - Data-based Management (Executive MBA)
  • September 2014 - Data-based Management (Executive MBA)
  • January 2013 - Data-based Management (Executive MBA)
  • November 2011 - Data-based Management (Executive MBA)

FH Campus Vienna

  • Summer 2023 - Statistik
  • Winter 2022 - Statistische Datenanalyse und Business Analytics
  • Summer 2022 - Ringvorlesung Digitalisierung
  • Summer 2021 - Ringvorlesung Digitalisierung
  • Summer 2020 - Ringvorlesung Digitalisierung
  • Winter 2020 - Angewandte Forschung in Public Management
  • Winter 2020 - Statistik
  • Summer 2019 - Ringvorlesung Digitalisierung
  • Winter 2019 - Angewandte Forschung in Public Management
  • Winter 2019 - Statistik
  • Winter 2018 - Angewandte Forschung in Public Management
  • Winter 2018 - Statistik
  • Winter 2017 - Angewandte Forschung in Public Management
  • Winter 2017 - Statistik
  • Winter 2016 - Statistik
  • Summer 2016 - Policy und Politikfeldanalyse anhand ausgewählter Beispiele (Bachelorarbeit 2)
  • Winter 2015 - Forschungsmethoden in der Anwendung (Bachelorarbeit 1)
  • Summer 2015 - Policy und Politikfeldanalyse anhand ausgewählter Beispiele (Bachelorarbeit 2)
  • Winter 2014 - Forschungsmethoden in der Anwendung (Bachelorarbeit 1)
  • Summer 2014 - Policy und Politikfeldanalyse anhand ausgewählter Beispiele (Bachelorarbeit 2)
  • Winter 2013 - Forschungsmethoden in der Anwendung (Bachelorarbeit 1)

Webster Vienna Private University

  • Fall 2021 - STAT 1100 Descriptive Statistics
  • Fall 2021 - BUSN 2750 Introduction to Statistics
  • Fall 2020 - BUSN 2750 Introduction to Statistics
  • Spring 2020 - BUSN 2750 Introduction to Statistics
  • Fall 2019 - COSC 2110 Computer Languages: Introduction to R for Data Science
  • Spring 2019 - BUSN 2750 Introduction to Statistics

University of Bergamo

  • Winter 2017 - Quantitative Methods in Finance
  • Winter 2016 - Quantitative Methods in Finance
  • Winter 2015 - Quantitative Methods in Finance
  • Summer 2015 - Quantitative Methods in Finance
  • Winter 2013 - Quantitative Methods in Finance
  • Winter 2012 - Quantitative Methods in Finance
  • Winter 2011 - Quantitative Methods in Finance
  • Summer 2008 - Scenario modeling for stochastic optimization problems

FH Burgenland

  • Winter 2016 - Datawarehouse & Data Mining

FHWien

  • Summer 2016 - Quantitative Methoden der Betriebswirtschaftslehre mit Excel

University of Vienna

  • Winter 2009 - 040713 UK Angewandte Statistik
  • Winter 2008 - 040558 UK Computational Statistics
  • Summer 2008 - 040107 FK Aktiv- und Passivmanagement
  • Winter 2007 - 040558 UK Computational Statistics
  • Winter 2007 - 040196 VO Datenbanksysteme
  • Winter 2007 - 040197 UK Datawarehousing
  • Summer 2007 - 040107 FK Aktiv- und Passivmanagement
  • Summer 2007 - 040311 UK Computational Statistics
  • Winter 2006 - 040193 VO Datenbanksysteme
  • Winter 2006 - 040194 UK Datawarehousing
  • Summer 2006 - 050046/1 PR KFK DS/AP Anwendungsprobleme I (Finance)
  • Summer 2006 - 040107/1 FK KFK Aktiv- u. Passivmanagement
  • Summer 2006 - 050022/3 UE SW/SDA Statistik und Datenanalyse
  • Summer 2006 - 050022/4 UE SW/SDA Statistik und Datenanalyse
  • Winter 2005 - 050085/1 UE SW/MLS Mathematik, Logik und Systemtheorie
  • Winter 2005 - 050085/2 UE SW/MLS Mathematik, Logik und Systemtheorie
  • Summer 2005 - 401186/1 PR KFK DS/AP Anwendungsprobleme I (Finance)
  • Summer 2005 - 407007/4 UE SW/SDA Statistik und Datenanalyse
  • Summer 2005 - 407007/5 UE SW/SDA Statistik und Datenanalyse
  • Winter 2004 - 407466/1 UE SW/MLS Mathematik, Logik u. Systemtheorie
  • Winter 2004 - 407466/2 UE SW/MLS Mathematik, Logik u. Systemtheorie
  • Winter 2004 - 401304/3 FK WMS Wirtschaftsstatistik 1
  • Summer 2004 - 401186/1 PR KFK DS/AP Anwendungsprobleme I (Finance)
  • Summer 2004 - 407007/4 UE SW/SDA Statistik und Datenanalyse
  • Summer 2004 - 407007/5 UE SW/SDA Statistik und Datenanalyse
  • Winter 2003 - 407466/2 UE SW/MLS Mathematik, Logik u. Systemtheorie
  • Winter 2003 - 401304/3 FK WMS Wirtschaftsstatistik 1
  • Summer 2003 - 401186/1 PR KFK DS/AP Anwendungsprobleme I (Finance)
  • Summer 2003 - 407007/4 UE SW/SDA Statistik und Datenanalyse
  • Summer 2003 - 407007/5 UE SW/SDA Statistik und Datenanalyse
  • Winter 2002 - 401263/1 PR Praktikum aus Angewandter Statistik
  • Winter 2002 - 401304/3 FK WMS Wirtschaftsstatistik 1
  • Winter 2002 - 401304/4 FK WMS Wirtschaftsstatistik 1
  • Summer 2002 - 407007/2 UE Statistik und Datenanalyse (SDA)
  • Summer 2002 - 407007/3 UE Statistik und Datenanalyse (SDA)