Research Projects

Selected Data Science and Academic Research Projects

Academic research:

• FutureTech: an interdisciplinary research at MIT that studies the foundations of progress in computing: what are the most important trends, how do they underpin economic prosperity, and how can we harness them to sustain and promote productivity growth.

• Unpacking the black box of ICO white papers. Topic modeling application to map Initial Coin Offerings’ (ICOs’) white paper thematic content to analyze its information value to investors. Together with the co-authors we find that the most value-relevant topics concern the technical features of the ICO. However, we find that white paper’s informativeness substantially diminishes after the token is listed. Moreover, we show that credibility-enhancing mechanisms (i.e., regulations and ICO analysts) reinforce the information value of ICO white papers. Overall, our results suggest that the topics discussed in white papers and the attention devoted to each topic are useful ICO performance indicators.

  Paper accepted in Journal of Corporate Finance (ABS 4) led by James Thewissen, together with Prabal Shrestha and Wouter Torsin.

• Discussing novel approaches to computerized text analysis in strategic entrepreneurship research. Owing to the substantial amount of text documents generated by organizations and their various members in different roles, computer assisted text-as-data methods are becoming increasingly popular among scholars of strategic entrepreneurship. Together with my co-author, we review several of the most popular and emerging computer assisted textual analysis approaches and data sources to help shine light upon new potential research frontiers.

  Book chapter accepted for publication in Handbook of Strategic Entrepreneurship, co-authored with Bill Wales.

Industry research:

• Google cloud based R&D of machine learning solutions for financial crime risk assessment in one of the major global banks. After successful launch of product for money laundering, I was building a money mules detection solution.

• Risk management in business schools assessment, mapping the practices in the accredited institutions. Research insights were particularly relevant for the later COVID crisis.

  Part of the project was academic and resulted in publication in Journal of Management Development, led by Ulrich Hommel, together with Wenwei Li.