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MSCA Individual Research Projects

In the DIGITAL program, each doctoral candidate is dedicated to a specific research project with a common overarching goal: to advance the digitalization of finance. 

  • Towards a European Financial Data Space:
    Collaborative learning across data silos Detecting anomalies and dependence structures in high dimensional, high frequency financial data Predicting financial trends using text mining and NLP Deep Generation of Financial Time Series
  • Artificial Intelligence for Financial Markets
    Strengthening European financial service providers through applicable reinforcement learning Developing industry-ready automated trading systems to conduct EcoFin analysis using deep learning algorithms Challenges and opportunities for the uptaking of technological development by industry
  • Towards explainable and fair AI-generated decisions
    Audience-dependent explanations Investigating the utility of classical XAI methods in financial time series Fair Algorithmic Design and Portfolio Optimization under Sustainability Concerns
  • Driving digital innovations with Blockchain applications
    Industry standard for blockchain Fraud detection in financial networks Risk index for cryptos
  • Sustainability of Digital Finance
    Modelling green credit scores for a network of retail and business clients A recommender system to re-orient investments towards more sustainable technologies and businesses Experimenting with Green AI to reduce processing time and contributes to creating a low-carbon economy Applications of Agent-based Models (ABM) to analyse finance growth in a sustainable manner over a long-term period

The DIGITAL program is designed to drive forward the digitalizations of finance by assigning each doctoral candidate a specific project that addresses different aspects of the field. These projects have specific objectives and expected outcomes, covering a wide range of topics such as: collaborative learning across data silos, detecting anomalies and dependencies in high dimensional financial data, language models, reinforcement and deep learning, eXplaianble AI, blockchain technology standards, and many more. Doctoral Candidates (DCs) are expected to produce at least three papers during their PhD program, with a minimum of two involving collaboration within their network. They must also participate in three conferences and present at two academic and one industry seminar each year. These requirements aim to promote collaboration, spread knowledge, and support the DCs' academic and professional growth.

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