MSCA Training Week on Blockchains in Digital Finance
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MSCA Training Week on Blockchains in Digital Finance
This course focuses on applying statistical modeling, machine learning (ML), and artificial intelligence (AI) methods—particularly large language models (LLMs)—to blockchain-based financial systems. Students will explore the use of these technologies in: Predictive modeling of crypto assets, Anomaly detection in decentralized finance (DeFi), Transaction graph analytics, Smart contract evaluation, Blockchain-based risk assessment. Emphasizing data-driven research, the course makes extensive use of real-world blockchain datasets from sources such as Quantinar, Dune Analytics, Etherscan, and Flipside Crypto. Through lectures and applied labs, students will formulate, implement, and evaluate models that capture the complexity of digital finance systems built on distributed ledger technologies. The course positions students at the forefront of quantitative blockchain analytics, with practical exposure to ML frameworks (e.g., PyTorch, scikit-learn), financial time series analysis, and the responsible use of LLMs for interpretability, auditing, and compliance in DeFi.
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- 0 Rating
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- 2 Students Enrolled
Requirements
- To successfully participate in this course, students are expected to have foundational knowledge in the following areas: Statistics & Econometrics Familiarity with linear regression, maximum likelihood estimation, GARCH models, and hypothesis testing. Machine Learning Understanding of core supervised and unsupervised algorithms (e.g., decision trees, clustering, n eural networks), including basic concepts of deep learning and transformers. Mathematics Solid grasp of linear algebra (eigenvalues, matrix operations), probability theory (distributions, expectations), and convex optimization. Programming Proficiency in Python, with experience using libraries such as NumPy, pandas, scikit-learn, PyTorch, and Hugging Face Transformers. Finance Basic understanding of financial markets, asset pricing, and blockchain-specific financial mechanisms (e.g., tokenomics, AMMs, DeFi protocols). Blockchain Fundamentals Familiarity with blockchain architecture, smart contracts (e.g., Solidity), Ethereum, and key tools such as Web3.py and Etherscan.
General Overview
Description
Monday (30/03)
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09:30 – 10:00 → Registration
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10:00 – 10:15 → Welcome and Introduction
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10:15 – 11:15 → CBDC Stress Tests in a Dual Currency Setting – (Cătălin Dumitrescu)
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11:30 – 12:30 → Central Bank Digital Currencies - an academic research on the potential design for digital LEU – (Raluca Micu)
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13:30 – 14:30 → Crypto and Stablecoins Stress Test – (Cătălin Dumitrescu)
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14:50 – 16:30 → Project: description and coding
Tuesday (31/03)
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09:50 – 10:00 → Welcome remarks – (Joerg Osterrieder)
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10:00 – 11:00 → Adapting SHAP to trustworthy window changes – (Raul Cristian Bag)
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11:20 – 12:20 → Early warning systems for cryptocurrency markets: Predicting ’zombie’ assets using machine learning – (Piotr Wójcik)
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13:30 – 14:30 → How Much Power was Saved in ETH Merge? – (Wolfgang Karl Härdle)
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14:50 – 16:30 → Discussion panel: prospects and barriers of Blockchain in digital finance
Wednesday (01/04)
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10:00 – 11:00 → A Graph-Theoretic Framework for Predicting Implied Volatility Surfaces in Crypto Option Markets – (Radu Lupu)
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11:20 – 12:20 → On-chain data sources: a practical guide – (Owen Chaffard)
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13:30 – 14:30 → Blockchain-as-a-Service (BaaS) application in Romania – (Adrian Costea)
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14:40 – 15:40 → Students Seminar Session
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16:00 – 17:00 → Students Seminar Session
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17:00 – 18:00 → Project: updates
Thursday (02/04)
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10:00 – 11:00 → Central Banking and AI – (Antoaneta Amza)
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11:20 – 12:20 → The Intelligent Skewness Factor – (Dan Gabriel Anghel)
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13:30 – 14:30 → Crypto-Asset Narratives in Romanian Financial News: A Topic and Sentiment Analysis – (Claudia Voicilă)
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14:50 – 15:50 → Day-ahead Forecasting for Redispatch Measures using Machine Learning – (Vlad Bolovăneanu)
Friday (03/04) – HE framework and research project management
Speaker: Oros Alexandra and Claudia Petrescu
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10:00 – 10:20 → Welcome & Introductions
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10:20 – 10:50 → Defining Scope in Research
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11:00 – 11:30 → Planning Under Uncertainty
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11:30 – 12:00 → Governance & Stakeholder Management
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12:20 – 12:50 → Managing Research Execution
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14:00 – 14:30 → Risk & Failure Management
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14:30 – 15:00 → Deliverables in Research Projects
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15:20 – 16:20 → Lessons Learned & Research Maturity
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16:20 – 16:30 → Horizon Europe Framework
Final Presentations (30/06/2026)
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13:00 - 16:00 → Final Group Presentations (Online)
Speakers
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Adrian Costea
Bucharest University of Economic Studies -
Antoaneta Amza
National Bank of Romania -
Cătălin Dumitrescu
Stratum Finance -
Claudia Petrescu
The Research Institute for Quality of Life, Romanian Academy -
Claudia Voicilă
National Bank of Romania -
Dan Gabriel Anghel
Bucharest University of Economic Studies -
Daniel Traian Pele
IDA Institute Digital Assets, Bucharest University of Economic Studies; Institute for Economic Forecasting, Romanian Academy, Romania -
Joerg Osterrieder
Coordinator MSCA Digital Finance -
Oros Alexandra
Omnisource Technologies; PMI Romania -
Owen Chaffard
Cardo AI; University of Kaiserslautern-Landau -
Piotr Wójcik
University of Warsaw, Poland -
Radu Lupu
IDA Institute Digital Assets, Bucharest University of Economic Studies; Institute for Economic Forecasting, Romanian Academy, Romania -
Raluca Micu
TOKEN Financial Technologies Romania -
Raul Cristian Bag
Institute of Digital Assets, Bucharest University of Economic Studies -
Vlad Bolovăneanu
Bucharest University of Economic Studies -
Wolfgang Karl Härdle
IDA Institute Digital Assets, Bucharest University of Economic Studies, Romania
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Meet the instructors !
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Daniel Traian Pele is a Prof. dr. Department of Statistics and Econometrics Faculty of Cybernetics, Statistics and Economic Informatics, The Bucharest University of Economic Studies. https://scholar.google.com/citations?user=tN32HYcAAAAJ&hl=en