Thesis Supervision

Thesis Supervision #

Ph.D. Students #

Tinbergen Institute Research Master Students #

  • Ming Cheng. A Guided Neural Network Approach to Volatility Forecasting. August 2023.

  • Hans Ligtenberg, Explaining the unconditional value premium using neural networks, August 2021. Python codes here

Master Students #

University of Amsterdam #

  • Julian Kerssens, Innovating market sentiment analysis with natural language processing, August 2024 (Nominated for Jan Brouwer Thesis Prize and UvA Theis Prize)

  • Zixiao Quan, Causal Impact of the Chinese Plastic Import Ban On Global Warming Trends, August 2024. (Currently PhD candidate at HKU)

  • Jiangcheng Li, Modeling Volatility with Machine Learning for Quantile Forecasting of Natural Gas Consumption: A Comparative Study with Econometric Model, August 2024

  • Thomas van der Zijden, Optimizing Cryptocurrency Portfolio Tail Risk: An Extreme Value Theory Approach, August 2024

  • Ruowen Liu, A Time-Dynamic Movie Recommendation System for Capturing User Preference Drift, August 2023

  • Gijs W.M. de Bruin, Synthetically Extending a Dataset to Improve Machine Learning Prediction, August 2023 (Nominated for Amsterdam AI Thesis Award)

  • Jiachen Zhong, Comparing Machine Learning Methods with Traditional Methods in the Context of Demand Sensing in a European Postal Industry, August 2023

  • Viktoria Akpan, Decoding Brainwaves for Thought-Controlled Movement Using Deep Learning, August 2023

  • Marcin Galas, Comparison of national and global data for VaR estimation of real estate prices, August 2023

  • Nguyen Hoang Minh Trang, The Impact of Feature Selection on the Deep Recommender Systems. July 2023

  • Shihan Yu, Analysing the Ranking in Search Engine Keyword Bidding with Different Models and Strategies, August 2022

  • Jop van Hest, Detecting Ponzi-Scheme Fraud in Ethereum Smart Contracts, August 2022

  • Wiebe van der Spek, How to Preserve Patient Privacy in Machine Learning Model Training?

  • Romy Ho, Scaling Federated Learning in Practice: How Heterogeneous Data Impacts Model Accuracy, July 2022

  • Liselotte van Dam, The effect of a sales promotion on revenue: An application of the causal forest in grocery retailing, Jan 2022

  • Alex Boosten, Should you invest in Bitcoin? A performance analysis of Bitcoin and reinforcement learning using bootstrap, Jan 2022

  • Coen van der Meijs, Bitcoin intra-day return prediction and trading using LSTM, August 2021.

  • Jan Willem Nijenhuis, Application of generalizability theory to construct a reliability framework for machine learning, August 2021. Python codes here

  • Eefje Roelfsema, How does industry-leading sentiment affect the probability of default of SMEs?, August 2021

  • Wisse Bemelman, Evaluating the use of artificial neural networks for financial asset price forecasting, July 2021

  • Dylan Houtman,The identification of personal data in semi-structured text, August 2020

  • Sophie Abrahamse, Bridging the gap between interpretability and predictability in customer churn modelling, August 2020

  • Alessandro Peron, A deep learning approach for non-parametric instrumental estimation: an empirical study, August 2020

  • Melle Gelok, Detecting fake job advertisements, August 2020

  • Stijn Mouris, Detecting social security fraud with an explanatory algorithm, December 2019

  • Maarten de Haas, Predicting the direction of stock prices, December 2019

Monash University #

  • Yuanjun Lu, Economic Forecasting with Big Data: A Simulation Study, June 2019
  • Balaji Dasari, Stock Predictability using Sparse Learning Approach, June 2019
  • Thadeu Freitas Filho, Measuring Systemic Risk: Least-squares versus Quantile Regression, October 2018
  • Sombut Jaidee, Optimal Investment using High Dimensional Statistics: Theory and Simulation, October 2017 (Best Thesis Award)
  • Aishwarya Pillai, Optimal Investment using High Dimensional Statistics: an Empirical Study, October 2017
  • Yue Wang, Measuring Systemic Risk with Extreme Value Theory, June 2017