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Master Theses

The 50 most recent M.Sc. theses supervised by members of the division

[1]
M. Olsson, "Role Mining With Hierarchical Clustering and Binary Similarity Measures," , 2023.
[2]
K. Golshani and E. Ekberg, "Detection and Classification of Sparse Traffic Noise Events," , 2023.
[3]
N. Mannberg, "Hierarchical Control of Simulated Aircraft," , 2023.
[4]
E. Engel, "Balancing Performance and Usage Cost: A Comparative Study of Language Models for Scientific Text Classification," , 2023.
[5]
M. Berg Wahlström and A. Hagelberg, "Analysis and Use of Telemetry Data for Car Insurance Premiums," , 2023.
[6]
E. Jonsäll and E. Mattsson, "Data Driven Modeling for Aerodynamic Coefficients," , 2023.
[7]
E. Granström, "Detecting Risky Riding on Micromobility Vehicles Using Sensor Data and Machine Learning," , 2023.
[8]
S. Syed and J. Stenberg, "Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction," , 2023.
[9]
H. Backe and D. Rydberg, "Statistical Modelling of Price Difference Durations Between Limit Order Books: Applications in Smart Order Routing," , 2023.
[10]
P. Sinander and A. Ahmed, "Clustering of Unevenly Spaced Mixed Data Time Series," , 2023.
[11]
R. Siridol-Kjellberg, "Hidden Markov Models for Intrusion Detection Under Background Activity," , 2023.
[12]
R. Molén, "Branching Out with Mixtures: Phylogenetic Inference That’s Not Afraid of a Little Uncertainty," , 2023.
[13]
P. Nydahl, "Robust Portfolio Optimization with Correlation Penalties," , 2023.
[14]
M. Axén, "Imitation Learning on Branching Strategies for Branch and Bound Problems," , 2023.
[15]
A. Dernsjö and E. Blom, "A Gradient Boosting Tree Approach for Behavioural Credit Scoring," , 2023.
[16]
O. Abdullah Mohamad and A. Westin, "Pricing and Modeling Heavy Tailed Reinsurance Treaties - A Pricing Application to Risk XL Contracts," , 2023.
[17]
J. Eriksson and J. Holmberg, "Portfolio Risk Modelling in Venture Debt," , 2023.
[18]
L. Fageräng and H. Thoursie, "Modelling Proxy Credit Cruves Using Recurrent Neural Networks," , 2023.
[19]
H. Andersson and J. Sjöberg, "Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning," , 2023.
[20]
M. Johnson and H. Forslund, "AI Based Methods for Matrix Multiplication in High Resolution Simulations of Radio Access Networks," , 2023.
[21]
A. Björnfot and S. Fjelkestam, "Predicting Short-term Absences of a Railway Crew using Historical Data," , 2023.
[22]
H. Fagerlund, "A Comparative Study of Machine Learning Algorithms for Angular Position Estimation in Assembly Tools," , 2023.
[23]
S. Nieto, "Identifying Optimal Throw-in Strategy in Football Using Logistic Regression," , 2023.
[24]
E. Larson, "Volatility Forecasting using GARCH Processes with Exogenous Variables," , 2022.
[25]
P. Hedvall, "Out-of-distribution Recognition and Classification of Time-Series Pulsed Radar Signals," , 2022.
[26]
J. Stymne, "Self-Play Reinforcement Learning for Finding Intrusion Prevention Strategies," , 2022.
[27]
D. Thinsz, "Properties of Discrete Laplacians With Application on Brain Networks," , 2022.
[28]
B. Lu, "Prediction of Short-term Default Probability of Credit Card Invoices Using Behavioural Data," , 2022.
[29]
B. Wehlin, "Approximating Quasistationary Distributions Using Deep Learning," , 2022.
[30]
O. Nordström, "Unstructured pruning of pre-trained language models tuned for sentiment classification.," , 2022.
[31]
J. Risberg, "Basil-GAN," , 2022.
[32]
Y. Shao, "Data-driven Discovery of Real-time Road Compaction Parameters," , 2022.
[33]
H. Essinger and A. Kivelä, "Object Based Image Retrieval Using Feature Maps of a YOLOv5 Network," , 2022.
[34]
A. Skärbo Jonsson, "Efficient Music Thumbnailing for Genre Classification," , 2022.
[35]
F. Fenoaltea, "Reliability Based Classification of Transitions in Complex Semi-Markov Models," , 2022.
[36]
M. Kazi and N. Stanojlovic, "Deep Learning Approach for Time- to-Event Modeling of Credit Risk," , 2022.
[37]
J. Hlöðver Friðriksson and E. Ågren, "Neural Ordinary Differential Equations for Anomaly Detection," , 2021.
[38]
M. Ulvklo, "Hybrid Ensemble Methods: Interpretible Machine Learning for High Risk Aeras," , 2021.
[39]
S. Aboud, "Predicting Customer Conversion using Supervised Machine Learning," , 2021.
[40]
F. Bragone, "Physics-Informed Machine Learning in Power Transformer Dynamic Thermal Modelling," , 2021.
[41]
L. Börthas and J. Krange Sjölander, "Machine Learning Based Prediction and Classification for Uplift Modeling," , 2020.
[42]
A. Prastorfer, "Simulation-Based Portfolio Optimization with Coherent Distortion Risk Measures," , 2020.
[43]
W. Löfgren, "Distributional Dynamics of Fama-French Factors in European Markets," , 2020.
[44]
T. Charitidis, "Sequence Prediction for Identifying User Equipment Patterns in Mobile Networks," , 2020.
[45]
N. Nayeri, "Option strategies using hybrid Support Vector Regression - ARIMA," , 2020.
[46]
S. Kornfeld, "Predicting Default Probability in Credit Risk using Machine Learning Algorithms," , 2020.
[47]
A. Andersson and S. Mirkhani, "Portfolio Performance Optimization Using Multivariate Time Series Volatilities Processed With Deep Layering LSTM Neurons and Markowitz," , 2020.
[48]
E. Lagerström and M. Magne Schrab, "An Empirical Study of Modern Portfolio Optimization," , 2020.
[49]
C. García Ling, "Graphical Glitch Detection in Video Games Using CNNs," , 2020.
[50]
A. Eskandari, "VAE-clustering of neural signals and their association to cytokines," , 2020.
Full list in the KTH publications portal