Machine Learning in Empirical Asset Pricing
This thesis consists of 5 chapters. Chapter 1 is the introduction of the thesis. Chapter 2, Chapter 3 and Chapter 4 are the main chapters of this thesis, which cover the U.S. bond market, international stock market and U.S. stock market respectively. Chapter 5…
Variable-dependent predictability of coastal atmospheric parameters in the marine wave boundary layer using Physics-informed machine learning at sub-hourly resolution: a thesis in Data Science
Advances in environmental sensing technologies have enabled the collection of high-frequency atmospheric observations, creating new opportunities for applying machine learning to short term environmental prediction. Despite considerable progress in data-driven…
Computational biology in plant tissue culture: Systematic evaluation of machine learning approaches for callus induction in Solanum L.: A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University
Optimization of plant tissue culture systems remains a major biotechnological challenge; yet successful callus induction, the formation of unorganized, proliferating cell masses from differentiated tissues, enables transformative applications in agriculture, m…
Predicting microbiologically influenced corrosion severity from electrochemical impedance spectroscopy using interpretable machine learning: a thesis in Data Science
Microbiologically influenced corrosion (MIC) accounts for an estimated 20–30% of global corrosion losses, yet reliable quantitative prediction of MIC severity remains unsolved. Electrochemical measurements combined with interpretable machine learning provide a…
Machine-learning emulator for multispecies biological reference points in the Eastern Bering Sea Groundfish Complex: a thesis in Data Science
Fisheries management increasingly relies on biological reference points, target fishing mortality and biomass levels, to set sustainable catch limits. For single-species stocks these reference points can often be computed from a fitted assessment model, but wh…
Predicting refractive index structure parameter in the marine wave boundary layer using machine learning models: a thesis in Data Science
The refractive index structure parameter, ??ₙ², quantifies optical turbulence and strongly influences the performance of electromagnetic and free-space optical systems operating within the marine wave boundary layer. Predicting ??ₙ² remains challenging due to…
Predictive Scheduling of Incoming Goods Using Machine Learning and Deep Learning Methods
Die vorliegende Arbeit untersucht den Einsatz von Machine-Learning- und Deep-Learning-Verfahren zur prädiktiven Terminierung von Wareneingängen. Ausgangspunkt bilden betriebliche Herausforderungen, welche durch Lieferabweichungen entstehen und eine zuverlässig…
Image analysis and machine learning in patients with brain tumors
Diffuse lower-grade gliomas (dLGG) are slowly growing primary brain tumors. Patients with dLGG represent a heterogeneous group with various symptoms, diverse progression of the disease as well as survival length. Collecting multidimensional patient data gives…
Machine learning for smart building heating optimization
This master's thesis deals with the optimization of building heating control using machine learning methods. Traditional control systems often fail to efficiently respond to the thermal inertia of buildings and variable external influences. Model Predictive Co…
Efficiency Advances in Moment Tensor Potentials for Machine-Learning Atomistic Modelling
The study of nuclear materials is strongly complemented by computational materials science (CMS), which provides an alternative means of investigating radiation-induced phenomena, defect evolution, and thermophysical properties—all of which can be hazardous, t…
Towards Trustworthy Machine Learning: Fairness Under Dynamics and Counterfactuals
Machine learning systems increasingly make decisions with long-term consequences for individuals and society. Designing trustworthy machine learning systems therefore requires going beyond static accuracy and one-shot fairness criteria. Decisions may alter fut…
