Doctoral Thesis
Recent Submissions
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Unbiased Identification of CD4+ T Cell Epitopes from the Intestinal Microbiota
(2024)The immune system is comprised of a dynamic and tightly regulated network of molecular and cellular interactions, orchestrating in harmony to protect the host from invading pathogens while maintaining tolerance to self-antigens and innocuous commensal bacteria. The symbiotic relationship between the host and intestinal microbiota plays a crucial role in shaping the host's innate and adaptive immune systems. Due to their involvement ...Doctoral Thesis -
Understanding Macroeconomic Dynamics: Insights from Output Gaps and Firm Surveys
(2024)Doctoral Thesis -
Stochastic Approximation on Riemannian Manifolds and the Space of Measures
(2024)Stochastic approximation methods are a class of iterative algorithms that play an essential role in applications involving noisy and incomplete observations. Rooted in the seminal works of Robbins and Monro (1951) and Kiefer and Wolfowitz (1952), this class of iterative processes drive a system towards a specified objective despite noise and bias. Stochastic approximation methods have become increasingly important in fields like statistics ...Doctoral Thesis -
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Hematopoietic Stem Cell Fate Decision: The Interplay of Signaling Dynamics, Cytokines, and Bone Marrow Niches
(2024)The dynamics of ERK and p38 MAPK signaling pathways are essential for deciphering how hematopoietic stem cells (HSCs) process environmental signals to determine their fate and function. Traditional methods often fail to capture the transient complexities of these signaling events in live cells. To address this, we utilized fluorescent biosensors and time-lapse imaging to track ERK and p38 MAPK signaling in live, individual HSCs derived ...Doctoral Thesis -
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From Micro Data to Macro Insights: Understanding Price Rigidity, Inflation, and Monetary Policy
(2024)This dissertation is a collection of four research articles on the price-setting behavior of firms and its implications for inflation and monetary policy. It begins with an introduction that summarizes each article and highlights its contribution to macroeconomics in general and monetary economics in particular. The subsequent sections present the articles in full. The first chapter, co-authored with Barbara Rudolf, provides new evidence ...Doctoral Thesis -
Mismatched motives: the economic consequences of distorted incentives in the public sector
(2024)This dissertation is a collection of four articles focused on the seeking of rents, which are rewards and prizes not earned or not consistent with competitive market returns. Each article explores a different aspect of the topic, focusing on the consequences, determinants or measurement of rent-seeking. The articles also differ in their unit of observation, with some examining country-level dynamics, and others adopting a more refined ...Doctoral Thesis -
Explore, Support, and Interact: Scaling Interpretable and Explainable Machine Learning up to Realities of Biomedical Data
(2024)Performant machine learning models are becoming increasingly complex and large. Due to their black-box design, they often have limited utility in exploratory data analysis and evoke little trust in non-expert users. Interpretable and explainable machine learning research emerges from application domains where, for technical or social reasons, interpreting or explaining the model's predictions or parameters is deemed necessary. In practice, ...Doctoral Thesis -
Gaining insights into bladder carcinomas and epithelial dynamics by 3d microscopy, image analysis and computational modeling
(2024)Epithelial tissues are far more than passive barriers that divide the outside from the inside in multicellular animals. They play essential roles in many bodily functions, adopt various tissue architectures, and can dynamically react to intrinsic signalling cues and extrinsic insults to maintain homeostasis. Losing this ability to maintain proper homeostasis can lead to different diseases, most notably cancer. Despite the importance of ...Doctoral Thesis -
Exploring Neuronal Function and Disease Mechanisms Through Advanced Electrophysiological Phenotyping with High-Density Microelectrode Arrays
(2024)Recent advances in high-density microelectrode array (HD-MEA) technology have significantly enhanced our ability to capture the complex electrical activity of neuronal networks at unprecedented temporal and spatial resolution. Concurrently, the advent of human induced pluripotent stem cells (iPSCs) has revolutionized disease modeling, enabling the generation of patient-specific neuronal cultures that recapitulate the phenotypic characteristics ...Doctoral Thesis -
Engineering chimeric antigen receptor signaling architectures for T cell immunotherapies
(2024)Chimeric Antigen Receptors (CARs) are rationally designed synthetic receptors that are engineered to redirect the specificity and effector function of T lymphocytes toward a target surface antigen. Particularly in the realm of cancer therapeutics, CAR T cells designed to target tumor-associated antigens have emerged as a groundbreaking approach within cellular immunotherapy, showcasing remarkable clinical efficacy in the treatment of B ...Doctoral Thesis -
Numerically Efficient Models for the Large Deformation Behavior of Metallic Structures and Materials
(2024)Doctoral Thesis -
Towards Monte Carlo based Full Spectrum Modeling of Airborne Gamma-Ray Spectrometry Systems
(2024)Doctoral Thesis -
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Tackling Bacillus spore resistance to isostatic high pressure germination and inactivation
(2024)Doctoral Thesis -
Design and Operation of Sustainable Net-Zero Energy Systems
(2024)Limiting human-induced climate change requires steep greenhouse gas (GHG) emission reductions to net-zero across all sectors. Carbon capture, removal, and storage technologies contribute to this target by reducing hard-to-abate emissions in industry and offsetting residual and historical emissions. A lack of real-world data limits the accuracy of environmental assessments of carbon capture, removal, and storage technologies. Here, we ...Doctoral Thesis -
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Unsteady data-driven and hybrid LES/RANS simulations of turbulent flows
(2024)Computational fluid dynamics (CFD) offers significant advantages over experimental methods in fluid dynamics studies. For example, it allows for detailed analysis and visualization of fluid flow phenomena that are often difficult or impossible to measure experimentally, providing insights into complex flow structures, turbulence, and interactions at a much finer scale. In numerous engineering disciplines, turbulent flow simulations ...Doctoral Thesis