Modular construction is increasingly seen as an efficient construction method in terms of time, cost, and energy. The full realization of these advantages partly relies on the efficiency of the production process inside the modular factories, which currently rely on tedious manual monitoring methods or expensive automated techniques. As a...
Metabolomics has recently gained momentum in biomolecule research and complements the genomics and proteomics research space. Metabolomics strives to detect, identify, and quantify all metabolites present in biological samples. In particular, biomolecular analysis using ultra-performance liquid chromatography combined with mass spectrometry (UPLC-MS) has become increasingly important for metabolomic analyses. Similarly,...
This dissertation consists of three essays that provide comprehensive insights into the complex dynamics shaping entrepreneurial and organizational outcomes. In the first essay I incorporate the Biophilia Hypothesis and the Challenge Hindrance Stressor framework to study entrepreneurial creativity. The findings emphasize the importance of more frequent nature visits for entrepreneurs...
Secure Computation is a powerful tool that enables a set of parties to jointly compute any function over their private inputs, without a trusted third party. Private Set Intersection is a specific case of two-party Secure Computation, where Alice (with private set X) and Bob (with private set Y) specifically...
The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
Machine learning applied to computer architecture has rapidly transitioned from a theoretical novelty to being a driving force behind design, control, and simulation in practically all components. These machine-learning-based methodologies are further notable for their scalability to increasingly complex design challenges, which has allowed these methodologies to surpass the prior...
Deep learning is now being utilized widely in applications where sensitive data is being used for model training, for example, in health care. In this scenario, any data leakage will cause privacy concerns to whose data records are used to train the model. An attacker can actively cause privacy leakage...
Consistent with its charge under Oregon House Bill 3543, the Oregon Climate Change Research Institute (OCCRI) conducts a biennial assessment of the state of climate change science, including biological, physical, and social science, as it relates to Oregon and the likely effects of climate change on Oregon. This sixth Oregon...
The focus of this thesis is to design, characterize, and apply novel computational methods and molecular systems to interrogate heterogeneous human gut microbiome-related phenomena. In Chapter 2, I design, implement, and characterize a method for embedding co-occurrence patterns derived from massive 16s amplicon datasets. I use this method to 1....
Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...