Derivative-free optimization (DFO) has received growing attention due to important problems arising in practice. Various research communities, ranging from machine learning to engineering design, have adopted distinct DFO methods. In this thesis, we present extensive studies as a meaningful step towards a comprehensive understanding of DFO methods. We study the...
In recent years, the understanding and identification of quantum materials supporting non-trivial band topology has progressed rapidly. This progress has been motivated in part by the potential application of topological quantum materials in quantum computers, sensors, and other next-generation devices. Despite this progress, the computation of bulk topological invariants in...
This dissertation focuses on quantifying protein folding stability determinants and presenting initial experiments that can guide the development of a novel assay that identifies cell-penetrating miniproteins. First, despite over a century of scholarship on protein folding stability, applying this knowledge to design proteins computationally remains limited. Usually, protein designers generate...
This dissertation investigates how scope relations are constructed and evaluated during real-time human sentence processing. Theoretical approaches to processing scope relations exist in a multi-dimensional space where trade-offs are made around how quickly scope relations can be computed, how many mistakes are made in computing scope relations, and how many...
Necessity is the mother of innovation. In the wake of the pandemic, with no flow of samples and limited fabrication techniques available, necessity demanded a new material platform and adaptable methods to make complex oxide samples worth measuring. The material platform was KTaO3 , the younger successor to the mainstay...
This dissertation aims to develop innovative analytical methods that integrate engineering, marketing, and social science disciplines to incorporate heterogeneous consumer preferences into product design using network-based customer preference modeling. Both companies and designers frequently face difficulties in understanding and addressing customer preferences, which can result in product failure and loss...
Machine learning and deep learning have been proven successful across various scientific fields, such as computer vision, natural language processing, and recommendation systems. As models become more complex, with more parameters and intricate architectures, they can achieve higher prediction accuracy when trained on larger datasets. However, despite the great prediction...
Controlled delivery of foreign cargo into cells is a critical step in many biological studies and in cell engineering and analysis workflows. Recent advances in micro and nanotechnology, specifically in microfluidics and microfabrication have added significantly to the precision, accuracy, resolution and throughput of cell manipulation and analysis pipelines. These...
Metalloenzymes catalyze remarkable reactions in Nature using transition metal ions. Common earth-abundant metals like copper, iron, zinc, and magnesium catalyze reactions that are the basis of life. These metal sites lend their chemistries to facilitate these reactions, making studying the structure and properties important in understanding the enzymes' abilities and...
For many years silicon tethers have been used to increase yields and control the stereochemical and regiochemical outcomes of coupling reactions. Silicon tethers may be incorporated into a wide range of reaction types including alkene metathesis, cycloadditions, and glycosylations. This thesis focuses on the development of the use of silicon...