Paul Zhang is a PhD candidate working to answer complex questions at the intersection of scientific computing, optimization, and geometry. Specifically, Paul studies quadrilateral (quad) and hexahedral (hex) meshing, an open area in geometry with bearing on simulation for computational fluid dynamics, fabrication, and other tasks. He has also investigated other areas of geometry, developing a new algorithm for approximating the isoperimetric profile of a two-dimensional shape and exploring new methods for interpolation in the space of probability densities. As a MathWorks Fellow, Paul will continue to push the frontiers of hex-meshing, utilizing and creating MATLAB tools to study meshing and geometry more broadly. In one current project, he is developing a robust, high-quality, automatic hexahedral meshing algorithm through the use of frame fields. The range and innovative nature of Paul’s work, as well as his many contributions to fellow researchers through shared resources like his Bulk Trilinear Inverse tool, make him a force multiplier in his field with the potential to greatly advance the fields of geometry and scientific computing.

Yang Zhong is a PhD candidate whose broad research interests in thermal sciences encompass atmospheric water harvesting, thermal management of 2-D electronics, and machine learning for boiling. With the support of a MathWorks Fellowship, Yang is currently working on the fundamental water adsorption and engineering design of atmospheric water harvesting devices. Specifically, he is advancing a concept to harvest water in the atmosphere based on the principle of adsorption. By using the temperature differential between night and day, Yang is designing a device to produce drinking water directly from the air via solar energy. MATLAB is a core component of this work for data collection, modeling, and analysis. This project will drive future work Yang hopes to accomplish in this sphere of research, including exploring materials design, characterization, and new water harvesting architectures, all of which will draw extensively on MATLAB tools. His work is leading the way to useful new technologies to address water scarcity, as well as a broader, fundamental understandings of how large-scale water harvesting systems could affect the global water economy and ecosystem.

Xingcheng (Cindy) Zhou is a PhD candidate whose research lies at the intersection of biology, electrochemistry, and small-molecule chemistry. Specifically, Cindy is working to develop accurate, low-cost diagnostic tools for infectious disease in low-resource settings. Her current work, supported by a MathWorks Fellowship, includes the creation of an electrochemical sensor for antibiotic screening, as an electrochemical Covid-19 diagnostic. The broader aim of her research is to develop inexpensive and accessible electrochemical sensors to accurately diagnose infectious diseases, both bacterial and viral, by conjugating biomolecules on the surface of electrodes to capture disease biomarkers and convert the capture to an electrical signal. Cindy has made extensive and innovative use of MATLAB to analyze the signals and model the sensors, advancing her own work and that of her colleagues. As she builds and refines new biosensor models, Cindy will share these tools with the MathWorks and electrochemistry community. Her research has significant potential to advance the use of biosensors in human health and to improve quality of life for vulnerable populations through accurate, economical, and facile detection of infectious diseases.