Benjamin Lahner
Benjamin Lahner is a PhD candidate who is expanding the frontiers of computational neuroscience, with research that applies cutting-edge data analysis and machine-learning methods to advance studies of the human brain. As a MathWorks Fellow, Benjamin will continue his work to compare functional neuroscience imaging data with deep neural networks and devise original ways to utilize that data. In his most recent work, Benjamin combined high resolution spatial and temporal data to examine inform ...
Justin Chen
Justin Chen is a PhD candidate whose research explores the intersection of algorithms, machine learning, and data analysis. Specifically, Justin is making important contributions in the emerging area of learning-augmented algorithms. As a MathWorks Fellow, Justin will build upon several recent projects in this domain, including research on counting triangles in a data stream (a fundamental tool of network analytics); the classic optimization problem of online bipartite matching; and offline a ...
Maz Abulnaga
Maz Abulnaga is a PhD candidate whose work is changing the way researchers and physicians study the placenta with the goal of improving health outcomes for mothers and babies. Specifically, Maz develops algorithms for studying the placental shape in fetal magnetic resonance imaging, an imaging modality that is being used to track the health and function of the placenta, identify pathology, and support patient outcomes. Maz has made several contributions to the theoretical and algorithmic foun ...
Xingcheng (Cindy) Zhou
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 inexpen ...
Dousabel Tay
Dousabel Tay is a PhD candidate whose work integrates bioengineering and mathematical modeling to advance clinical diagnostics. Specifically, Dousabel is developing new approaches for rapid diagnostic testing, in a unique integration of protein engineering and microfluidics, to improve the tests’ performance, turnaround time, scalability, and affordability. With the support of a MathWorks Fellowship, Dousabel will expand and refine an end-to-end MATLAB model she has created, which predicts ...
Nadia Tahsini
Nadia Tahsini is a PhD candidate whose research explores the chemistry of atmospheric particulate matter (PM), a factor with significant influence on climate, air quality, and human health. Specifically, Nadia is investigating the role of peroxy radicals (RO2), which are key intermediates in the oxidation of volatile organic compounds (VOCs) emitted into the atmosphere. These insights into RO2 chemistry could serve to increase the accuracy of global atmospheric models. As a MathWorks Fellow, ...
Thomas J. Sheehan
Thomas J. Sheehan is a PhD candidate whose research is focused on an emerging new class of semiconductors known as halide perovskite nanomaterials. The remarkable optical properties of these materials—including near-unity quantum yields, highly tunable emission wavelength, and narrow emission line widths—make them highly promising components for next-generation solar cells, light-emitting devices, television displays, lasers, and quantum information systems. As a MathWorks Fellow, Thomas ...
Arjav Shah
Arjav Shah is a PhD candidate whose research focuses on the development of sterility testing methods for cell and gene therapies for human disease. Specifically, Arjav is working on new strategies to make biomanufacturing safer through the real-time detection of adventitious agents, such as viruses, at various points in the manufacturing process. With the support of a MathWorks Fellowship, Arjav is pursuing a highly promising novel application of nanopore sensors to fingerprint viruses. The o ...
Pedro Seber e Silva
Pedro Seber e Silva is a PhD candidate whose computational research uses the power of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL), to solve problems related to biomedicine and bioproduction. Pedro has made contributions to the research community with powerful new ML and DL models that predict the glycosylation of monoclonal antibodies (mAbs), which are important biotherapeutics in the treatment of autoimmune conditions, infections, and cancer—and ha ...
Kariana Andrea Moreno Sader
Kariana Andrea Moreno Sader is a PhD candidate whose research focuses on decarbonizing transportation systems, a key component in addressing climate change and developing a sustainable, global economy. Specifically, Kariana uses a combination of MATLAB-based simulation and analysis to compare options in long-haul trucking, one of the most challenging sectors of the economy to decarbonize. As a MathWorks Fellow, Kariana will advance her innovative modeling techniques to provide comparisons of ...