Toros Arikan is a PhD candidate whose interdisciplinary work integrates signal processing, machine learning, and computational imaging to significantly expand the capabilities of sensing systems for acoustic, radio frequency (RF), and optical modalities. With the support of a MathWorks Fellowship, Toros will pursue innovative research that takes a new, and potentially highly useful, view of system design. Traditionally, system designs are based on relatively low-dimensional models. Toros’s work, by contrast, embraces high-dimensional models and finds potential in that complexity for better performance and surprising new capabilities. One example is the presence of unknown complex obstacles and reflecting structure in physical environments that can improve object localization and scene imaging performance. MATLAB tools play a central role in Toros’s research, serving as his algorithm prototyping and experimental data analysis environment. The tools, methods, and insights emerging from this work hold important potential for future research and applications, including the acoustic and RF communities. To help realize these new possibilities, Toros will make the resulting tools of his research widely available through the MathWorks File Exchange.