Ameya was accepted into the acclaimed UCLA ECE Visual Machines Group (VMG) due to her unique background in scientific research and art. VMG's research focuses on simulating human interactions with biomedical sensors to advance healthcare devices. The lab's work has diverse applications in computer vision, including vision models for medical imaging across different skin tones, algorithms for contactless heart rate and blood clot imaging, and equitable healthcare technologies.

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At the UCLA ECE Annual Research Review, Ameya was part of the VMG team that presented a demo on thermal non-line-of-sight (TNLOS) imaging, a computer vision technique that enables self-driving cars to detect objects around corners. The demo was showcased to industry representatives, students, and professors, earning Best Undergraduate Demo.

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At VMG Ameya contributed to a grant proposal for the DARPA Young Faculty Award at the UCLA School of Medicine. The proposal detailed a module of biological sensors and custom imaging systems designed for contactless COVID-19 testing, as well as the process for obtaining patient consent. Her work involved refining the proposal to ensure clarity and precision in describing the research objectives and methodologies.

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Additionally, Ameya worked on reproducing BioFaceNet, a deep convolutional neural network (CNN) designed to infer biophysical properties, such as blood volume, hemoglobin content, and melanin content from facial images.

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