Aaron L.

Distributed Systems Engineering

Software Engineer on the Cell Manufacturing Software Team

Researching MRI imaging parameters. Employing machine learning to achieve high fidelity reconstructions from undersampled signal-domain data with Bloch simulators and deep learning neural networks using the PyTorch and Tensorflow interfaces in the Pines and Reimer Lab.

Undergraduate student researcher in the AGURP program run by the Alivisatos Group at UC Berkeley. Analyzed supercomputer generated data from the Materials Project database to find trends between thermal expansion coefficient and elastic behaviour in negative and zero thermal expansion materials.

Worked on reformulating a Hidden Valley Ranch dressing product using food science to find suitable alternative ingredients to reduce costs and match policy trends

Developing a pipeline to process SMRT sequencing data to glean epigenetic information using machine learning

Optimized 3D-reconstruction parameters for improved image quality for 3D-ultrasound images and implemented a new metric to quantify the performance of machine learning image enhancement

Researched the structural components of the Nuclear Inclusion a Protease of Turnip Mosaic Virus(TuMV) using deletion mutations and confocal microscopy. Authored original research paper and presented at a research symposium.

Learned about biodiesel synthesis and market feasibility. Converted waste glycerol from biodiesel synthesis into glycerol acetal fuel additives and documented the effects on the freezing point and energy density of the resulting fuel mixture.