Aerial Mycelium Process Development
Ecovative Design
2023–2026
Developed and optimized cultivation processes for aerial mycelium production, resulting in co-inventorship on a patent covering growth media compositions and environmental conditions. Work encompassed media design, environmental programming (temperature, CO₂, airflow, mist rate), pre-colonization optimization, and aerial growth phase control. Contributed to a platform tracking 25 environmental conditions in real time, with AI-model-informed decision-making across 26,000+ growth records.
Mycelium Cultivation Process Development Media Optimization Environmental Programming Patent Scale-up
Quantitative MRI for Tumor Treatment Response
Weill Cornell Medical College / NYU
2020–2023
Developed and validated novel MRI methods for measuring cellular water exchange and treatment response in glioma models. First-author work published in Scientific Reports demonstrated that a two-flip-angle DCE-MRI approach can quantify intracellular water lifetime (τᵢ), providing a metabolic biomarker that correlates negatively with FDG-PET uptake. This work bridges imaging physics, computational modeling, and translational cancer biology.
DCE-MRI Pharmacokinetic Modeling Cancer Biology Quantitative Imaging Scientific Reports
Image Texture Analysis & Reproducibility in Preclinical MRI
Weill Cornell Medical College
2021–2023
Investigated how image resolution affects the reliability of texture features derived from pharmacokinetic parameter maps. First-author publication in Tomography demonstrated that 3D isotropic resolution is critical for reproducible radiomics analysis. This work has implications for standardizing preclinical imaging protocols and making quantitative biomarkers more robust across studies.
Radiomics Image Analysis Reproducibility 7T MRI Preclinical Imaging Tomography
Active Contrast Encoding (ACE) MRI Development
NYU / Weill Cornell
2020–2022
Contributed to the development and validation of ACE-MRI, a method for simultaneous estimation of contrast agent kinetics and tissue relaxation parameters. This technique enables more efficient characterization of tumor microenvironment compared to conventional DCE-MRI. Research presented at multiple ISMRM annual meetings and published as a collaborative journal article.
ACE-MRI Method Development Tumor Microenvironment ISMRM Collaboration