HEAL @ Olin College

At Olin’s HEAL bio-photonics lab, I am contributing to pioneering research aimed at developing noninvasive photoacoustic diagnostics for endometriosis. As a part of our optical phantoms sub-team, I work to design affordable materials that accurately replicate the optical characteristics of human tissues. 

My primary role has been developing a Python-based tool to systematically process experimental spectroscopic data. This tool automates data transformations and calculates absorbance using the Beer-Lambert law, enabling quick statistical assessments, such as standard deviation, that are critical to ensuring experimental reliability. Additionally, I enhanced data entry methods, significantly improving user experience and automation compatibility. 

The structured and streamlined nature of this software significantly improves our lab’s ability to interpret results and accelerates our progress toward accessible, noninvasive diagnostic solutions.  

Most of my technical contributions at HEAL have involved creating software solutions to manage and analyze complex spectroscopic datasets efficiently. Using Python libraries like Pandas and NumPy, my software ingests raw experimental data from the spectrometer, applies the Beer-Lambert law to calculate absorbance values, and computes key statistics such as standard deviations. The software automatically exports the results into a neatly structured Excel file, making it straightforward for all team members to quickly engage with the data and streamline their workflow. 

By streamlining labor-intensive workflows, this software frees our researchers to prioritize meaningful data interpretation, strategic decision-making, and ongoing optical phantom development.  

Throughout this experience, I’ve learned how to effectively operate a spectrometer, create optical phantoms, and manage complex user-collected scientific data to enhance usability and accessibility. I’m deeply grateful to HEAL at Olin College for providing this enriching opportunity, helping me build a solid foundation in medical devices and biophotonics.