Dexter A
- Research Program Mentor
MS at University of California Davis (UCD)
Expertise
Chemistry/Biochemistry Machine Learning, Open Source Software Development and Spectroscopy (and combining all of those fields together)
Bio
I am a recent graduate passionate about applying next-gen data science techniques to improve processes and draw novel insights from unusual data. I have experience in a range of disciplines including computer science, statistics, chemistry, chemical engineering, and biomanufacturing. I recently completed a Master of Science degree in Chemical Engineering with the thesis topic "Removing Bottlenecks in Research Workflows: Improving SERS Sampling and Computational Zeolite Experiments through the Application of Machine Learning and the Construction of Custom Data Pipelines". I enjoy exploring the outdoors in my free time. I am currently living in Davis California, but I frequently go home to the Bay Area on the weekends to explore the nice hikes there. I also enjoy working on my own personal coding projects and learning new things.Project ideas
Applying machine learning to interpret the Raman spectra of mixtures
Raman spectroscopy is an emerging, non-destructive analytical technique useful in-line bioprocess monitoring. A major barrier to its widespread deployment is the challenge interpreting the spectra of mixtures. Advanced computer vision algorithms have shown considerable promise in improving the interpretation of these mixture spectra, yet advances in this area are limited due to the lack of freely available Raman mixture datasets. Software can be used to generate synthetic Raman spectra, allowing for the creation of large datasets needed to assess the performance of computer vision algorithms. There is limited research in this area and it would be an exciting, inexpensive project to explore spectroscopy, machine learning, software development and biopharmaceutical production.