During my time as a lab technician in Sjulson Lab, I helped the lab optimize their data analysis by studying and analyzing various dimensional reduction algorithms, including PCA, gPCA, ePCA, lPCA, and NMF. I determined which of these algorithms effectively reduced the gigabytes of neuronal spike data into visual trends that the Dr. Sjulson could use in his research. I then presented these findings to the rest of the lab. Near the end of my term at the lab, I also began studying the MATLAB machine learning interface to classify theta and ripple cells by their firing patterns. 

This was my first professional programming job. Working as the only high schooler in a lab full of graduate students, I felt intimidated, yet my mentors were happy to help lead me in the right direction. The fundamental design patterns I learned from Dr. Sjulson still follow me into the work I do today. I am very grateful to Dr. Sjulson and the rest of his staff for giving me this opportunity and I wish them the best in their future endeavors. 

Repository: https://github.com/jakejack13/DimensionalReduction
Lab website: https://sjulsonlab.org/