A year ago, I faced the greatest predicament of my education so far: I had finally found the discipline truest to my interests, but it was not my area of study. I had been fortunate enough to lead the computational side of our research on the protein cancer target Hsp90 at the Spyracopoulos Lab, and it left me longing for a deeper understanding of the workings and design of distributed systems, multithreaded applications, and distributed programs. I thoroughly enjoyed the computational chemistry and biophysics, but I wanted a deeper technical foundation – one that I could rely on to build scalable software in any industry. And so, I made the difficult decision to pursue another degree in computer science (CS).
I missed the problem solving I did in high school math competitions, and I wanted more robust technical skills that I could apply broadly to my life. The computational research helped me realize that I enjoyed focused problem solving, testing, and troubleshooting with technology far more than hands-on lab work. I will carry my appreciation for research into my CS studies. I am looking forward to trying various CS subfields such as distributed systems, artificial intelligence and machine learning (AI/ML), and cybersecurity while remaining open to further opportunities in computational biology.
After a season of applications, administrative errands, and CS learning, I am more excited than ever to begin my studies this fall at the University of British Columbia (UBC). I am happy to be spending this summer as a Google Summer of Code (GSoC) contributor with MDAnalysis, and I hope you enjoy following along on this blog.