Hello, I’m Brandon,
I am excited to share with you my unique, nontraditional journey and experiences as an avid scholar and professional in mathematics and computer engineering. I am duly eager to share where my passions and experiences have taken me to now, and what lessons from undergrad I feel were most helpful moving forward. I plan to share all of these things with you here in hopes to foster motivation for those planning on pursuing either of these fields, and to hopefully make the journey a little less arduous for others.
I found that I had an admiration for mathematics early on in my course of education, and quickly found my niches in digital logic, set theory of mathematics, and differential equations (ODEs and PDEs). I quickly understood that mathematics such as these, are for individuals willing to push their comprehension of physical nature, and must want to pursue a deeper, foundational understanding of the world around them in terms of mathematics and equations.
During my time in undergrad I collected a slew of diverse and thought-provoking experiences, including: taking a course on epidemiology models, conducting research in AI, learning and utilizing Matlab, and mastering the techniques of Numerical Analysis. Though these experiences are multifarious and quite distinct from one another, they all had an easily overlooked relationship that connected them collaboratively: the finite difference method.
My newfound interest in the finite difference method led me down a rabithole of fervent reading on the subject, where I quickly connected it to my previous understanding in epidemiological models. While I was formulating the code for the finite difference code, I realized that the equations were turned into arithmetic problems and that some of these arithmetic could be replaced by a convolution if the equations were re-arranged. It was rewarding, challenging and fascinating all at once.
I also want to share the obstacles and challenges I am facing as well, the prominent barrier being that I am not trained as an Engineer or Physicist. Since I have spent little time translating physical systems into the differential equations that describe the problem, I do not have the knowledge or practice necessary to formulate the physical interpretations of any of these equations. Thus, I have now met somewhat of a roadblock, and feel unable to move forward with my technique because I don’t know how to implement my work in real world applications.
My next step in this journey is to determine how to conquer this obstacle and move forward. I now find myself questioning what the next best step is. Should I change the trajectory of my career? Move forward in the abstract? Retrain myself as an Engineer? But, which subject do I choose to study then? I continue to find myself feeling confused and unsure of what route is best to take, especially since I still enjoy computer engineering. But, how do I apply this to a simulation format?
I hope that this blog not only provides valuable advice for others, but can also open discussions and commentary around the uncertainty I am facing with my own career and work presently. Additionally, I hope to encourage an environment where students and professionals alike can share what they’ve learned and aid others in finding the most fulfilling and befitting careers in the fields of mathematics, engineering, computer engineering, and/or physics.
I look forward to growing and learning with you!
Best regards, Brandon