Kevin Wong:

Education: B.S. Math and Physics, M.S. Physics, Dropped out of Cognitive Psychology PhD hoping to enter the real world as a data scientist or full-stack developer.

Creator of Ethos AI. 

Portfolio sample:

Real time parameter estimation using particle filters. This technique could make fMRI analyses more accurate and hopefully, ideas from this project will be extended to shorten the long scan times involved in fMRI research. This could save time, money, and lives.

Data visualization: collection of simple data visualization techniques.

Housing Price prediction (XGBoost Regression)

Real Time facial feature recognition using OpenCV:

and of course this site!

Personal Summary:

In high school, I didn't really have plans for my future, and wasn't even sure about going to college. I ended up going to UC Riverside, even though I didn't apply there. During the summer in between high school and college, I worked my first 9-5 job selling drugs.

At a pharmacy.

This was my first time I was sort of independent, so I wanted to see what I was capable of. Every morning I arrived to work about an hour early to read pages from 2 books: Calculus of a Single Variable by J. W. Kitchen and Chemistry by Oxtoby and Gillis. I have never felt so focused. As I read Kitchen, I felt as if I was learning secrets to the universe. General truths were revealed in the cleanest arguments I've seen. Oxtoby gave me my first glimpse of emergent phenomenon: how important structures like atoms, cells, organs, life, or planets, emerge from smaller scales. Many people attribute this to a god, but to me, it was something more. Only years later did I discover the concept of the renormalization group.

I then decided to major in physics. Since I didn't meet the prereqs for some upper division physics courses, I decided to take a bunch of math classes for fun. I was reminded of math's general truth revealing properties. So I decided to take a second major in pure math. I was then sent an email about the Putnam math competition, an annual undergraduate math competition in the US and Canada. The average score each year tends to be around 1/120 and each problem is worth 10 points... We would have unofficial weekly club meetings to talk about relatively low level problems. Simply communicating mathematical concepts to my friends taught me a lot about other ways of thinking. Small communities like this made my time at UC Riverside very well spent.

Before graduating, I faced a familiar problem of not knowing what to do with my life, so I just went with the natural choice by attending the physics PhD program at Ohio State. I honestly chose the school based on their building and how much more money they offered compared to California. My time here was mostly review, but I did gain self-confidence by teaching classes. In the past, I've always feared publc speaking. I felt nervous at first, but over time, I learned to turn the nerves into excitement which fueled my teaching. Teaching actually became fun! So, by the time I left, I felt it was time well spent.

After lecturing for a year, I later transfered to the cognitive psychology department since I found a new interesting question: how does consciousness emerge from the brain? I started pondering this after doing a computer letter recognition project in one of my computational physics classes and trying to understand how people (like my students) learned new things. However, even though I was comfortable with my math and physics, I had absolutely no knowledge of psychology or statistics. I picked a lot of pieces up, but there where more pieces than I could count. I ultimately left with the hope that I can learn faster through self-motivation while gaining real world experience.

With technical knowledge (like data science, statistics, and computer science), we have the tools to explore anything of interest, while bettering the world and connecting with others. If jobs aren't available, make them! This is one of my reasons for sharing my journey.


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