I was a terrible student. Not "got a B in chemistry" terrible. When I started community college, I placed into remedial math, remedial reading, and remedial writing. Not one of those. All three!
It wasn't until I met my wife that I started taking it seriously. She saw something in me that I didn't see in myself. We were hanging out one day when she looked at me and said, "What about engineering? You're great with computers."
So I went for it. Even starting that far behind, I wanted to finish in four years, so I took 24 credit hours a semester to catch up. A normal full load is 12 to 15. I'm still proud of that one.
It sounds more impressive than it is. At community college there were a lot of 8-week accelerated courses I could stack in the first half of a semester and then keep going in the second half. That made it easier for me to get caught up and transfer into the University of Oklahoma. At the time, I was juggling 24 hours a semester while working two jobs to make sure I could pay my rent (and my coffee bill).
Then I transferred into the electrical engineering program at OU. Circuits 1 beat me. Not just the first time, the first three times! After the third, I had the audacity to ask the professor if I could be his TA. Prof. Fitz took a chance on me, and the next semester I was the teaching assistant for the class I'd failed three times. That job came with financial assistance, and over the next two semesters I scored a 4.0. I ended up TA'ing Intro to Digital Design too. I got pulled into undergraduate RF research, which is how I ended up working on cell networks for a living. I spent my last year of school as a co-op at T-Mobile and graduated in December 2016.
What being bad at math taught me
Struggling with math made me better at explaining it. When you've been the person in the back of the room who doesn't get it, you remember exactly where the explanation lost you.
Things finally clicked when I stopped memorizing how to solve the problem and took a step back to learn the concept underneath it. Then I had to teach it, and that's when things really took off. You can fake your way through a homework set. You can't fake it in front of a room full of students asking why.
That's still how I work. When I walk a customer's leadership team through network data, I'm basically talking to my remedial-math self. No jargon until it's earned, one chart that makes the point, and the caveats said out loud.
What I tell my capstone students
For the last two years I've been a senior capstone mentor at OU, which still feels a little funny given where I started. Now I'm bringing it closer to home. I sit on the Industry Advisory Board for the University of Houston's ECE department, and I've proposed hosting a similar senior capstone project there too. The projects use real connectivity data and they're ambiguous on purpose. Nobody hands the students a clean question, and most teams get a lot wrong at first. That's the point. Real data doesn't come with an answer key.
The last team analyzed how internet performance in Vietnam changed from 2019 to 2025, with a pretty limited dataset. It didn't say which technology each measurement came from, so they used speed and latency to estimate where 4G and 5G had rolled out. They also noticed the number of speed tests dropped during big storms, and used that drop as a clue for where outages hit. Watching that come together over a semester was pretty cool.
What I tell them is what I wish someone had told me:
- Being behind isn't the same as being bad at something.
- Learn the concept before the problem. Once you get why it works, the answers follow.
- Ask the question you think is dumb. Somebody else in the room is wondering the same thing.
If you're starting from behind
If you're starting from behind, let that be a data point, not a defining factor.
It's funny. In the gym, missing a rep or a weight was never a big deal. It was always "no problem, next time." I just never carried that attitude into any other part of my life.
Looking back, that's what this whole story was. Remedial classes were just my starting number. Failing Circuits 1 three times was three reps that didn't go up, and the fourth time around I was the one teaching it. Same thing for my capstone students: a first analysis that falls apart is just the first attempt on a messy dataset.
So get comfortable failing. Every miss is a chance to try again, and the embarrassment of trying gets you one step closer to what you want.