Top 6 photos from first family photo shoot

Below are my top 6 photos I cherry picked from our first family photo shoot that took place a couple weeks ago.

As some of you my already know, my daughter Elliott was born recently, on October 3rd (2019). And shortly after, my wife had arranged for a professional photographer — Stephanie BC — to spend half the day in our Pacific Northwest home, scheduling the photographer on a typical, no sunshine Sunday to snap some photos and capture some moments of our growing wolf pack: once four now five (3 humans and 2 dogs).

And I must say, the images turned out nothing short of beautiful; I could not be any happier with not just the end product but the process itself. Apart from one or two photos, all the captured images are not staged, meaning we were not posing or putting on a forced smile or contorting our arms and body in some uncomfortable (but aesthetically pleasing) position. The entire shoot felt organic.

Anyways, enough of the chatter. Here are my 6 photos I hand picked from the our shoot.

Music. Such a gift. Here I am playing guitar and singing for Elliott and my wife. The song is titled “My Little Bird”, which I wrote when Elliott was just a week or two old.
This is how I spend 90% of my time with Elliott: cradling her in my arms and rocking her to sleep.
Here’s my and my first fur daughter: Metric. In her head, she weights 10 pounds still and loves to lean all her weight on those willing.
Look at this cutie staring out the window while I hold her in the foot ball position. I cannot imagine that I’ll be able to hold her like this much longer since her weight is increasing exponentially, my forearms no longer able to sustain the burn.
Yes. She’s peeing all over me. Luckily, this time, the pee only hits my shirt and my jeans. I have been tagged in the eye and mouth (who knew girls and projectile pee like boys).
Me giving Elliott what I call “Kissy kisses” (no idea how I came up with that name) while she rests on top of my wife’s folded legs.

Almost half way through M.S. in Computer Science

I’m almost half way through the OMSCS (online masters in computer science), last week marking the end Spring 2020, my third term in the program. And although I’m looking forward to taking compilers next semester, my mind often wanders into the distant future , my mind fast forwarding to the time in which I’ll be graduating from the program. So, I stitched together a line graph that includes the classes, breaking down each term along with the courses that I’ve already taken (and will take). Here’s what it looks like:

As you can see from the above graph, I’ve historically taken one class per semester (except for the previous semester, when I simultaneously took information security and computer networks simultaneously); taking one class per semester takes the middle path, allowing me to balance school and work and family and other obligations and the millions of my other hobbies (e.g. singing, guitar). So at this current rate, I anticipate that I’ll graduate in Spring 2021 — 2 years from now. Seems like a long time away but it really isn’t. Because as they say: time flies. And It really does. Feels like yesterday when my wife and I were discussing whether it even made sense for me to apply and enroll to this masters program.

Masters in CS paying off

Taking computer science courses are already paying off in my career. Nothing too significant (yet) but I am witnessing small wins.

For example, this past summer I suffered through HPCA (high performance computing architecture), a course historically only offered in the longer semesters (e.g. fall, spring). In the course, I learned a lot of theory: barrier synchronization, processing pipelines, instruction scheduling, multi level caches, branch predicators, cache coherence protocols, and much more (many of which I have already purged from my memory). However, since most of that knowledge was primarily theory, very little of it I’ve been able to directly apply to my day to day job.

Until a couple days ago.

While at work, my co-worker had pointed out that the unlikely C function calls were sprinkled throughout our code base, used for branch prediction. And thanks to theory, I was able to describe to another co worker how the compiler (with its understanding of the underlying CPU architecture) will rearrange the assembly (or machine code) in order to avoid a branch prediction miss: if the wrong instruction is fetched, the processing pipeline must flush all the previous instructions queued in the pipeline, temporarily halting the pipeline, which ultimately reduces the throughput.

And this is just one example of how taking my masters had paid off. There have been a number of other situations (like understanding shared memory and interprocess communication) that I’ve been able to apply theory from academia to practice at work.

Thanks to the program, I’m feeling much more competent and confident working as a software developer at Amazon Web Services.