Giving tech labs
“Hi Arthur, What is special about July 31?”
Because of covid, most normal workflows were interrupted. In-person attendance was no longer mandatory (or even encouraged) and finals were cancelled. My job at Giving Tech Labs was one of the more fortunate ones that could be done remotely.
The brilliant people at Giving Tech Labs had the idea of doing a Reindeer Gift exchange, giving everyone a $20 Amazon gift certificate and a matching budget. The idea was to leave a clue in the gift receipt that would help them guess who gave the gift. We weren’t just playing for bragging rights either–winner took home another $20.
So, alongside a muscle roller and a small pad of mini notebooks, came a note with a simple question. “Hi Arthur, What is special about July 31?”
Obviously, it is Harry Potter’s birthday, but apparently, it was also the day I came in for my in-person interview and met the chief research scientist in charge of my research fellowship, Dr. Ying Li.
And no, I didn’t win $20.
But besides learning the correct answer to this question, I’ve learned a few other things during my experience this last year. Here are some of them:
1) Don’t go to work twice a day.
Yeah, this one is pretty obvious, but it goes to show that Freshman optimism can be pretty irrational. To be fair, it was a great opportunity for me to read more. I consider myself a binge reader only because any book that I find worth picking up is one that is hard to put down. Commuting to and from work meant I had these nice restricted windows of reading time where I couldn’t do much else. Going twice, however, gives some diminishing returns. In fact, I opted instead to wake up at 7:00 and get to work extra early. (I still don’t understand how my highschool self could wake up at 6:15 everyday… 7:00 is painful in college.)
2) Vision is pretty cool
Whereas optimism is generally not great for planning work schedules, the vision and optimism that Dr. Ying and Research Fellowship Officer Vitalli brought to the table was indispensable. I remember the first time Vitalli was explaining the knowledge graph and sound voice projects to me, and I was both confused and a little skeptical. I am glad that both of them were always 100% convinced and believed in the work because with research, I often felt like I was not getting much progress.
During our demo’s, Dr. Ying would always elaborate on where we were heading from the smaller protoypes and pieces we were building, and I am thankful that she was able to remind us of what was over the hill.
3) The Value of a Program Manager
I was a little surprised when I found out that our program manager, Vitalli, would not be helping us out with the coding process. It turns out that having someone handle the logistics is a big life saver and essential for pushing a project forward. Among his many tasks, Vitalli meticulously planned out sprints and scoped out our project, discussing deliverables with other companies as well as clarifying the details of our designs. Basically, PM’s are pretty great.
4) Try not to eat all the snacks
One of the perks of working at Giving Tech Labs was the free snacks. I definitely got up from my seat too often to grab some snacks, but that’s clearly because I needed more brain juice to output all the great work I was doing ;). I’m not sure that I really practiced this advice, but after indulging myself on too many cheese-its and peanut butter pretzels, it feels nice to bring some lunch and eat some real meals instead.
Wow
I’m realizing it’s pretty hard to remember let alone summarize a whole year all in one post, so maybe I’ll write a followup in the future. Maybe.
Some of the other cool things that happened was…
…releasing SUVOTEK SDK Technology used in a voice coaching app, Coach Ana! (Only OG GTL employees will remember Ora’s Voice).
…getting a paper accepted to the ACM SIGKDD 2020 Conference: Acoustic Measures for Real-Time Voice Coaching! I ran some pretty cool intonation experiments with some neat graphs (peep the thumbnail image of this blog!).
…writing some neat pipelines that crawled webpages, classified grants with a model, and extracted data for our knowledge graph
…and graduating early :,)
