I live next to a train. To be more specific, the desk I am currently typing on is approximately 200 ft from the tracks. I have become somewhat immune to the shockingly loud train horns that trumpet several times each day and literally shake my apartment. Still, I began wondering if there is any rhyme or reason to the train’s schedule.
Coding Projects
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As this is a lengthy and somewhat technical post, here’s a summary. The AIM marketplace matches officers with their next assignment. After resume exchanges and interviews, officers and units each submit a ranking of their preferences. Then, human resources runs the Gale-Shapley algorithm to determine the matches. However, there is considerable scheming in the form of both parties revealing/lying about their preferences and units pressuring officers to rank them highly. I wanted to understand how varying degrees of scheming affected the optimality of the match and, in particular, whether rule breaking was incentivized under these conditions. I found that rule breaking is advantageous under almost all circumstance for both units and officers. Those that don’t break the rules perform worse on average. The rule breaking allows both units and officers to outperform the Gale-Shapley baseline. There are a number of limitations to these findings based on the simplifications inherent in modeling a complicated, dynamic process.
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A Chinese Salesman in Shippan
Shippan is a beautiful community of a hundred houses or so that sit on a peninsula in the Long Island sound. It’s a popular place to go for a walk, and I have spent considerable time running there. One day, as I was running around this neighborhood, I began to think about visiting every home. How long would it take to walk every street?
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The NFL just had its annual draft. My team, the Chicago Bears, had the first overall pick and traded down. The Chicago Blackhawks also recently won the lottery for the first NHL draft pick with considerable excitement about potential generational talent Connor Bedard. The Chicago Bulls lottery pick fell outside of the top four and their pick thus went to the Orlando Magic. For all the excitement, how big of a difference does this all make? How reliably does having a higher draft pick translate to drafting a better player?
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TLDR: I saved my coworkers hours of time by automating a menial task.
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TLDR: I explored biographical Wikipedia articles and their popularity.
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The kickoff has traditionally been one of the most exciting plays in football. I remember the joy of watching Devin Hester in his prime. Every time he touched the ball, everyone held their breath! But the excitement goes hand-in-hand with danger and injury risk, and the NFL determined the violent full-speed collisions on kickoffs were too dangerous. So, in 2011, the NFL moved the kick from the 30 yard line to the 35 yard line, along with limiting the running start by the kickoff team to 5 yards. The hope was to increase touchbacks and reduce the speed of collisions. It worked! They further attempted to discourage returns for the 2016 season when they moved the touchback starting position from the 20 yard line to the 25 yard line.
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I am an unfortunate soul. Chicago sports fandom was bestowed upon me, as it was upon my father and my father’s father. While there is the occasional flare of success with a particular team (90s Bulls, 80s Bears, 2010s Blackhawks), the city as a whole seems doomed to mediocrity.
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The Army has changed as an employer significantly over the course of the 20th century. It transitioned from a smaller professional Army with a draft to an all-volunteer force. I was curious how, if at all, this change has reflected in wages.
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My thesis can be found here. I won’t talk about the content; you’ll have to read it. Instead, I’ll share a quick reflection on the value of writing a thesis.
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I thought I’d share a final course project I did on “The Rise of the Career Politician.” The website can be found here.
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TLDR: I attempt to illustrate the History of the Peloponnesian War by extracting locations using natural language processing and plotting them using Python Plotly.
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TLDR: I run an elevator simulation to determine optimal behavior in my apartment building when an elevator breaks.