MaiSci ☕

  Algorithm coding battle sounds cool. That is the main reason why I chose to join the terminal competition, organized by Correlation One and Citadel, recommended by one of my friends   Xinyu . It was the first time for me to take part in such a coding competition. Beyond my expectation, our team hit top 8 out of 34 participating teams. Special thanks to   Henry Rossiter   and   Prajval Gupta , who are excellent team members to work with. Made it to Finalist Bracket. Please forgive the organizers’ typo of our  algo  name. Prajval made a thorough after-game analysis of  pros  and cons of our algorithms. Appreciate his summary  here . Overall, we implemented a balanced strategy of defeating and defending, which performs well in the first several battles. Also, we chose to send waves of attackers every 3 turns with both “attack absorbers” and “tanks”. As the costs for different attack units were changed a lot specifically for the competition by the organizer, defending wave hit strategy s

    DII (Discover, Innovate, Impact) challenge is a national data science challenge held by UTHeath with Amazon AWS platform. Coincidentally, I saw a  group  recruiting members when glancing at my phone. I personally had no practical experience in a data science project. All I had learned were the machine learning theories in a seminar in my undergraduate years. This challenge could be a pretty good chance for me to implement the theories I learned and get a feeling about all the tools the data scientists usually use. Doing scientific research in the era when interdisciplinary thinking is critical, it is definitely worthwhile to extend knowledge and skills. Plus, I also like the experience to try new things from scratch. So there I am. Since the challenge was based on real patients’ data, the restrictions of getting access to the database are pretty strict. At the registration phase, we need to get a signature from the affiliation to sanction our participation, which became a tricky pr