Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 1

One of my previous projects named, "Parallelization of bandit algorithms to reduce computational cost of news article recommendation systems." was selected for poster presentation at yearly project exhibition at UNIST.
In my previous internship, I was working with one of the state-of-the-art CNN architectures called “HRNet” to estimate poses from 2D data. Our experiments led to a 0.01% increase in the accuracy of the model. Prior to that, I was working on recommending news articles to the users using bandit algorithms. Our task was to reduce computation to provide services to multiple users in a short amount of time. Final algorithms increased the recommendation speed almost twice than the previous algorithms.
Currently, I'm more interested to explore the application of AI in real life since my previous works were mostly related to academia. I want to see how the state of the arts models react in real life scenario.