Over a zoom meeting, Justin Weltz from Duke university called us to discuss social networks and sampling methods. We discussed the pros and cons of biased and random sampling and applied sampling probabilities with math. We also further discussed reinforcement learning today and how it connects to AI and machine learning.
This morning, we met with Justin Weltz, a grad student at Duke about his research in Reinforcement Learning and Response Driven Sampling. However, something interesting is that he actually didn’t start out planning to go into computer science. He went into undergrad initially focusing on English/Political Science and decided to pursue more Statistics/Computer Science related ideas in his junior year. After making that decision, Justin applied to Duke grad school on a whim and wasn’t sure if he’d actually get in. Overall, Justin found that grad school was a good experience and much more self directed than high school or undergrad. While his first year had a lot of classes and work, his second year, when he began researching RDS with Dr. Laber, was much more research oriented and independent, without a set schedule.