Panel Title: Learning to Learn: Developing New Data Analysis Skills in STEM
Panel Moderator: Dr. Gary Snyder
Our panel explores how college researchers apply foundational knowledge from our education to tackle diverse, data-driven projects across multiple disciplines. Each project—ranging from Social Network Analysis, DNA translocation through nanopores, Graph Theory, Social Communication and Habituation, and Deep Learning with Computer Vision for Traffic Digital Twin—required the rapid development of unique analytical skills. We will discuss how we bridged theoretical learning with hands-on application, navigating the challenges of unfamiliar methodologies, balancing stress, and learning when to ask for help. Through both quantitative and theoretical approaches, we engaged with data in ways that pushed us to quickly adapt and identify our learning needs. Our experiences highlight a core realization: the true value of a college education lies not just in content knowledge, but in the ability to develop and implement new skills and collaborate across disciplinary boundaries in new environments. This panel underscores the importance of flexibility, resilience, and interdisciplinary thinking in collaborative research environments.

• Speaker 1 Name: Siyu Lan
  Title: From Data to Insight: A Journey Through Social Network Analysis and Collaborative Research
• Speaker 2 Name: Diksha batra
  Title: Understanding DNA translocation through New Mediums
• Speaker 3 Name: Sarahjeen Paul
  Title: Conquering Graph Theory
• Speaker 4 Name: Arin Lalsare
  Title: Little Goals (and Small Animal Communication) are a Big Deal
• Speaker 5 Name: Autumn Nguyen
  Title: Interning at the Department of Energy’s National Lab