Students Explored a Diversity of Topics at the DSAN Fall Poster Sessions
Poster sessions are an important part of the student experience within the MS Data Science & Analytics program. Not only do they allow students to explore a wide range of topics, they provide an opportunity for students to fine-tune their research, project management and presentation skills.
Earlier this month, students from both the Advanced Research Methodologies (Capstone Project) course and our Data Science and Climate Change course gathered to present their projects to an audience of faculty, staff, mentors, and fellow students.
The Advanced Research Methodologies course, taught by Dr. Britt He, guides students in developing data science research projects as well as teaching effective scientific writing. Topics include the principles of research questions development, research methods selection, effective results interpretation, effective writing, appropriate journal paper writing styles, peer review, authorship, and communicating scientific ideas to academic and non-academic audiences. This year’s students worked with mentors from a wide-ranging list of organizations such as USAID and AstraZeneca, and on a wide range of subject areas, from anthropology to modern media.
Many students in this course will go on to pursue PhDs and/or research positions in the field.
Our Data Science and Climate Change course investigates the myriad ways Data Science can be used to address climate change. This includes aspects of climate change in which Data Science is already beginning to tackle, such as mitigating emissions from the five most carbon-intensive societal activities – energy, manufacturing, agriculture / land use, transportation, and buildings / infrastructure.
This year’s students explored applied data science techniques to a variety of climate change issues, including:
- assessing marine biodiversity
- forecasting climate-driven trends (storms, floods, sea level rise, wildfires, heatwaves, crop failure, vector-borne disease)
- optimizing agricultural practices
- understanding political sentiment
- analyzing the effect of renewables on the energy grid
- automating waste categorization
“This was phenomenal hands-on work at the intersection of two profound societal forces: AI and climate change”- Prof. Dan Loehr- Data Science and Climate Change
We can’t wait to see what these students do next!