User:Edoyle
About Me
My name is Erin Doyle and I am a rising senior at St. Mary's College majoring in Mathematics. I am working with Dr. Puri on analyzing ICESat-2 data to look at sea ice melting specifically in the Arctic.
Work Log
Week 1
• REU Orientation
• Mini Data Science Bootcamp
• Met with Dr. Puri to discuss project specifics
• Good research practices and recording work logs talk from Dr. Brylow
• Read various articles and videos about my specific project from Dr. Puri
• Wrote about my research goals and milestones
Week 2
• Developed more specific research questions
• Attended RCR training from Dr. Brylow
• Finished the CITI modules
• Read research papers
• Attended technical writing meeting
• Researched parameters used in the data and their meaning
• Looked and previous code samples and downloaded some data to begin working with
• Met with Dr. Puri on teams to discuss project
Week 3
• Used GitHub resources and started building a code to classify leads vs. Solid sea ice
• Created my Wiki page and updated profile
• Downloaded test data from NSIDC to use in my code
• Attended student check in
• Meet with Dr. Puri to discuss project and steps to go forward
• Download HDF5 viewer to look into data more
• Signed up for XSEDE user portal
• Read ATL03 NSIDC data algorithm paper
• Looked at XSEDE portal
• Met with Dr. Puri on Teams to discuss next weeks work
Week 4
• Read research papers finding various ways sea ice thickness has been modeled before
• Found some code on GitHub of a previous modeling of sea ice thickness prediction algorithm
• Read about various models that are used for predicting sea ice thickness
• Looked at University of Washington’s Hackweek machine learning algorithm they used for modeling ATL03 data
• Emailed Dr. Puri to follow up on next steps
• Read “Feasibility of Burned Area Mapping Based on ICESat-2 Photon Counting Data”
• Preprocessed the data to prepare
• Built a Gaussian and K-fold model for the data
• Met with Dr. Puri on teams
Week 5
• Worked on my mini presentation
• Read research papers about machine learning techniques for remote sensing
• Emailed Dr. Puri about my presentation
• Downloaded Cyberduck
• Met with Dr.Puri on teams to go over presentation
• Watched some tutorial videos
• Practiced my presentation to time it
• Attended the mini presentation with the other students
• Worked on Python code and download HDF5 files
• Followed up on progress with Dr. Puri
Week 6
• Attended Data Ethics talk
• Converted the h5files to text files
• Attended good poster presentation talk
• Student check in
• Gathered more data
• Met with Dr. Puri on teams to discuss desired approach
• Continued working on machine learning model
• Began plotting and debugging model
Week 7
• Made progress on machine learning model
• Began planning out research paper
• Improved accuracy of model
• Followed up with Dr. Puri about a few questions
• Student check in
• Debugged some of code
• Met with Dr. Puri on teams to go over my code
• Started writing paper
Week 8
• Met with Dr. Puri and Anmol on teams to fix the error in my code
• Finished outline for paper
• Researched vector autoregression
• Made improvements to neural network
• Gathered data for vector autoregression
• Started writing code for vector autoregression
• Started methods section of paper
• Followed up with Dr. Puri
Week 9
• Looked at old poster presentations from previous years
• Followed up on emails with Dr. Puri
• Attended Industry Panel
• Began writing Intro section of paper
• Started poster
• Read research papers sent by Dr. Puri to improve code
• Attended weekly check in
• Continued working on poster
• Met with Dr. Puri on Teams
• Continued working on paper
• Completed first draft of poster
Week 10
• Completed and turned in poster
• Continued working on methods section of paper
• Completed presentation and had it reviewed
• Worked on results and conclusion section of paper
• Attended student presentations
• Attended student poster section
• Present and attended other student presentations
• Finished paper
• Turned all my work in
