It's finally time for me to wrap up my internship. It's been a phenomenal summer, and I've truly learned so much.
For the last two weeks, I essentially finished reviewing the papers assigned to me, and after a penultimate meeting, we decided on who gets to write which portion of the review paper. I was given the Metrics section, where I had to detail the metrics used to assess the performance of the Transfer Learning (TL) methodology proposed in the papers. Since this is a review paper, its goal is to explain the state-of-the-art in this particular field - Transfer Learning in smart buildings to save energy. The paper will aid future research in this field, as they will get to know what exactly is happening in this sphere. One part of it is to know what metrics have past researchers used to measure performance.
In the process, I learned a lot about how papers are written on LaTeX and general conventions in research writings. I had to work on the logical flow of my writing, which meant dividing my section into cogent sub-sections and writing about the metrics in a way that is easy to comprehend. I started off with the common metrics used, which are also ubiquitous in general Machine Learning papers, and then narrowed down to more specialised metrics.
I've finished writing my section, and it's very gratifying to see your work materialize in such a form, nestled in between other sections written by amazing scientists and researchers. This has been a great journey, and I would like to thank Cal Energy Corps and LBNL for giving me this opportunity to explore my nascent passion for sustainability and energy research.