Here I’m writing about my life changing experience at the Interdisciplinary and Quantitative REU en la Universidad de Puerto Rico, Rio Piedras. I hope sharing this experience can be useful to any students interested in doing an academic research internship in Puerto Rico or any other research institution.
How did I get here?
With the support of the Los Medanos College Math Engineering Science Achievement (MESA) program’s weekly newsletter I got wind of this really cool sounding opportunity. If I had to be honest, at the moment I saw the opportunity I thought it was not for me considering I had not taken a single biology course nor had interest in biology as I was taking all engineering and computer science classes.
But.. desperate times called for desperate measures. I had not a single idea where I was going to spend my summer and at this point I was distraught after not hearing back from so many internship applications I submitted for software engineering roles. Prof. Melinda Capes, my teacher for Chemistry, at this point had always been incredibly supportive of my education and was willing to not only revise my personal statement and application but also write me a letter of recommendation, which I would find out later was the biggest reason I even was given a shot to intern per my advisor at Puerto Rico. I really owe everything to Prof. Capes and everyone else that got me in the position I am today.
What did I do?
|Sofia Melendez Gartagena (far left), Dr Patricia Ordonez ( left) and Dr Jose Agosto Rivera (right)|
I was afforded my first opportunity to conduct formal research as a NSF funded, University of Puerto Rico-Río Piedras Interdisciplinary and Quantitative REU (IQ-BIO) summer intern. Not only was I further exposed to the field of data science, I gained experience into how powerful computational tools can be at the intersection of particular fields of research. I joined Dr. Patricia Ordóñez, Dr. Jose L. Agosto Rivera and master student Sofía Meléndez-Cartagena for a project on the development of analytical approaches to cluster and characterize individual differences in biological mechanisms of an eusocial model species, Lassioglassum malachurum (Sweat Bee). Within the large research group, concerned with the study of the highly complex individual behavior of thousands of bees over extended periods of time, our team was responsible for interpretation and analysis of the data. In doing so, I aggregated analytical tools such as R Markdown, git, linux shell and various openly sourced CRAN libraries to create a workflow that clusters and visualizes data obtained from infrared beam breaking monitors as well as achieving a significant result in clustering L. malachurum individuals by relative locomotor activity. Furthermore to better inform my analytical solutions, I went outside my comfort zone and practiced field sampling and animal handling protocol. My work presents an opportunity for future investigations to gain newfound knowledge into associations between age and foraging behavior, sedatives inhibiting activity in populations of insects and potential differences in locomotor activity implying differences in central complexes among other insights. Further work of my research advisors now aim at expanding these tools onto new Apis mellifera gAHB (Honey Bee) datasets, generated from large scale video footage applied to automatic pose, fanning and pollen detection ML models, to answer questions such as if individual bee variation could be beneficial to the colony performance. With the support of my research advisors and program, I took the initiative to communicate the results of my studies to a much larger audience at The Annual Biomedical Research Conference for Minority Students (ABRCMS) that was held in Anaheim, CA in November of 2019.
How has this changed my life?
I made incredible connections with so many people and even got to go to MIT!