I work at the Massive Data Institute (MDI) within Georgetown's McCourt School of Public Policy. In addition to highly-decorated academics in scientific fields, MDI hosts postdoctoral fellows, graduate and undergraduate students as both scholars and staff. It is a great privilege to learn from this community of passionate social and ethical thinkers.My initial primary role is in support of Dr. Lisa Singh's portion of Dr. Carole Roan Gresenz's recent NIH R01 grant—"Using Digital Signals from Credit Data for Early Detection of Alzheimer's Disease and Related Dementias"—which is one of three central aims for the project: approaching diagnostic prediction of ADRD with machine learning. Alongside Lisa and one of her 5th year doctorate students, I will be exploring the feasibility of predictive tools with significant focus dedicated to algorithmic fairness.

▪ Designed and maintained optimization algorithm logic for productionized APIs using spatiotemporal data for micromobility.▪ Developed encapsulated classes, functions, and unit tests while cutting and reviewing tickets across infrastructure.▪ Optimized SQL insertions to decrease application runtime by over 400% compared to Django ORM (PostgreSQL).▪ Implemented a budget utilization threshold with data science team and suggested a ‘hot start’, reducing segment runtime by 10%.▪ Completed a Jira epic individually to upgrade 67 packages with Conda.

With the support of my manager and project leaders, I have been extending my networking and software engineering skillset to leverage data science. My section of a larger project's development team ~(4/12 people) is implementing machine learning models based in time series analysis. We focus on experimenting and prototyping and I am grateful to learn from the others and contribute to our success. One challenge is scripting the more complex creation of recurrent neural networks (LSTMs). I am integrating software from several colleagues; we are using Bayesian optimization to tune model hyper-parameter selection, and it is striving for end-to-end modularity in terms of input size. Mainly our goal is to leverage results and produce visualizations to validate adapting QoS for potentially interesting network topologies.I have also gained exposure to natural language processing (NLP) and its intersection with data science as part of this effort to acquire utile skills. Through the impressive network of professionals at MITRE, I was able to join the Q1 of a social science research effort led by academics in social and industrial psychology, as well as computational law. I initiated a code repository for normalizing and parsing state level policy text related to food waste. On the technical side, I experimented with molecular biology alignment algorithms (Smith-Waterman, affine gap) to find longest common subsequences (to find legal text reuse). I tested several state of the art packages including SpaCy and SciKit, many custom developer approaches, and tweaked two major implementations from our literature review.The statistical and behavioral portion of that project and the ongoing NLP development will, in my opinion, yield interesting results. I am in the process of transitioning from this project to pursue an individual opportunity. I was chosen for a one year early career research program with my proposal to explore optimizations for federal aquaculture regulation.

I implement research methods on an Agile software development team. We use GitLab and have a containerized unit testing pipeline for both front end and back end. I work primarily with the latter and python3 is the primary programming language. I've gained exposure to deploying a full stack application in varied computing environments including physical and remote virtualization, with a flexibility for Linux distributions.Before joining this team but within my role as a networking security engineer, I contributed to several interesting projects. One of my teammates and I were asked to assist for a small six week endeavor of several senior academics, which led to a crash course in software astrodynamics, Docker Swarm and Prometheus and Grafana. This was a good refresher of the satellite event planning I worked on as an intern. I also contributed to a long-term project based on programming at the Data Link layer of the OSI model. With a different teammate over two quarters, I deployed a physical cluster of networking servers and thoroughly tested multiple operating systems and cable adaptors and formations. During a warm Boston summer the cold blast of AC and loud fans of a large server room create an almost cozy learning environment, up until they become motivating to finish!

I taught for one hour weekly of a Fall semester English class to the incoming cohort of writing center consultants. I was also TA for the English professor, who was the Director of the Writing Center, and supported the other two hours of rotating one-on-one and group discussions. I enjoyed the challenge of coming up with lesson plans for my peers, and benefitted from trying to echo the empathetic and ethical approach of our teacher.

Nominated and hired as consultant for Georgetown University's Writing Center. I work 5-10 hours a week and have been exposed to a wide variety of both clients and assignments, including high schoolers from D.C.'s 7th ward with the SEED foundation, graduate students and their theses, Ukranian, Chinese, and French second language learners, and frantic freshman with theology essays. A humbling role.

This experience taught me the importance of being flexible, as I grappled with new arenas including an embedded security and watermarking competition and software-defined radio. I picked up Python and bash scripting to implement an asynchronous mobility framework using multiprocessing and multithreading. I was exposed to a breadth of topics—radio wave propagation pathloss and fading models, extended mobile ad-hoc networking topologies, Common Open Research Emulator (CORE)—but also dove deep into emulating an emerging network technology and protecting a small IOT-like device.

Worked primarily as a translator for Loyal Solutions, a quality management software company in Buenos Aires, Argentina. My assignments were highly varied, including powerpoint presentations in Spanish on international competitors, writing and recording software tutorial videos, and translating and correcting business and web materials.

Hired as an intern for the business section during the summer. Asked to return during the holiday season, where I became the youngest person in the paper's history to have a front-page byline. Over the course of 16 weeks, I published solo articles across the paper, including headline CEO profiles, tragedy and hate crime coverage for Breaking, and social media reporting.