New Haven, Connecticut, United States
Ex-PhD student in Computer Science largely interested in multilingual NLP (natural language processing) and computational social science with extending interests as of late into medical data, S&P (security & privacy), and user research. Six publications to date in medical machine learning ethics, distributed systems, security, NLP. Aside from working with languages as a computer scientist, I like to learn many for fun with a desire of incorporating them into teams, projects, and secondary roles or volunteering, such as in my emergency care roles and computer science & phonics teaching endeavors. Current work includes collaboration with neuroscience faculty at Brown in the theme of analyzing memory structures and affordances in my natural language processing lab in the computer science department at Brown, as well as image processing for histological data as a researcher in Brian Hafler and Marcello DiStasio's group within the Yale School of Medicine. I have also recently contributed to a cancer care platform as a senior NLP engineer after consulting for Kaiser Permanente for around a year prior in MLOps Python development on behalf of predictive modeling. My blossoming interests and endeavors surrounding healthcare technology and practice have largely centered around EMS systems, having recently trained in my first Level 1 trauma center/adult ER with my EMT-B as a scribe-turned-night-tech, and I currently work nights in a second ER & volunteer with two fire companies as a complement to the medical angles of my daytime research endeavors and product designs. I am very interested in EMS data science and QI, though at the intersection of passions surrounding user research, UI/UX, and grounded usability, I hope to study & develop first-responder tech integration in an eventual return to PhD work as an aspiring MD-PhD candidate after more computational exposure -- per my expertise to date -- to such research and teams in the interim. Prior experience in economics (FDIC), banking fintech (Goldman Sachs, J.P. Morgan), defense (US Army Research Lab), healthcare (Rhode Island Hospital, ScribeAmerica, UChicago ER, Northwestern Ophthalmology, Yale ER, Yale School of Medicine, OncoHealth, Kaiser Permanente, Resilience, Rush & St. Joseph's Hospital, North Branford & Allingtown Fire), social media (Twitter), law & legal tech (Relativity), & education (ML instructor for Inspirit AI, research mentor for Summer STEM Institute and Lumière, various grad & undergrad teaching assistantships, volunteering with LaAmistad & New Haven Reads), with ongoing interests in each.
Training image processing models for satellite recognition on behalf of space intelligence in the national security solutions (NSS) division of KBR as a principal MLOps and data engineer; building a data lineage pipeline for ingestion, storage, and processing of images and human-sourced annotation metadata on behalf of multiple sensors (factoring in incoming or deprecated sensors in coordination with the sensors/hardware teams) to further improve and specialize said models. Primarily utilizing Python, PyTorch/Torch, JSON and .fits data formatting, Docker containerization, GitLab, and the AWS suite to facilitate on-prem GPU remote model training prior to Kubernetes facilitation of testing and deployment in coordination with the infrastructure team.
As an emergency room technician, my role is to support the nurses and doctors in providing high-quality care to patients in the emergency department. I am responsible for a variety of tasks, including taking vital signs, collecting blood and urine samples, performing EKGs, and assisting with procedures. In addition to these clinical duties, I am also responsible for ensuring that the emergency department is properly stocked and organized. I help to maintain medical equipment and supplies, restock rooms, and clean and sanitize equipment after use. One of the most rewarding aspects of my job is the opportunity to provide emotional support to patients and their families during times of crisis. I am often one of the first healthcare professionals to interact with patients, and I take pride in making them feel comfortable and reassured during what can be a stressful and overwhelming experience. Overall, my role as an emergency room technician requires a combination of clinical skills, organization, and compassion. It is a challenging and fast-paced environment, but I find it incredibly rewarding to be able to make a difference in the lives of patients and their families during times of need.
Instructor for 3 courses: AI for Healthcare (current), Introductory AI, Advanced Methods in Machine Learning. Leading 2.5-hour classes split into lecture (1h) and coding (1.5h), with each course cumulating in one of a variety of topical projects for student development & presentation.
As a postgraduate computational researcher in spatial transcriptomics for a neuroimmunology lab at Yale, my role is to develop and implement computational methods for analyzing spatial transcriptomic data in the context of neuroimmunology and ophthalmology. My work involves designing and implementing computational pipelines to process large volumes of spatial transcriptomic data, using tools like Python, R, and MATLAB to analyze gene expression patterns and identify spatially distinct cell populations within tissue samples. I also collaborate closely with experimentalists who work to design experiments that generate high-quality spatial transcriptomic data.and who utilize my transcriptomics tools and pipelines for downstream analysis.
As a senior NLP engineer in for an oncology platform, I have extensive experience using Databricks, Spark, Python, and other similar tools. My work involves developing and implementing NLP models to analyze large volumes of healthcare data, helping to identify patterns and insights that can be used to improve patient outcomes and reduce costs. With my expertise in machine learning algorithms and programming languages like Python, I have been able to design and implement innovative solutions that have significantly improved the efficiency and accuracy of our data analysis. I am also experienced in working with large-scale datasets and cloud computing platforms like Amazon Web Services (AWS) and Microsoft Azure, which have enabled me to scale our data processing capabilities and reduce the time required for analysis. Overall, my job experience has allowed me to develop a deep understanding of NLP and data analytics, making me a valuable asset to any organization looking to leverage these technologies to improve healthcare outcomes and patient care. As for not having been at OncoHealth for too long of a time, the company in May 2023 decided to pursue a significant overhaul in product offerings, eliminating the entire Life Sciences division on behalf of focusing on a singular product, ultimately affecting myself, managers, and many others under the data science, NLP, clinical, and other roles within Life Sciences.