Hi, I'm Eunice!
I'm a junior (Class of 2026) studying computer science at Massachusetts Institute of Technology.
My interests include software development, artificial intelligence, machine learning, computer vision, and natural language processing, and data analytics.
The leading principles of my life are: collaboration, creativity, proactivity, curiosity, and impact, and I am always looking for new opportunities to grow and learn
Experiences
Burmester & Vogel
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Having joined the team in its early stages, I've been able to contribute to the development of the company's core products and see the direct impact of our work on the maritime industry. I've learned a lot about developing industry-grade software, working in a team, and the importance of data-driven decision-making. I love onboarding new interns and helping them learn the ropes because it reminds me of how lost I was when I first started and how much I've grown in the past year.
- Digitizing and classifying 2k+ unstructured handwritten documents using Optical Character Recognition (OCR) and Natural Language Processing (NLP) to analyze numerical/semantic differences and merge documents
- Developing the backend of a patent-pending, interactive visualization tool for the maritime shipping industry to create audit reports in pdf and web formats
- Creating predictive models utilizing Pytorch, Tensorflow, sci-kit, and numpy to forecast trends in cargo ship loading efficiency
- Implemented custom search querying across 1k+ historical documents and books via elastic search and langgraph
- Spearheading backend unit testing with pytest and Postman tests for Rest API endpoints to integrate testing seamlessly into the CI/CD pipeline
- Accelerated bug tracking by automating health checks and user-encountered errors with Trello for over 15 Azure functions, streamlining Agile workflows and accelerating issue resolution.
- Integrated Azure Cloud for scalable data storage
- the digitalization reduces time spent on manual review by up to 90%, saving users hundreds of hours each month
- the audit reports reduces human error by 75% and streamlines contract disputes, saving companies +$100,000 per document
- the predictive models are available to users in a data dashboard, allowing users to optimize shipping delay costs, allowing potential savings of +$1,000,000 per year
- the unit tests and automated Trello workflow currently achieves 100% API test coverage, reduces bugs pre-deployment by 75%, and accelerates issue resolution by 80%
MIT Computer Science and Artificial Intelligence Lab
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This was my first experience working in a research lab, and I learned a lot about the importance of collaboration and communication in a team as well as the importance of setting your ego aside and not being afraid of asking questions. I was just a freshman at this point so I spent a large part of this experience asking for help. I had never written deployable code or collaborated on the same codebase so it was a lot of adjusting, but I learned a lot and am grateful for the opportunity to contribute to the development of a software that has the potential to revolutionize the way we analyze complex datasets.
- Used Large Language Models (LLMs) and Word2Vec to generate embeddings of complex, unstructured data
- Fine-tuned clustering algorithms to cluster thousands of datapoints by topological proximity based on semantic, numerical, temporal, categorical, and hierarchical relations using Natural Language Processing and Matplotlib
- Used numpy, pandas, and Matlab to refine dimensionality reduction algorithms to transform the relations between datapoints into a 2D or 3D space
- Used Python ML libraries such as HuggingFace, Tensorflow, and Pytorch to build a pipeline that incoporates user annotations on datapoints through incremental learning.
- Utilized time-series analysis and forecasting techniques to identify emerging trends and patterns over time, detecting seasonal/cyclical patterns and correlations within clusters in the datasets.
- Cleaned dozens of datasets to extract voice/face prints and perform audio diarization using PyAnnote
- Contributed to implementing search querying across ontologies, topics, entities, and metadata of datasets using langchain
- Secured over +$2M in funding and currently awaiting patent approval.
- Although it is still in the beta phase, it eliminates the bottlenecks of traditional, manual ontology creation, enabling dynamic, real-time adaptation to evolving knowledge domains
- Automates data annotation and organization, enabling organizations to make data-driven decisions faster and smarter
MIT Department of Urban Studies and Planning
This was my first time independently working on the full-stack development of a platform that is used by real people. I learned a lot about the importance of user experience and how to design a platform that is intuitive and easy to use for all ages. I was able to see the direct impact of our work on the utility companies and the people they serve, and it was a very rewarding experience.
- Spearheaded the full-stack development of a data analysis platform utilizing NextJS, ReactJS, Typescript, and Javascript
- Integrated Matlab and R-scripts performing advanced analysis of geospatial and socioeconomic factors from the US Census Bureau and the American Community Survey
- helped 200+ utility companies make informed policy decisions that will help millions of people across the nation get access to clean water
Some things I've been up to lately...
- I used OpenCV and pytesseract to track hand movements and extract text instructions from the screen, utilized Open AI's whisper module to transcribe voiceovers, and scraped captions and comments to extract full recipes from videos.
- I then integrated custom NLP models such as NER (Named Entity Recognition), CRF (Conditional Random Field), and sequence classification using BERT-based models from HuggingFace to parse the extracted recipes.
- I use MySQL to allow users to come back to saved recipes in their accounts
- For the front-end, I used Typescript through Next.js and React.js and I used Flask for the backend.
- To deploy everything, I used AWS: web server on EC2, database on RDS, ML models stored on S3, and AWS Lambda to call the models
- Due to limited resources, I am currently working on a more efficient way to deploy the computer vision models, but the basic functionalities are deployed.
AI Chatbot for Cleft Patient Healthcare
This was one of my most rewarding experiences learning about end-to-end development with a relatively smaller team. MIT's Code for Good is structured in a way where there are no technical mentors, but we all learn from each other instead. A huge challenge in this project was regarding security since we would be dealing with real patient healthcare data, but with the help of the technicians at the Global Smile Foundation, we were able to find a secure way to store patient data. Seeing the technology we built remove barriers and directly impact real people in such a tangible way reinforced why I do what I do.
- We developed a chatbot app for androids using Kotlin (Java) to provide information about cleft conditions and answer common questions.
- Integrated Apache Spark to process the large dataset of patient information
- Used Postgres to store patient data and allow for querying and used Redis for caching
- Utilized Apache Kafka to facilitate calls/chats between patients and healthcare providers in real-time
- Developed and trained a symptom image recongition model using Pillow/PIL, OpenCV, and Pytorch
- Utilized spacy to train our chatbot in 3 languages (English, Portuguese, and Spanish)
- Integrated the chat into Whatsapp using the Twilio API to allow users to use technology that they are already familiar with
- Many of these patients lived in remote areas with limited access to healthcare, often left with questions after receiving cleft-palate surgery.
- Since a significant portion of our patients are children, who may not be able to verbally express their discomfort or symptoms, our symptom image recognition helps better assess their condition and provide more accurate care
Skills
Languages: Python, JavaScript, TypeScript, Java, Kotlin, R, C, C++, C#, SQL, Matlab
Databases: MySQL, Postgres SQL, NoSQL (MongoDB)
Frameworks/Libraries: NodeJS/Express/Next, React.js, Flask, Django, Angular, Vue, Prisma
Machine Learning & Data Science: PyTorch, Tensorflow, HuggingFace, OCR (Optical Character Recognition), NLP (Natural Language Processing, LLMs, spacy), computer vision (OpenCV, Pillow/PIL), langchain/langgraph, sci-kit, matplotlib, pandas, numpy, Apache Spark
Software Development Practices/Tools: Git version control, Docker, Azure, AWS, REST APIs, Apache Spark, Redis, Full-stack development (front-end + back-end), end-to-end development, Android mobile development, CI/CD, pytest (unit testing), OOP (Object Oriented Programming), Agile methodology (Trello, Jira)
About Me
I'm currently a junior pursuing a Bachelor of Science (B.S.) in Computer Science and Engineering and concentrating in Writing at the Massachusetts Institute of Technology (MIT). I was born in California, raised in Vegas, and am now based in Boston. I'm naturally curious and am super excited to learn new skills to solve complex problems.
Things I'm learning right now: iOS mobile development, building a paper trading bot, sewing
Things I want to learn more about: Go, Three.js, Springboot, woodworking, metalworking, embedded engineering, literature, and golfing
Activities
I'm on the MIT varsity fencing team and have been fencing epee since high school
I'm a lab assistant for MIT's 6.1900 (Intro to Low-Level Programming in C and Assembly) course
I'm a consultant for MIT's Code For Good club
I've been on the exec board for MIT's Asian American Association since freshman year and currently serve as treasurer.
I'm a web developer for MIT's Educational Studies Program
I love trying out new recipes, restaurants, and cafes
Current Favorites
Books: Tuesdays with Morrie by Mitch Albom, The Idiot by Elif Batuman, and The Stranger by Albert Camus
Shows: Arcane, Culinary Class Wars, Cunk on Earth, and Brooklyn Nine-Nine
Movies: Interstellar, Hereditary, Parasite
Artists: Mitski, Beabadoobee, Big Thief, and Laufey