About Me
Work
Data ScientistSchool
Harvard UniversityHobbies
Art and Gaming👋 I'm Amelia, a recent Master's graduate in Data Science and currently working as an AI Engineer. Feel free to reach out to me through email!
Chat with me!Work & Extracurriculars
Data Science
Internship
Doctor Anywhere
Data Science Internship
Doctor Anywhere
May 2023 - Aug 2023
During the summer of 2023, I interned at Doctor Anywhere, a digital healthcare company, where I developed a machine learning algorithm for TPA/B2B claim processing.
Using OCR, key-value parsing, table parsing, and entity recognition, the algorithm enhanced claim efficiency and was seamlessly integrated into
the company's system.
In addition to the primary algorithm, I built utility tools for dataset benchmarking and model prototyping, boosting the accuracy from 66% to 84%.
I also ventured into Large Language Models (LLMs) in healthcare, creating a prototype to aid policyholders with insurance inquiries.
I'm grateful for this enriching experience, which sharpened my technical skills and provided deep insights into technology deployment in healthcare.
The guidance from my team and mentors was invaluable, significantly shaping my professional development.
Graduate Teaching
Fellow
Harvard University
Graduate Teaching Fellow
Harvard University
Aug 2023 - Present
As I embarked on my Fall 2023 semester, I found myself at the heart of nurturing future data scientists. For the CS209a: Intoduction to
Data Science course at Harvard University, my role involved facilitating weekly office hours, offering crucial guidance and support in
Data Science. These sessions have become a vibrant hub for learning, where students from diverse backgrounds share their insights and
challenges, enriching our collective understanding.
Moreover, mentoring students in their data science projects has been the most rewarding experience. Guiding them from conceptualization to
execution, I've seen them develop practical skills and a strong research aptitude. Their progress has been a testament to the power of
effective mentorship.
This semester has been a journey of mutual growth - a reaffirmation of the crucial role mentorship plays in the realm of data science. I look
forward to the continued evolution of my students and the invaluable lessons they teach me along the way.
Research
Assistant
Harvard LIT Lab
Research Assistant
Harvard LIT Lab
Sep 2022 - Present
In my first semester at Harvard, I joined the Harvard LIT Lab to work on a groundbreaking project. Our aim was to detect stress in coding environments
using non-survey methods like analyzing micro-gestures, facial expressions, and coding patterns.
We focused on physical cues, using meticulously cleaned and preprocessed 17-point joint data from 3D Kinect captures and facial expressions
from videos. This approach helped us observe stress signs beyond conventional surveys. Additionally, I converted Jupyter Notebook logs into
Abstract Syntax Trees (ASTs) to understand stress through changes in coding behavior.
This project was a unique blend of data science, education, and psychology, offering new insights into the human aspect of coding. It was an invaluable
experience, shaping my understanding of technology's interaction with human emotions.
Undergraduate
Student Instructor
UC Berkeley
Undergraduate Student Instructor
University of California, Berkeley
May 2021 - May 2022
In my role as an Undergraduate Student Instructor at UC Berkeley, I had the privilege of directly teaching the Data 8: Foundations of Data Science
course. My audience was a group of 120 students enrolled in the Data Scholars program, each eager to dive into the world of data science and statistics.
Each week, I created and delivered lectures, complementing them with tailored worksheets to reinforce key concepts in data science and statistics.
This approach not only facilitated learning but also encouraged active engagement among students.
One of the most rewarding achievements during my tenure was successfully scaling the program. In just one semester, we doubled the number of participants
from 60 to 120 students, a testament to the program's growing popularity and effectiveness.
This experience was incredibly fulfilling, allowing me to contribute to shaping the next generation of data scientists. It underscored the
importance of clear communication, effective teaching methodologies, and the adaptability required to scale educational programs successfully.
Recent Projects
Skills
Programming Languages
Python
AdvancedC++
AdvancedSQL
IntermediateMATLAB
BeginnerR
IntermediateHTML/CSS
IntermediateJavascript (d3.js)
IntermediateMachine Learning and Data Analytics
A/B Testing
AdvancedRandom Forest
AdvancedCNN
AdvancedKNN
AdvancedLarge Language Models
AdvancedNLP: ELMo/BERT/GPT
IntermediateDevOps and MLOps
Docker
AdvancedKubernetes
IntermediateAnsible
IntermediateDVC
IntermediateGCP
AdvancedVertex AI
AdvancedFastAPI
IntermediateData Science Tools and Frameworks
Git
AdvancedGitHub
AdvancedTensorFlow
AdvancedMatplotlib
AdvancedPandas
AdvancedExcel
IntermediateSeaborn
IntermediateTableau
IntermediatePyTorch
AdvancedKeras
Intermediatescikit-learn
AdvancedGEE
IntermediateEducation
Harvard University
M.S. Data Science
Graduated: May 2024
RELEVANT COURSEWORK
-
Data Science 1: Introduction to Data Science [AC 209a]
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Data Science 2: Advanced Topics in Data Science [AC 209b]
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Systems Development for Computational Science [AC 207]
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Visualization [CS 171]
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Generalized Linear Models [STAT 149]
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Critical Thinking in Data Science [AC 221]
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Advanced Practical Data Science, MLOps [AC 215]
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Computational Science and Engineering Capstone Project [AC 297r]
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The Dark Side of Big Data [ENG 198BD]
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Computer Graphics [CS 175]
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Classics of Computer Science [CS 191]
University of California, Berkeley
B.A. Data Science [Domain Emphasis: Business and Industrial Analytics]
Graduated: May 2022
RELEVANT COURSEWORK
Data Science
-
Foundations of Data Science [Data 8]
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Principals and Techniques of Data Science [Data 100]
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Data Structures [CS 61B]
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Probability for Data Science [STAT 140]
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Computational Structures in Data Science [CS 88]
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Human Context and Ethics of Data [DATA 104]
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Data Inference and Decisions [DATA 102]
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Data Mining and Analytics [DATA 144]
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Natural Language Processing [INFO 159]
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Professional Preparation: Teaching of Probability and Statistics [STAT 375]
Business and Industrial Analytics
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Economic Models [DATA 88]
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Data and Decisions [UGBA 88]
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Data Science for Smart Cities [CIVENG 88]
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Industrial and Commercial Data Systems [INDENG 115]
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Logistics Network Design and Supply Chain Management [INDENG 153]