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Rejoice Hu

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About Me

Hi! I'm Rejoice Hu, a recent Master's graduate in Information Science with a focus on Machine Learning from Cornell University.


My experience spans ML/Data Science/GenAI roles through working, internship, and research positions at Morgan Stanley, Ecolab, Credibly, and more.


I'm eager to find a full-time role where I can leverage my skills to tackle real-world challenges and deliver meaningful value to users. I am passionate about driving innovation and continuously seeking opportunities to apply my expertise in impactful ways.


Let's connect and explore how I can contribute to your team!

Resume

Skills

Languages

Python

Javascript

SQL

Java

C#

Technologies

Jupyter Notebook

Docker

AWS

Git

Agile

Machine Learning

Statistical Modeling

Deep Learning

Regression

Clustering

Regularization

Packages

Pandas

NumPy

Scikit-Learn

SciPy

Matplotlib

PyTorch

TensorFlow

Experience & Education

  1. Software Engineer (MLOps & Investment Platforms)

    Morgan Stanley

  2. Natural Language Processing (NLP) Intern

    Ecolab

  3. Data Science Consultant

    Credibly

  4. Machine Learning & Cloud Intern (IT Emerging Talent)

    Merck

  5. Artificial Intelligence Research Intern

    Weill Cornell Medical Center

  1. Master's - Information Science (focus in ML)

    Cornell University

    Relevant Coursework: Data Science, Machine Learning, Deep Learning, Reinforcement Learning

  2. Bachelor of Science - Information Science

    Cornell University

    Awards: Summa Cum Laude, Dean’s List, Grace Hopper Scholarship Recipient 2021 & 2022

Projects

BiteWise (Menu Item Recommender)
BiteWise (Menu Item Recommender)

Implemented transfer learning & Aspect-Based Sentiment Analysis with 3 advanced LLM models (DistilBERT, DeBERTa, PyABSA) in Python to provide precise insights beyond standard Yelp ratings

DQN & LSTM for Human-Robot Interaction
DQN & LSTM for Human-Robot Interaction

Developed & optimized RL system with DQN & KNN, SVM, Random Forest, LSTMs, & designed state/action/reward

2048 with Reinforcement Learning
2048 with Reinforcement Learning

Researched and tested whether stochastic Policy Gradient algorithms like PPO can outperform DQN in game 2048

CrochEtsy
CrochEtsy

Created online shopping catalog/ Etsy website for crocheted products with CRUD actions in PHP, JavaScript, HTML / CSS, SQLite

Cure the Cancer!
Cure the Cancer!

Coded a tile map game in Python using OOP, A* Algorithm

Deployed Deep Learning Kidney Segmentation for ADPKD Disease MRI
Deployed Deep Learning Kidney Segmentation for ADPKD Disease MRI

Published in Radiology AI with 17 citations

Leadership & Activities

Vice President of Corporate Relations

Vice President of Corporate Relations

Women in Computing at Cornell (WICC)

Grace Hopper Scholarship Recipient 2021 & 2022

Grace Hopper Scholarship Recipient 2021 & 2022

Cornell University

Graduate Teaching Research Specialist

Graduate Teaching Research Specialist

Cornell University - INFO 2950 Intro to Data Science

AI Fellow

AI Fellow

Headstarter AI

Member

Member

Rewriting the Code (RTC)

Interested? Email me at rhu712 (at) gmail (dot) com! 👏