letiany Goto Github PK

• ScM Data Science student at Brown University (Sep 2023 - May 2025).
• Bachelor of Engineering in FinTech at the Chinese University of Hong Kong (Sep 2018 - Dec 2022).
• After obtaining my Bachelor's degree, I worked at Natixis APAC Data & Innovation - Centre of Excellence as Data Science Trainee (Mar to July 2023). My first internship was at the data team of the Laboratory for AI-Powered Financial Technologies Limited (HKAIFT) from Mar to Dec 2022.
• I am super interested in the field of machine learning, optimization and applied mathematics!
• I used to be a member and contributor of WISE CUHK to share ideas and spread knowledge with peers at CUHK. And I'm always passionate about and dedicated to data science related projects for social good. Here is my kaggle page and leetcode page. Join this telegram channel for my personal machine learning & data science knowledge sharing if you are interested.
• Some of my favorite artists & writers: Ryuichi Sakamoto, Camus, Rilke, Krishnamurti, Pina, the Beatles. I am into contemporary dance and photograph these years.
• Welcome to reach me at letian_yu[at]brown.edu 📫

"Whoever wants music instead of noise, joy instead of pleasure, soul instead of gold, creative work instead of business, passion instead of foolery, finds no home in this trivial world of ours." -- Hermann Hesse

Tools & Skillsets:

• data1030 Hands on Data Science: Optiver Trading at Close

Full machine learning pipeline (data cleaning, EDA, feature engineering, modelling, evaluation, interpretation) implemented in python. XGBoost and reduced mean method (with LASSO, Ridge, SVM, Random Forest) used.

• csci2470 Deep Learning: Ancient Chinese Machine Translation

We used RNNs, Transformers and unconditional Diffusion Models with pretrained transformers (GPT2) for MT task. While all our course assignments are done using tensorflow, the project is self-implemented using PyTorch. See the devpost page and our final report for details.

3. csci1450 Advanced Intro to Probability for Computing and Data Science:

Assignment codes related to probability (e.g., Bayes Classifier, probability distributions).