Huangrui Chu

Master of Science in Biostatistics Data Science Track

August 2022 - Present

Relevant Coursework

• Data Science Software Systems
• Topics in Natural Language Processing
• AI Foundation Models
• Big Data & Customer Analytics
• Cost-Effectiveness Analysis and Decision-Making
• Machine Learning with Biomedical Data
• Longitudinal and Multilevel Data Analysis
• Clinical Database Management Systems and Ontologies
• Management of Software Development

Bachelor of Science in Interdisciplinary Studies

Augest 2018 - May 2022

Relevant Coursework

• Speech Recoginition
• Computer Vision
• Data Acquisition and Visualization
• Artificial Intelligence
• Interdisciplinary Data Analysis
• Numerical Analysis and Optimize
• Probability and Random Process

Bachelor of Science in Data Science

Augest 2018 - May 2022

Relevant Coursework

• Algorithms and Databases
• Statistical Machine Learning
• Deep Learning
• Principle of Machine Learning

Claudius LI

January 2024 - Present

Data Scientist

• Utilized LLM to help Law School professors and students improve their law articles by estimating article influence with a Transformer model to predict the reference number of law articles and reduced the MSE by 42%
• Conducted data cleaning, data validation, and data visualization in Tableau and developed ETL pipeline for ingesting the top 200 law journals’ 50,000+ legal documents into database for law firms and in-house legal counsels
• Built a Bert based classification model with HuggingFace platform in Python to classify the topics of the article and implemented a Chat Bot with LangChain to allow users to chat with the law article interested in via OpenAI API

Yale University Student Accessibility Services

September 2023 - May 2024

Data Analyst

• Streamlined routine email responses by applying prompt tuning to Large Language Models, achieving an 80% reduction in response time
• Developed robust matrix and filter system to process Exam Accommodation datasets across multiple data sources
• Led team of 43 to help proctoring exams as request by Yale Professors by collecting exam information and coordinating proctors and students

Drexel University The DANNER Lab

May 2023 - Augest 2023

Graduate Researcher

• Implemented central pattern generators using neural networks and simulated physics engines for robotic coordination and muscle mechanics experimentation
• Applied reinforcement learning and conduct simulations by building virtual environments, leading to a 35% improvement in robot walking stability and performance robust strategic model training and simulation analysis
• Collaborated with Neural Scientists to develop and conduct neural network models, focusing on understanding spiral functions and neuromechanical control in locomotion

Yale University

January 2023 - May 2023

Graduate Researcher

• Developed and implemented a Transformer model in Python to extract high-order relationships among brain regions from fMRI data to provide insights into neurological disorders demonstrating a performance boost of 11.2%
• Utilized PyTorch to train and compare the performance of a transformer-based encoder model and an MLP model in reconstructing functional connectivity features of the brain and conducted features importance analysis
• Adapted linear regression to evaluate the performance of models (KNN, BrainGNN, HYBRID, etc.) for predicting the cognitive ability of the patients; summarized research results and paper submitted to ICML 2024

KONE Elevators Co., Ltd.

January 2021 - September 2021

Data Scientist

• Trained a multimodal dynamic neural network in PyTorch to detect elevator emergency call with a precise prediction of 98% accuracy and reduced real SOS message delivery time from 5s to 2s
• Developed an advanced multistage Keyword Spotting system, attaining a high recall rate of 0.87 in accurately identifying real calls for emergencies
• Led a team of 12 to annotate and check 4168 collected raw audio-visual clips to establish a multimodal dataset.
• Co-authored and presented two papers at the 2021 International Conference on Multi-modal Interaction [1, 2]

Duke Kunshan University SMIIP Lab

March 2021 - September 2022

Undergraduate Researcher

• Developed a novel program that extracts and reconstructs facial data with a 3D point cloud using the 2D color image and depth information by employing the Iterative Closest Point algorithm.
• Calibrated multiple cameras of different angles using OpenCV in Python
• Trained and finetuned CNN models such as RetinaFace to do face detection and alignment in PyTorch
• Trained multitunal multilayer perceptron model classifier to enhance the emotion recognition accuracy by 5.8%

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