JIAZHANG, YU (Kevin)

**** *** **** **, *** ****, Houston, Texas, United States. 77030

Cell: +1-858-***-**** Email: ad1sgl@r.postjobfree.com

EDUCATION

Rice University Aug 2022 – Dec 2023 (Expected)

Master of Data Science

University of Michigan Ann Arbor Sept 2019 - May 2022 Major: B.S. Data Science, Minor: Math

Awards: University Honors (Apr 2021 & Dec 2019)

Northeastern University Sept 2018 - Jun 2019

Major: Mathematics/Business Admin

Cumulative GPA: 3.8/4.0, Major GPA: 3.89/4.0

Awards: Dean’s List (Fall 2018 & Spring 2019)

WORK EXPERIENCE

Lead Teaching assistant for Graduate Design Analysis of Algorithm Aug 2023 - Dec 2023 (Expected)

Held office hours and responded to students’ questions about course materials and logistics.

Commuted with the professor about homework assignments and distributed work to other teaching assistants.

Hosted weekly meetings to synchronize workflow progress with other teaching assistants. INTERNSHIP

Software Developer Engineer Intern, Shanghai Intuition co. ltd Jun 2023 – Aug 2023

Programmed an RPA (Robotic Process Automation) to retrieve more than 2,000 national laws and 620,000 judgement documents to train a large language model designed for legislative inquiry and case analysis and optimized its RAM usage by 60%.

Established connections between stored documents and a Postgres database to allow quick updates.

Built a monitoring system to retrieve the import/export merchandise information from the official customs websites for monthly updates on any given inventories.

Developed a report retrieval program to collect seasonal and annual financial reports of the listed companies for further document parsing.

RESEARCH EXPERIENCE

Capstone Project, Rice University Jan 2023 – Apr 2023 (Expected) Identifying Motor Vehicle Collision Prevention Opportunities in the Houston Fire Department Group Member, Mentored by Dr. Su Chen, PhD Akshat Dave This project aims at identifying HFD motor vehicle collision out of all emergency runs by predicting binary outcomes based on various features: fatigue factors, driver experiences and etc., using logistic regression and isolation forest.

Constructed a dataset of 1,048,576 records with 41 columns by merging six datasets. Each row contains a work shift of an individual on a specific date from 01/01/2010 to 12/31/2022.

Trained a logistic regression model and other outlier detection model, including Isolation Forest, Local Outlier Factor and Minimum Covariance Determinant, on the heavily imbalanced dataset: 0.26% emergency runs have collisions.

Applied DBSCAN (Density-based spatial clustering with the application of noise) to find similarities in the distributions of civilian collisions and the HFD collisions. SKILLS

Statistical Analysis Software: Python (Selenium, Matplotlib, Numpy, PyTorch), R Programming: Java, C++. PowerShell, Linux

Database: MySQL, MongoDB, PySpark, AWS

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