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Education

Bachelor, School of Computing

Mathematics and Computer Science Specialization, 2017-Expected 2022. Queen's University, Kingston, Canada.

Dean's Honor List, Core GPA: 3.95/4.3

Relevant Courses: Computational Data Analysis, Statistical/Machine Learning, Data Structures and Algorithms, Applied Method in Statistics, Image Processing & Computer Vision, Database Design & Management System

Academic Experience

Undergraduate Research Assistant - Department of Mathematics and Statistics, Queen's University

May,2020 - Present

• Research in MAB algorithms

• Implemented UCB, epsilon-greedy, EXP3 and Linear-UCB algorithms using Python

• "Truncated LinUCB for Stochastic Linear Bandits", Yanglei Song and Meng Zhou, submitted to Bernoulli Journal

Undergraduate Teaching Assistant, Queen's University

Sept. 2019 - Dec. 2019, School of Computing

• Teaching Assistant of Computer Science program second level core course.

• Led weekly office hour to 20+ students for homework assistance, languages involving Assembly and C

Sept. 2020 - Present, Department of Mathematics and Statistics

• Teaching Assistant of Mathematics and Statistics Major First Year Calculus and Linear Algebra course.

• Led weekly office hour in a 1 on 1 manner via zoom meeting, helping students to clarify questions and ensure they have a thorough understanding of course material

Professional Experience

Algorithm Engineer, Illuminera Group

Apr. 2021 - Jul.2021

• Collected Image data from Hive database using PySpark, implemented Perceptual hash algorithm to eliminate highly similar images

• Peformed image reshape algorithm for image classification model, used transfer learning to train a VGG16 model and adjust the hyper-parameters

• Labled data and trained a Yolo Object Detection model, acheives 98%+ precison, recall and mAP score

• Deployed image classification model online, increased prediction accuracy by 20% comparing to NLP based classification model, decreased 10% of prediction time

Summer Analyst, Deloitte Digital

May 2019 - Aug. 2019

• Performed prediction and pricing analysis for a Cloud- Platform Architecture Bidding Project

• Compiled historical data using Excel to estimate bidding price of 20 million RMB and predicted a 70% chance of winning the contract by leveraging Python simulation

• Led a team of six members to build a digital transformation solution for client

• Conducted industry competitive landscape research, created a technical architecture diagram for data platform based on the basic knowledge of MongoDB, Spring Cloud and Vue.js

• Resulted in more than 100 million RMB forecasted profit for client using Excel

• Conducted a smart city analysis and leveraged external data to build a machine-learning algorithm in Python and R to classify and evaluate different investment opportunities

Technical Skills

Domains:

Machine Learning, Data Science, Software Engineering

Research Methods:

Quantitative and Qualitative Analysis

Programming Languages:

Python, R, Java, SQL, MATLAB, Haskell, Prolog, SAS, C/C++, HTML, PHP, CSS, Assembly

Frameworks:

Scikit-Learn, Apache Spark, Hadoop, Numpy/Scipy, Pandas, Matplotlib, TensorFlow/Keras, Pytorch

You can also find the PDF version of my resume/CV on this web page.

中文版简历请点击这里(老版，暂未更新)。