Yiqian Zhang

Bachelor of Applied Mathematics & Statistics

Sep 2021 - May 2025

University of Illinois at Urbana-Champaign

• GPA: 3.86/4.00
• Selected Coursework: Abstract Linear Algebra, Ordinary/Partial Differential Equations, Statistical Modeling, Statistics Programming Methods, Fundamental Mathematics, Real Analysis, Design of Experiments, Applied Complex Variables, Statistical Learning, Applied Bayesian Analysis.
• Honors & Awards: Dean’s list in Spring 2022 and Spring 2023, IGL Hoover Mathematical Scholar Award.

Course Assistant — College Algebra

Aug 2023 - Present

University of Illinois at Urbana-Champaign, Mathematics Department

• Conducted group discussions and office hours for 56 students, covering topics like factoring, equations, functions, and polynomials.
• Assisted in grading, problem-solving, and course optimization.

Tutor — Calculus & Calculus 1

Aug 2023 - Dec 2023

University of Illinois at Urbana-Champaign, Mathematics Department

• Provided tutoring in Calculus and Analytic Geometry to over 50 students weekly.
• Enhanced students’ understanding and performance in assignments, quizzes, and exams

Language

English (Advanced), Mandarin Chinese (Native)

Technical Skills

Python, SQL, R, Git, LaTeX, JAVA, Tableau, MongoDB, C++, Docker, Microsoft Office

Professional Competence

Machine Learning, Data Mining, Data Visualization, Linear Algebra and Calculus, Probability and Statistics, Data Management, Web Scraping and APIs, Geographic Information Systems, Database Management

Abilities

Strong leadership, teamwork, and problem-solving skills; Outstanding critical thinking and analytic skills; Excellent communication, negotiation, and presentation skills

Computational Modeling of MDD and Bipolar Disorder

Jan 2024 - Present

Research Assistant Under the Guidance of Dr.Brandon Brown(Carle Foundation Hospital) and Professor Xinzhu Yu

• Create computational models that mimic mood fluctuations, with a specific emphasis on simulating Major Depressive Disorder (MDD) and Bipolar Disorder (BD).
• Utilize Markov chain and Hidden Markov Models to portray mood states, encompassing normal, depressive, and manic phases, along with transitions influenced by a combination of internal and external factors.
• Conduct in-depth statistical examination to assess the prevalence and trends of both MDD and BD, mirroring actual epidemiological data.

Network Dynamics Analysis through Preferential Attachment Models

Jan 2024 - Present

Research Assistant Under the Guidance of Professor Yuexi Wang and Professor Yuguo Chen

• Implemented simulations in Python, leveraging libraries such as NetworkX for network generation and Matplotlib for visualization.
• Applied Bayesian inference and Markov Chain Monte Carlo (MCMC) methods to estimate model parameters, aligning simulations with observed network characteristics.
• Analyzed network formation processes by comparing simulated degree distributions with empirical data, utilizing statistical methods to validate model accuracy.

Analysis of Proportion Data Transformations in Microbiome

Nov 2023 - Present

Research Assistant Under the Guidance of Professor Liangliang Zhang(CWRU)

• Participate in a project on statistical analysis of proportion data, utilizing R for simulation and analysis, and Shiny for interactive data visualization.
• Evaluated and synthesized sophisticated statistical models to assess the effectiveness of various data transformations, such as logit and arcsine, on beta and logit-normal distributions.
• Conducted comprehensive analyses to evaluate normalization, variance stabilization, and skewness of data pre- and post-transformation.
• Documented methodologies and findings, contributing valuable insights to the field of statistical modeling and enhancing data analysis approaches.

Rail Transportation and Engineering Center (RailTEC), Rail Safety and Risk Group

Oct 2023 - Present

Undergraduate Research Assistant Under the Guidance of Professor Christopher P. L. Barkan

• Engaged in comprehensive railway transportation safety projects, applying engineering, analytical, and operational principles to real-world challenges.
• Developed and implemented a Python script to automate the weekly Tank Car Report, significantly enhancing team efficiency by 96%.
• Authored and contributed to detailed reports, presenting findings and recommendations to enhance railway safety protocols and procedures.
• Utilized Python for data management and analysis. Successfully processed the ’CarList2022’ dataset, a comprehensive 25GB+ collection of vehicle information. Integrated this with the ’FRA’ dataset, which details car accidents. This involved meticulous data matching and merging, with a focus on correlating car accidents with vehicle length, ensuring data consistency and accuracy for in-depth research analysis.
• Collaborated with a multidisciplinary team of engineers and researchers, continuously expanding knowledge in transportation risk analysis and railway engineering.

Ukraine Data Analysis - Link

May 2023 - Jul 2023

Undergraduate Research Assistant Under the Guidance of Professor Richard B. Sowers

• Created and executed a comprehensive data analysis pipeline using Jupyter Notebooks to analyze and visualize the Armed Conflict Location and Event Data Project (ACLED) in Ukraine using Python, pandas, folium, and MongoDB.
• Constructed choropleth maps to compare differences in military engagements across various cities and time frames, utilizing Open StreetMap API for data extraction.
• Employed advanced data visualization techniques such as heatmaps, word frequency distributions, and time series animations to provide dynamic insights into the conflict data.
• Stored and managed over 10 GB of data in MongoDB, achieving fast and efficient queries and updates.
• Documented all processes and methodologies in detailed notebooks and an API guide, enhancing the accessibility and usability of the data analysis pipeline for future researchers and stakeholders.

UIUC Student Distribution Analysis - Link

Mar 2023 - May 2023

• Developed an R Shiny application to visualize UIUC student distribution, enabling dynamic data exploration.
• Integrated various data visualizations like bar and pie charts, and a map feature to illustrate student distribution across the U.S.
• Provided detailed data tables for a comprehensive state-and-year-specific student breakdown.

Advanced SQL: MySQL Data Analysis & Business Intelligence Project

Mar 2022 - Jul 2022

• Analyzed e-commerce website traffic using advanced SQL techniques, identifying key traffic sources and user behavior patterns
• Developed and implemented marketing strategies that improved conversion rates by 15% and reduced bounce rates by 10%.
• Performed statistical tests to optimize budget allocation, resulting in a 20% efficiency increase.

Covid-19 Data Visualization by Tableau

Oct 2021 - May 2022

• Utilized Tableau to create dynamic dashboards visualizing global COVID-19 trends, including case and death counts.
• Analyzed daily new cases to identify patterns and regions of concern.
• Designed intuitive and informative visuals for enhanced data interpretation and user experience.