About

Learn more about me

Undergraduate Student & Researcher

Yiqian Zhang is a highly skilled and motivated Mathematics and Statistics student at UIUC, with expertise in data analysis, research, and various technical tools, demonstrating strong analytical and problem-solving abilities in diverse projects and research experiences.

  • Birthday: 4 October 2002
  • Phone: 2172001608
  • City: Urbana, IL, USA
  • Age: 21
  • Degree: Bachelor
  • Email: yiqianz5@illinois.edu

Skills

PYTHON 100%
R 100%
SQL 100%
SAS 80%
LaTeX 100%
Git 90%
Tableau 75%

Interests

Microbiome

Compositional Data Analysis

Omics data

Cancer

Zero-Inflated Models

Resume

Check My Resume - overleaf

Education

Bachelor of Applied Mathematics & Statistics

Sep 2021 - May 2025

University of Illinois at Urbana-Champaign

  • GPA: 3.88/4.00
  • 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.

Publication

Zhang, Y., Schluter, J., Zhang, L., Cao, X., Jeng, R. R., Feng, H., Haines, J., & Zhang, L., “Review and Revamp of Compositional Data Transformation: A New Framework Combining Proportion Normalization and Contrast Transformation”, Computational and Structural Biotechnology Journal (CSBJ), (Under review)

Campus Experience

Course Assistant — Statistical Modeling I (STAT 425)

Aug 2024 - Present

University of Illinois at Urbana-Champaign, Statistics Department

  • Graded assignments on Gradescope, ensuring accurate evaluation and timely feedback for students.
  • Proctored in-person exams, maintaining academic integrity during assessments.

Course Assistant — Statistics Programming Methods

Aug 2024 - Present

University of Illinois at Urbana-Champaign, Statistics Department

  • Assisted in virtual exam proctoring and final exam grading for two major exams, ensuring academic integrity and timely assessment.

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

Relevent Projects

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.

Proficiencies

Language

English (Advanced), Mandarin Chinese (Native)

Technical Skills

Python, SQL, R, Linux, DESeq2, Kraken2, QIIME 2, 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

Research Experience

Microbiome Analysis for Alzheimer's Disease Pilot Study

May 2024 - Present

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

  • Project Focus: Investigated the role of the microbiome in Alzheimer's Disease-like phenotypes as part of the Jax.IU.Pitt Microbiome Pilot Study, aiming to identify microbiome-related factors contributing to Late Onset Alzheimer's Disease (LOAD).
  • Methodology: Utilized QIIME 2 for microbiome data analysis, including quality control, taxonomic classification, and diversity analysis. Implemented advanced data transformation techniques to improve differential testing accuracy.
  • Analysis and Visualization: Conducted alpha and beta diversity analyses, creating interactive visualizations to present microbial community structures. Used statistical methods to evaluate changes in diversity metrics and the impact of metadata features.
  • Tutorial Creation: Created a comprehensive tutorial on using QIIME 2 for microbiome analysis. Website: https://yiqianzhang.com/hpc_tutorial/

Reconstruct the Analytical System of Compositional Data Transformations in Microbiome Studies

Nov 2023 - Present

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

  • Biological Data Analysis: Utilizing R and Shiny for statistical analysis of microbiome compositional data. This involves association studies between microbial communities and health outcomes, aiming for biomarker identification.
  • Statistical Methodology Enhancement: Implementing and comparing data transformations, including logit, arcsine, and the novel truncated logit transformation, for beta and Dirichlet distributed data. This effort supports differential testing by improving data accuracy.
  • Microbial Community Analysis: Incorporating Dirichlet regression and GUniFrac analyses to explore microbial community structures and diversity. This work aids in pattern recognition within complex biological data, offering insights into microbial interactions.
  • Evaluation of Data Transformation Performance: Assessing techniques for normalization, variance stabilization, and skewness correction to examine their impact on data interpretability and analysis stability. This includes analyzing the effects of different transformations on microbiome data.

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.

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.

Services

My Services

Lorem Ipsum

Voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi

Sed ut perspiciatis

Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore

Magni Dolores

Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia

Nemo Enim

At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis

Dele cardo

Quis consequatur saepe eligendi voluptatem consequatur dolor consequuntur

Divera don

Modi nostrum vel laborum. Porro fugit error sit minus sapiente sit aspernatur

Portfolio

My Works

  • All
  • Research
  • Card
  • Web

Ukraine Data Analysis

May 2023 - Jul 2023

Web 3

Web

App 2

App

Card 2

Card

Web 2

Web

App 3

App

Card 1

Card

Card 3

Card

Web 3

Web

Contact

Contact Me

My Address

904 W Hill St, Urbana, IL, USA

Social Profiles

Email Me

yiqianz5@illinois.edu

Call Me

+1 217 200 1608