Yilin Xia

Hello, I’m Yilin Xia

I am a Ph.D. student advised by Dr. Bertram Ludäscher and Dr. Matthew Turk in the School of Information Sciences at the University of Illinois at Urbana-Champaign. I also work closely with Dr. Shawn Bowers , Dr. Evgeny Skvortsov and ArviZ Team. Additionally, my research benefits from collaborations with researchers & engineers at Microsoft Research, the CYENS Centre of Excellence and Open Source Communities.

My research focuses onDeclarative Data Science, where I apply techniques from Declarative Programming Languages, Data Visualization, and Databases to enhance user interaction with data, making it more accessible and explainable. I regularly incorporate Human-Computer Interaction methods to evaluate the tools developed in my research projects. My current areas of interest include:

Declarative AI: Logical Reasoning and Explanation

Declarative Query Language: Query Explanation and Evaluation

Declarative Visualization: Visualization Formalization and Construction

In my spare time, I'm deeply interested in the arts, like painting and photography. I also enjoy sports such as badminton, hiking, skiing and running.

Name Pronunciation

Ph.D. Student @UIUC

Featured Publications

COMMA'24

Layered Visualization of Argumentation Frameworks

Yilin Xia, Daphne Odekerken, Shawn Bowers, Bertram Ludäscher

EuroVis'24

Designing Born-Accessible Courses in Data Science and Visualization: Challenges and Opportunities of a Remote Curriculum Taught by Blind Instructors to Blind Students

Joo Young Seo, Sile O'Modhrain, Yilin Xia, Sanchita Kamath, Bongshin Lee, James M Coughlan

EDBT'24

Logica: Declarative Data Science for Mere Mortals

Evgeny Skvortsov, Yilin Xia, Bertram Ludäscher

CHI'24

MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation

JooYoung Seo*, Yilin Xia*, Bongshin Lee, Sean McCurry, Yu Jun Yam

IDCC'24

Reconciling Conflicting Data Curation Actions: Transparency Through Argumentation

Yilin Xia, Shawn Bowers, Lan Li, Bertram Ludäscher

CHI'23

CrowdIDEA: Blending Crowd Intelligence and Data Analytics to Empower Causal Reasoning

Chi-Hsien (Eric) Yen, Haocong Cheng, Yilin Xia, Yun Huang

Latest News

Sept, 2024 We got two papers on Logica accepted by ICLP workshops Datalog2.0 & PEG

July, 2024 Attended SciPy'24 and presented two posters on JupyterLab NodeEditor (JLNE) and Arviz Dashboard

June, 2024 Our demo paper "Layered Visualization of Argumentation Frameworks" accepted for COMMA 2024

Feb, 2024 Our demo paper "Logica: Declarative Data Science for Mere Mortals" accepted for EDBT 2024

Jan, 2024 Our paper "MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation" has been accepted for CHI 2024

Dec, 2023 Our manuscript "Reconciling Conflicting Data Curation Actions: Transparency Through Argumentation" has been accepted for IDCC 2024

Nov, 2023 Received $10,000 funding from NumFOCUS to work on project "Dashboard-assisted exploratory analysis of Bayesian models"

Nov, 2023 Our work "Games, Queries, and Argumentation Frameworks: Time for a Family Reunion!" has been accepted to AI^3 at AIxIA

Oct, 2023 Awarded $1,000 Conference Travel Grant from United States Research Software Engineer Association(US-RSE)

Featured Projects

This is a graph from the paper where it indicates how similar the argumentation and game theory are

Logica

Query Language; Logic Programming; Reasoning

Logica is a logic programming language that compiles to SQL. It runs on Google BigQuery, PostgreSQL and SQLite.

Code Demo Paper

gamearg

Rule-based Reasoning; Explanation; Argumentation

By using logic programming and data visualization, gamearg help explain the status of argument and reasoning process.

Code

MAIDR

Visualization Construction; Accessibility

MAIDR offers non-visual access to statistical visualizations for users with visual impairments. It supports interaction through braille, text, sonification, and review (BTS + R).

Code Demo Paper

Jupyterlab NodeEditor

End-user Programming; Scientific Computing

A graphical user interface using a dataflow-driven visual programming language to enhance data science tasks. It provides domain experts with intuitive tools for complex data workflow.

Code Demo

ArviZ Dashboard

Dashboards; Statistics; Model Comparison

Designed for Bayesian statisticians, this project transforms static visualizations into interactive dashboards with tools like Panel and Bokeh. It enables dynamic model comparison within a unified interface.

Code

CrowdIDEA

Visualization; Causal Reasoning

CrowdIDEA integrates crowd beliefs, data analytics, and causal diagrams into a tool for stimulating causal reasoning. Its design encourages exploration of causal relationships using collective insights

Code Demo