Joe Zhu
Urbana,Illinois
Summary
Proactive and goal-oriented professional with excellent time management and problem-solving skills. Known for reliability and adaptability, with swift capacity to learn and apply new skills. Committed to leveraging these qualities to drive team success and contribute to organizational growth.
Overview
1
1
year of professional experience
1
1
Certification
Work History
SIGCHI UIUC Member
SIGCHI UIUC
08.2025 - Current
I created an add-on for Google Calendar called Smart Calendar Assistant by writing code in Google Apps Script. It has multiple functions: tag, priority, flexibility, and event color. I also developed an AI-powered function: Smart Break Suggestions. Smart Break Suggestions can generate suggestions for the time slot between two user-created events to improve users' time management.
Illinois Data Science Club Member
Illinois Data Science Club
08.2024 - 12.2024
- Work on a group project about creating a table tennis recommendation system.
- Data Collection
- Data Analysis
- Python Programming
Table Tennis Recommendation System
Education
Bachelor of Science - Statistics And Computer Science
University of Illinois At Urbana-Champaign
Champaign, IL05-2028
Skills
- Computer skills: C, Java, Python, RStudio, Excel, SQL
- Generalized Additive Mixed Models(GAMMs), data visualization
- Machine Learning, Large Language Models
- Intelligent automation, rule-based AI systems
- Google Apps Script, Google Calendar API integration
- Task prioritization algorithms, time-block detection
- UI design with CardService, workflow optimization tools
- Teamwork and Leadership
- Friendly, positive attitude
- Problem-solving
- Attention to details
Projects
Sandia Data Challenge(Datathon), November 2025
Presentation Slides Presentation Video Github Repository
Ranking: top 10 out of 40 groups
Data Problems Brief:
1)Your customer has provided you with a dataset on
build parameters and dimensions of
additively manufactured parts. These parts must
meet qualification requirements to be
considered for use. Otherwise, they will be
scrapped. We need to know the combinations
of build parameters(powder type, build plate layout, location on the build plate, existence of test artifacts) that minimize the
potential scrap rate.
2) Does the use of recycled powder affect the particle size distribution of
the source powder?
Conclusions:
1.Parts produced with recycled powder are more than twice as likely to scrap compared to those
made with virgin powder.
2.Scrap Rate
Varies Systematically Across the Build Plate(higher scrap rate at edges and corners)
3.Interaction between the four factors:
Scrap rate is influenced by both material and build conditions.
● Virgin powder consistently shows lower predicted scrap across all layouts.
● Recycled powder amplifies edge scrap, especially in larger build layouts.
● Test Artifacts (TA) reduce scrap near their placement by stabilizing thermal gradients.
● The combination of Recycled + Large Layout + TA produces the highest scrap risk.
4. Powder type distribution
● Both powders show similar overall particle size distributions
● Recycled powder exhibits a slightly broader distribution
● This suggests a small increase in fine particles during reuse
Certification
- AWS Educate Machine Learning Foundations: https://www.credly.com/badges/4f592dcd-2581-41e3-b9d2-ee3823985adb/public_url
- AWS AI& ML Scholars : Introducing to Generative AI with AWS www.udacity.com/certificate/e/43dca510-5727-11f0-a230-3ff90d0a0bd3
Languages
English
Native/ Bilingual
Chinese (Mandarin)
Native/ Bilingual
Timeline
SIGCHI UIUC Member
SIGCHI UIUC
08.2025 - Current
Illinois Data Science Club Member
Illinois Data Science Club
08.2024 - 12.2024
Bachelor of Science - Statistics And Computer Science
University of Illinois At Urbana-Champaign