Climate Vulnerability Analysis
Connecting climate and socioeconomic data to identify the communities most at risk.
Jaewon Cho
Data · AI · Engineering
I’m Jaewon Cho, an engineer passionate about using data and technology to solve real-world problems.
My experience spans data analytics, machine learning, software engineering, and AI-driven problem solving. I have worked on projects ranging from electric vehicle charging demand forecasting and synthetic data generation to backend system development and data-driven analysis in the semiconductor industry.
I especially enjoy turning complex and ambiguous problems into structured, actionable solutions. Whether I am analyzing data, building a system, or collaborating with a team, I focus on understanding the problem first and finding practical ways to create measurable impact.
Along the way, I have had opportunities to work with multidisciplinary teams and participate in global analytics competitions. These experiences taught me that strong results rarely come from technical skills alone — they come from curiosity, collaboration, and the willingness to keep improving.
Outside of work, I enjoy basketball and travel.
Professional Journey
| When | Experience & highlights |
|---|---|
| Present | Working on data-driven problem solving and analytics in the semiconductor industry, with a focus on applying data and AI to real operational challenges. |
| Nov 2024 | Won 1st place globally in the SAS Hackathon, competing with 145 teams from 70 countries. |
| Aug 2024 | Led a synthetic data initiative to expand EV charging demand forecasting research using machine learning and synthetic data. |
| Aug 2024 | Completed a software engineering internship at Samsung Electronics, working on backend systems and database development. |
| Apr 2024 | Won 2nd place in the SAS Curiosity Cup, competing against 107 teams from 19 countries. |
| Jan 2024 | Joined the SAS ORSOL research team, contributing to data preprocessing, forecasting, and EV charging demand research. |
What I’m Interested In
- Data & Analytics
- Finding meaningful patterns in complex data and transforming them into actionable insights.
- Artificial Intelligence
- Exploring how AI and intelligent agents can make engineering and business processes more efficient.
- Engineering & Problem Solving
- Building practical solutions that connect technology with real operational needs.
- Collaboration
- Working with people from different backgrounds and turning diverse perspectives into better solutions.
Selected Projects
A selection of the problems I’ve worked on.
EV Charging Demand Forecasting
Using traffic patterns to forecast charging demand when station-level data is scarce.
Synthetic Data for EV Demand Forecasting
Exploring synthetic time-series data for EV demand forecasting and optimization.
Boiler Time
A student-centered app bringing schedules, community, and campus essentials together.
FIRE: Fire Detection & Rescue Support
An infrared and machine-learning system concept to support safer emergency response.