Jin's tory — About me / CV

CV

Full document, updated August 2026

Ph.D. in Civil and Environmental Engineering Rensselaer Polytechnic Institute · Troy, NY, USA Aug 2026 – Present
Transportation and Highway Engineering.
M.S. in Logistics Inha University, Graduate School of Logistics · Incheon, Korea Aug 2024 · GPA 4.35 / 4.5
Inha President's Award. Thesis: A Study on the Determinants of Customer Logistics Volume — A Case Study of the Parcel Delivery System in Seoul (Advisor: Dr. Daisik Nam).
B.A. in Logistics, Minor in Computer Engineering Inha University · Incheon, Korea Feb 2022 · GPA 3.84 / 4.5

Researcher Korea Transport Institute (KOTI) · Sejong, Korea Sep 2023 – Jul 2026
Carbon Emission System Development — national GHG emission model improvement, link-based traffic data, ML applications. Autonomous Driving High-Risk Accident Prediction — network segmentation and risk factor definition.
Research Assistant Inha University Mar 2022 – Aug 2023
Built an integrated parcel / land-use / census database for customer logistics; slot allocation optimization for last-mile delivery.
Research Assistant Inha University Mar 2021 – Aug 2022
Social Network Analysis of government–industry–academia collaboration during COVID-19.
[ Project — title to be confirmed ] — —
Placeholder for the additional project marked in the draft. Fill in title, host, period and one-line description.

President's Award, Graduate School of Logistics Inha University 2024
Bronze Award, Kakao Mobility Data Contest 40th Anniversary International Conference of the Korean Society of Transportation 2022
Silver Award, Industrial Application Project Competition Korean Society of Supply Chain Management 2022
Excellence Award 88th TOSOK Daegu / Gyeongbuk International Tourism Conference 2020
Encouragement Award, Undergraduate Financial Security Camp Financial Security Institute 2020

What I want to work on next

Database-driven decision making in transportation and freight
Turning large operational datasets into decisions that hold up — for networks, fleets and freight corridors.
Vehicle-level GHG emission modeling
Correction factors for road gradient and acceleration; moving national inventories toward Tier 3 trajectory-based accounting.
Last-mile and urban logistics
Demand intensity, service-vulnerable areas, and shared multimodal delivery as a lever on urban traffic.
Traffic big data & machine learning
Link-based trajectory data, RF-based volume estimation, and network connectivity as model inputs.