Technical Strengths & Skillsets
A comprehensive overview of programming, mathematical frameworks, domain expertise, and communicative capabilities Dr. Joo applies to real-world mobility challenges.
Data & Programming 6 Skills
Python
Primary language for data science, deep learning models, and safety evaluation workflows. Proficient in pandas, NumPy, scikit-learn, PyTorch, and VLM APIs.
R
Used for advanced statistical modeling, econometric analysis, and experimental design validation.
SQL
Querying and structuring large-scale database systems, performing complex temporal and spatial traffic data aggregations.
Data Processing
Wrangling large, noisy spatial-temporal datasets including high-resolution traffic signal logs, vehicle telemetry, and sensor streams.
Statistics & Experimentation
Designing rigorous statistical tests, causal inference workflows, and before-and-after experiments to validate system-level safety changes.
Large-scale mobility data workflows
Processing millions of high-frequency data points (ATSPM) using distributed computing concepts and cloud-adjacent pipelines.
Machine Learning & AI 6 Skills
Machine Learning
Applying supervised and unsupervised techniques to classify traffic patterns, predict crash risks, and evaluate driver safety profiles.
Conformal Prediction
Implementing distribution-free uncertainty quantification frameworks to calibrate ML models and provide rigorous confidence bounds on predictions.
VLM Evaluation
Adapting and evaluating vision-language models (e.g., GPT-4V, LLaVA, Gemini) to classify and assess complex driving scenes and visual risks.
Generative AI
Applying generative models (such as tabular GANs) to address class imbalance issues in crash severity prediction datasets.
Uncertainty Quantification
Developing systems that distinguish between aleatoric and epistemic uncertainties in risk-heavy transportation environments.
Model Validation
Validating ML models against real-world human data using structured test suites, cross-validation, and out-of-distribution metrics.
Transportation Safety & Mobility 6 Skills
Driving Risk Assessment
Creating models to quantify scenario risk, human perceived risk, and automated safety indexes in real-world driving environments.
Traffic Conflict Analysis
Using surrogate safety measures (e.g., time-to-collision, post-encroachment time) to evaluate rear-end and intersection conflict risks.
ATSPM
Leveraging Automated Traffic Signal Performance Measures to evaluate intersection performance and corridor operations.
Traffic Signal Analytics
Correlating signal controller event logs, timing plans, and cycle lengths with vehicle safety behaviors and delay analytics.
Smart Mobility
Applying connected vehicle data, V2X concepts, and advanced sensory inputs to improve public transit and autonomous fleet safety.
DOT Project Experience
Delivering research, deliverables, and dashboards for state Departments of Transportation (e.g., FDOT) and municipal agencies.
Research Translation & Communication 6 Skills
Technical Writing
Publishing peer-reviewed articles in high-impact journals (IEEE T-ITS, AMAR, AAP) and drafting detailed technical project reports.
Grant Writing
Contributing to successful research proposals, work scopes, and funding bids for transportation agencies.
Survey Design
Creating rigorous survey methodologies and user validation studies to link human risk perception with computational models.
Cross-functional Collaboration
Partnering with computer scientists, human factors experts, and civil engineers to solve interdisciplinary safety problems.
Agency-facing Reporting
Presenting complex data insights in clear, actionable business formats to transportation officials and policy-makers.
Research Presentation
Translating theoretical concepts into production-ready software tools, presenting findings to technical and business stakeholders.