Biometric Signal Analysis
EEG-based biometric signal processing for pedestrian emotion and response
EEG-based biometric signal processing for pedestrian emotion and response
Scene segmentation of self-built virtual urban environments for pedestrian research
Reinforcement learning for pedestrian behavior and intelligent transportation systems
VR-based driving and pedestrian simulation for human factors research
Microscopic and macroscopic traffic simulation
Urban mobility patterns and travel demand modeling
Spatial analysis and urban design for sustainable city development
A multimodal global-optimization benchmark — and why it matters for validating gradient-free solvers before they touch expensive, nonconvex transportation objectives.
Vision-Language Models for structured streetscape assessment from open street-level imagery
A computer-vision approach to walkability, active aging, and housing capitalization
Congestion-based traffic assignment and design optimization for pedestrian networks (PedNetOpt)
Published in SH Urban Research & Insight, 2024
Recommended citation: Park, W., Ko, H., & Kim, S.-N. (2024). "An analysis of threshold access time and distance to age-friendly facilities: A comparison between senior and pre-senior populations." SH Urban Research & Insight, 14(3), 75-96.
Published in Virtual Reality, 2024
Recommended citation: Son, D., Im, B., Her, J., Park, W., Kang, S. J., & Kim, S. N. (2024). "Street lighting environment and fear of crime: a simulated virtual reality experiment." Virtual Reality, 29(1), 1-17. DOI
Published in Virtual Reality, 29, 145, 2025
Recommended citation: Park, W., Son, D., Im, B., Her, J., Kim, Y.-J., & Kim, S.-N. (2025). "Fear of crime revisited: analyzing the effects of urban nighttime illuminance on neural and psychological responses using recorded virtual environments and electroencephalogram data." Virtual Reality, 29, 145. DOI
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Introduction to statistical learning concepts with Python (NumPy, Pandas, Matplotlib)
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Measuring the quality of fit: MSE, bias-variance trade-off, and training vs. test error
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KNN classifier and regressor: a non-parametric approach to classification and regression
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Fitting a linear model with a single predictor using OLS
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Extending linear regression to multiple predictors, interaction terms, and polynomial regression
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Optimization algorithm for minimizing the cost function in linear regression
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Binary classification using the logistic function and maximum likelihood estimation
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LDA, QDA, and Naive Bayes classifiers based on Bayes theorem
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Extending linear models beyond Gaussian: Poisson regression and the GLM framework
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Model assessment and selection using validation set, LOOCV, and k-fold cross-validation
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Estimating uncertainty and standard errors through resampling
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Shrinkage methods for regularization: L1 and L2 penalties
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Best subset, forward stepwise, and backward stepwise selection methods
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Non-linear extensions of linear models: polynomial, step functions, and regression splines
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Recursive binary splitting for classification and regression trees
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Ensemble methods using bootstrap aggregation and random feature selection
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Boosting and other ensemble strategies for improved prediction
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Dimensionality reduction using PCA: theory, implementation, and visualization
Undergraduate course, [Chung-Ang Univesrity], 2024