Publications

Peer-reviewed research.

A selection of representative work from the lab. Several papers are currently under review; the full list is updated with links and DOIs as papers are published.

2026

JournalJ. of the Korean Inst. of Communications & Information Sciences · Forthcoming · 2026

Dynamic DNN Partitioning and Cooperative Offloading for EV-Hub Edge AI in Public-Safety Networks

I. Lee

Dynamic DNN partitioning and cooperative offloading across heterogeneous devices on EV-Hub edge infrastructure, optimizing latency and energy for public-safety networks.

Edge AISplit ComputingPublic-Safety Networks
JournalJournal of Police Policy (KCI) · Under review · 2026

Simulating Voice-Phishing Defense for Older Adults with Generative Agent-Based Modeling

I. Lee

A Victim–Attacker–EchoChamber generative agent-based model that pre-tests voice-phishing defense strategies for older adults under adversarial coevolution.

GABMSimulationFraud Prevention
JournalSocial Science Computer Review (SSCI) · Under review · 2026

A Four-Pillar Validation Framework for Synthetic Personas

I. Lee

Distributional fidelity, stereotype audit, convergent and construct validity — four pillars that tier synthetic personas for reliable research use.

Synthetic DataValidationPersonas
JournalAI and Ethics (Springer, SSCI) · Under review · 2026

Procedural Compliance and Self-Preference in LLM-as-Judge Evaluation

I. Lee

Quantifying self-preference bias in LLM-as-judge evaluation across procedural scenarios and alignment conditions.

LLM-as-JudgeEvaluationBias
JournalJournal of Computational Social Science (Springer) · Under review · 2026

Countering Disinformation with Generative Agent-Based Modeling: Backfire and Adversarial Coevolution

I. Lee

Agent-based simulation comparing counter-disinformation interventions, revealing emergent backfire effects and adversarial coevolution dynamics.

GABMDisinformationGovernance
JournalKorean Police Studies Review (KCI) · Under review · 2026

The Policing-AI Trilemma and Future Scenarios

I. Lee

An impossible-trinity lens on policing AI, developed through a synthetic expert panel and 2×2 scenario planning across seven national cases.

GovernanceScenario PlanningPolicy