Postdoctoral Fellow at the Department of Computer Science, City University of Hong Kong, working with Prof. Qingfu Zhang (IEEE Fellow). My research bridges evolutionary computation and machine learning to tackle complex optimization challenges.

• Evolutionary Computation: Multi/Many-objective optimization, algorithm design
• Adversarial Machine Learning: Robustness evaluation, attack generation, defense strategies
• LLM for Optimization: Automated algorithm design, symbolic solution evolution

• [CVPR] MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework [Code]
• [IEEE TETCI] Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume

• [GECCO] L-AutoDA: Large Language Models for Automatically Evolving Decision-based Adversarial Attacks [Code]
• [Preprint] CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models [Code]

• [EMO] Approximation of a Pareto Set Segment Using a Linear Model

LLM-driven evolutionary optimization framework implementing the CoEvo methodology for continual solution evolution.

• 🎯 Applications: Symbolic regression, algorithm discovery, automated optimization

Automated adversarial attack generation using Large Language Models (GECCO 2024)

• 🏆 Conference: GECCO 2024
• 📊 Benchmark: State-of-the-art on multiple adversarial robustness benchmarks

Conference Reviewer: NIPS • ICML • ICLR • AISTATS • CEC

Journal Reviewer: Swarm and Evolutionary Computation • Evolutionary Computation

• Email: pingguo5-c@my.cityu.edu.hk
• Office: Department of Computer Science, City University of Hong Kong