Research

Adversarial, LLM Attacks

PLeak: Prompt Leaking Attacks against Large Language Model Applications, Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, Bo Hui, Haolin Yuan, Neil Gong, Philippe Burlina, Yinzhi Cao, 2024

Generative models, Semantic Atttributes, Disentanglement, AI Fairness

Representation learning / Anomaly Detection

RENATA: REpreseNtation And Training Alteration for Bias Mitigation

R'{e} nyi Generative Adversarial Networks

Other Adversarial ML

Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks

Random Projections for Adversarial Attack Detection

Zero / Low-Shot Learning

Semantic Zero Shot Learning

Hybrid Hierachical/Semantic Zero-Shot Learning

Hierarchical Classification for Zero-Shot Learning

AI for Medical / Healthcare / Bio

Low-shot deep learning of diabetic retinopathy with potential applications to address artificial intelligence bias in retinal diagnostics and rare ophthalmic diseases

Addressing Artificial Intelligence Bias in Retinal Disease Diagnostics

AI-based detection of erythema migrans and disambiguation against other skin lesions

Deep Reinforcement Learning

DRL/robotic reaching

DRL/robotic grasping

Misc

Video tracking, efficient particle filtering

Probability hypothesis density filters for tracking

Distributed vision sensors, consensus pose estimation

MRCNNs