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🌟 Featured Publications

Network Intrusion Detection

Uncertainty-Quantified Neurosymbolic AI for Open Set Recognition in Network Intrusion Detection

Oct 28, 2024

Hallucination

Mitigating Large Vision-Language Model Hallucination at Post-hoc via Multi-agent System

Oct 1, 2024

Uncertainty Quantification

URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference Methods

URSABench is an open-source benchmarking suite for assessing Bayesian deep learning models and inference methods, focusing on uncertainty quantification, robustness, scalability, and accuracy in classification tasks for both server and edge GPUs.

Apr 1, 2022

Uncertainty Quantification

Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting

We introduce a new symmetric integration scheme for split Hamiltonian Monte Carlo (HMC) that enables efficient inference for Bayesian neural networks on large datasets. Our method outperforms stochastic gradient MCMC in accuracy and uncertainty quantification, demonstrating HMC as a viable option for large-scale machine learning problems.

Dec 1, 2021

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🕑 Recent Publications

Chung-en (Johnny) Yu, Brian Jalaian, Nathaniel D Bastian (2025). Hydra: An Agentic Reasoning Approach for Enhancing Adversarial Robustness and Mitigating Hallucinations in Vision-Language Models. arXiv preprint arXiv:2504.14395.

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Jacob Sander, David Moe, Achraf Cohen, Brent Venable, Venkat Dasari, Brian Jalaian (2025). Constrained Edge AI Deployment: Fine-Tuning vs Distillation for LLM Compression. arXiv preprint arXiv:2505.18166.

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Huynh TT Tran, Jacob Sander, Achraf Cohen, Brian Jalaian, Nathaniel D Bastian (2025). Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning. arXiv preprint arXiv:2506.04454.

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Jacob Sander, Achraf Cohen, Venkat R. Dasari, Brent Venable, Brian Jalaian (2025). On Accelerating Edge AI: Optimizing Resource-Constrained Environments.

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Fudong Lin, Jiadong Lou, Hao Wang, Brian Jalaian, Xu Yuan (2025). Towards Interpretable Adversarial Examples via Sparse Adversarial Attack. arXiv preprint arXiv:2506.17250.

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