Publications | Dr. Brian Jalaian's Website

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Featured Publications

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

Network Intrusion Detection

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

Oct 28, 2024

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

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

Oct 1, 2024

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

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

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

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

🔬 Selected Publications by Research Area

Recent Publications

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

Alice Bizzarri, Chung-en Yu, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D Bastian (2024). Neuro-Symbolic Integration for Open Set Recognition in Network Intrusion Detection. International Conference of the Italian Association for Artificial Intelligence.

Jacob Sander, Chung-en Johnny Yu, Brian Jalaian, Nathaniel D. Bastian (2024). Uncertainty-Quantified Neurosymbolic AI for Open Set Recognition in Network Intrusion Detection. MILCOM 2024 - 2024 IEEE Military Communications Conference (MILCOM).

PDF Cite DOI URL

Chung-en Johnny Yu, Brian Jalaian, Nathaniel D Bastian (2024). Mitigating Large Vision-Language Model Hallucination at Post-hoc via Multi-agent System. In AAAI-FS 2024.

Alice Bizzarri, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D. Bastian (2024). A Neuro-Symbolic Artificial Intelligence Network Intrusion Detection System. 2024 33rd International Conference on Computer Communications and Networks (ICCCN).