BJBrian Jalaian

Publications

Selected work.

A curated set of peer-reviewed papers, grouped by research thrust. The complete, continuously updated record lives on Google Scholar.

Full list on Google Scholar

2026: new and in review

New
Decomposable Collective Uncertainty for Multi-Agent Multimodal Reasoningwith Chung-En Yu & David Garcia · Robust Visual Agentic Systems
Under review
Scale- & Architecture-Dependent Routing of Compression for Edge AIwith Venkat Dasari · Efficient AI at the Edge
MILCOM 2026 workshop
What Actually Matters in Synthetic-Data Distillation for Small LMswith Jacob Sander · Uncertainty, Assurance & Trust
Under review
Statistically Valid Stopping for Autonomous Experimentationwith Venkat Dasari · Uncertainty, Assurance & Trust
Under review
01

Robust Visual Agentic Systems

Towards Interpretable Adversarial Examples via Sparse Adversarial AttackLin et al.
ECML PKDD · 2025
Mitigating Large Vision-Language Model Hallucination at Post-hoc via Multi-agent SystemYu, Jalaian, Bastian · Student-led
AAAI Symposium Series · 2024
Improving Object Detection Robustness against Natural Perturbations through Synthetic Data AugmentationPremakumara et al.
ACM CVIPPR · 2023
Reducing Classifier Overconfidence against Adversaries through Graph AlgorithmsTeixeira et al.
Machine Learning (Springer) · 2023
Attribution-Based Confidence Metric for Deep Neural NetworksJha et al. · Confidence under adversarial inputs
NeurIPS · 2019
02

Efficient AI at the Edge

A Generalized Optimization Engine (GOE) for Edge AI Inference AccelerationDasari, Adams, Mishra, Jalaian
IEEE MILCOM Workshops (LEAF) · 2026
Constrained Edge AI Deployment: Fine-Tuning vs. Distillation for LLM CompressionSander et al. · Student-led
IEEE MILCOM · 2025
Enhancing Resilience in Mobile Edge Computing under Processing UncertaintyLi et al.
IEEE JSAC · 2023
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep LearningVadera et al.
arXiv · 2022
Generalized Bayesian Posterior Expectation Distillation for Deep Neural NetworksVadera, Cobb, Jalaian, Marlin · Signature distillation result
UAI · 2020
03

Uncertainty, Assurance & Trust

Neurosymbolic AI for Network Intrusion Detection Systems: A SurveyBizzarri et al.
J. Information Security and Applications · 2025
Neurosymbolic AI Transfer Learning Improves Network Intrusion DetectionTran et al. · Student-led
IEEE MILCOM · 2025
Uncertainty-Quantified Neurosymbolic AI for Open Set Recognition in Network Intrusion DetectionSander, Yu, Jalaian, Bastian · Student-led
IEEE MILCOM · 2024
A Neuro-Symbolic Artificial Intelligence Network Intrusion Detection SystemBizzarri et al.
ICCCN · 2024
Neuro-Symbolic Integration for Open Set Recognition in Network Intrusion DetectionBizzarri et al.
AIxIA · 2024
Neurosymbolic AI in Cybersecurity: Bridging Pattern Recognition and Symbolic ReasoningJalaian et al. · First author
IEEE MILCOM · 2023
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte CarloKungurtsev et al.
Machine Learning (Springer) · 2023
Runtime Monitoring of Deep Neural Networks Using Top-Down Context ModelsRoy et al.
AAAI Spring Symposium · 2022
Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric SplittingCobb, Jalaian · Underlies the hamiltorch library
UAI · 2021
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural NetworksVadera et al.
arXiv · 2020

Author names abbreviated for brevity. Citation counts and full metadata on Google Scholar and ORCID.