Computational Intelligence Systems

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Vol. 4 No. 1 (2026): Computational Intelligence Systems

View Vol. 4 No. 1 (2026): Computational Intelligence Systems

Published: 2026-04-08

Articles

Enhancing Predictive Precision in Clinical Trial Modeling through Deep Survival Learning Architectures Integrating High-Dimensional Patient Covariates and Temporal Treatment Dynamics

Vincent Westbrook
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Achieving Robust Alignment in Autonomous Systems via Inverse Reinforcement Learning Integrating Human Ethical Value Priors

Vincent Pennington
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Synergizing Symbolic Logic and Reinforcement Learning for Provably Correct Reasoning in Large Language Model Decision Pipelines

Douglas Ashcroft, William Prescott
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Artificial Intelligence Approaches for Discovering Functional Gene Expression Patterns in Oncogenic Signaling Pathways

Clifford Lewis, Francis Graham
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An Adaptive Particle Swarm Optimization Approach for Multi-Objective Scheduling Problems

Leon Grant
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An Intelligent AIOps Framework for Fault Detection and Network Optimization in 5G-A Systems

Brandon Kingsley, Paul Langford
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Bridging Multi-Modal Radiomics and Deep Learning Features for Precise Lesion Detection using Uncertainty-Aware Cross-Attention Fusion Networks

Ananya Mukherjee
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Empowering Real-Time Financial Decision Systems via Reinforcement Learning Driven Large Language Models and Distributed Temporal Pipelines

Paul Carver
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Adversarial Cross-Modal Representation Learning for Human Activity Anticipation and Video-Driven Behavioral Prediction

Felix Ferguson, Viktor Bell
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Securing Algorithmic Trading Infrastructures via Large Language Model Driven Automated Vulnerability Analysis and Real-Time Protocol Hardening

Calvin. Sterling, Cassie L. Vance
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Quantifying the Ethical Risks of Generative AI through Automated Toxicity Scoring and Human-Centric Alignment Auditing Pipelines

Paul Whitmore, Edward Telford
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Facilitating Cross-Domain Reasoning Generalization through Conservative Offline Reinforcement Learning Leveraging Pre-trained Large Language Model Representations

Maxwell Ashford
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A Multiclustering Evolutionary Hyperrectangle-Based Algorithm

David Kingsley, Harold Wainwright
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AI Governance Challenges in Financial Decision-Making Systems: Beyond Regulatory Constraints

Russell Hensley, Victor Calder
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Auditing the Long-Term Societal Impact of AI-Driven Surveillance through Temporal Bias Analysis and Human-in-the-Loop Governance

Theodore Pennington
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Developing Autonomous Financial Decision Systems by Synergizing Multi-Agent Large Language Models with Distributed Temporal Learning Pipelines

Elizabeth Thornton, Catherine Vance
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Causal Regime-Aware Portfolio Allocation under Residual Stress and Tail-Risk Transmission

Andres Schwartz, Nitin Jha, Yangnan Fan
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Modeling the Influence of News Sentiment on Public Perception Using Natural Language Processing

Leon Donovan, Vincent Wexford
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Mitigating Tail Risk in Portfolio Optimization via Generative Adversarial Networks Simulating Synthetic Market Crashes and Non-Linear Correlation Shifting Events

Zachary Hawthorne
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Integrating Causal Inference into Reinforcement Learning via Large Language Model Reasoning for Transparent and Robust Counterfactual Decision Analytics

Matthew Wentworth, Thomas Ellington, Scott Donovan
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Fin-LLM-Inference: A High-Throughput Distributed System for Real-Time Financial Time Series Forecasting via Heterogeneous LLM-Augmented Reasoning Pipelines

Brandon Prescott, Christopher Sinclair
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Toward an Internal Governance Architecture for General-Purpose AI Systems

Wesley Sutherland
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Advancing Responsible AI Governance through Decentralized Policy Enforcement Frameworks for Ethical Autonomous Agent Behavior

Derek Ellsworth
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Quantifying Structural Healthcare Disparities through Fairness-Aware Large Language Models Integrating Multi-Modal Electronic Health Records and Socioeconomic Determinants

Julian Thorne, Timothy Ellison, Colin Callahan
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Developing Incentive Compatible Attribution Engines for Social Advertising using Game Theoretic Autonomous Agents and Distributed Transaction Pipelines

Harrison Sterling
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Extracting High Frequency Alpha Signals through Deep Visual Representation Learning on Order Flow Imbalance and Multi Level Liquidity Patterns

Maxwell Wainwright
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Synthesizing Cross-Modal Decision Policies through Reinforcement Learning Integrating Visual Perception and Large Language Model Tactical Planning

Ethan Ellsworth, Scott Norwood, Benjamin Pennington
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Towards High-Throughput Financial Intelligence: A Hardware-Aware Distributed Infrastructure for Real-Time Time Series Forecasting via Speculative LLM Decoding

Warren Wexford, Franklin Langford
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Cross-Modal Federated Learning Security: Extending Prototype Consistency for Backdoor-Resilient Multimodal Representation Learning

Henri C. Berry, Davide Allen, Sunil Jha
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Mitigating Behavioral Divergence in Autonomous Agent Systems via Real-Time Alignment Auditing and Proactive Safety Constraint Synthesis Architectures

Dylan Whitmore
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Enhancing Model Accountability via Automated Lineage Tracking and Cryptographic Proofs of Decision Integrity in Financial AI

Jeremy Hollis, Alan Kingsley
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Facilitating Collective Reasoning Intelligence through Multi Agent Reinforcement Learning for Consensus Driven Logic Synthesis in Large Language Model Systems

Dennis Hawthorne, Gavin Nolan, Jason Reeves
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Deep Reinforcement Learning-Based Decision Support System for Smart Environments

Oliver Harrington, Franklin Radford
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Improving Model Interpretability in Credit Scoring Systems through Counterfactual Explanation Frameworks for Equitable and Transparent Financial Decision Making

Sarah Jenkins
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Advancing Strategic Decision Excellence through Self Play Reinforcement Learning Frameworks Leveraging Large Language Models for Recursive Policy Improvement

Nathaniel Blackwood
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Fed-AdAgent: A High-Throughput Distributed Infrastructure for Social Commerce via Privacy-Preserving LLMs and Incentive-Compatible Mechanism Design

Theodore Hollingsworth, Charles Ashford
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Adaptive Network Slicing and Resource Allocation in 5G-Advanced Systems

Elias Hartmann
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Reducing Gender and Racial Biases in Multimodal Vision Language Models via Contrastive Debiasing and Representative Dataset Synthesis

Dylan Clarke
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Streamlining Real Time Decision Reasoning via Reinforcement Learning Driven Large Language Model Agents for Complex Task Planning and Adaptation

Alexander Ellison, Stephen Carmichael, Eric Whitman
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Cultural Bias Auditing in Multimodal Generative Models Through Cross-Lingual Prompt Sensitivity Analysis

Roy J. Burton, Maurice D. Greene, Arthur M. Walters
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A Novel Evolutionary Feature Selection Method for High-Dimensional Data Classification

Samuel Calder
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Performance Optimization of RISC-V Based Embedded Systems for Real-Time AI Applications

Ethan J Walker, Hiroshi Tanaka
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Defining Global Standards for AI Safety through Multi-Stakeholder Consensus Frameworks Integrating Technical Robustness and Ethical Sovereignty

Samuel Higgins, Patrick Hawthorne
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Advancing Autonomous Crop Monitoring via Semantic Visual Alignment using Large Language Model Guided Navigation for Agricultural UAV Systems

Victor Grant
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Fed-AdScale: A Distributed Edge-Cloud Infrastructure for Social Commerce via Privacy-Preserving LLM Inference and Trusted Execution

Miles Crawford, Marcus Whitmore, Blake Callahan
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Mitigating Societal Biases in Recommendation Algorithms through Fairness-Aware Reinforcement Learning and Demographic Parity Constraints

Gerald Telford
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Integrating Causal Inference into Reinforcement Learning Pipelines for Robust Counterfactual Reasoning in Generative Large Language Models

Raymond Norwood, Derek Clarke
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Agri-UAV-Inference: A High-Throughput Distributed System for Precision Agriculture via Financial-Grade Time Series Forecasting and Edge-AI Swarm Intelligence

Silas Thorne
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A Hybrid Fuzzy Neural Network Model for Time Series Prediction in Complex Systems

Connor Redford, Ian Hollis
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Governance Risks of Autonomous AI in Healthcare Recommendation Systems

Gavin Carmichael
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Balancing Privacy and Explainability in Healthcare AI through Secure Multi-Party Computation and Local Interpretable Model-Agnostic Explanations

Michael Chen
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Scaling High-Frequency Financial Intelligence using Adaptive Resource Scheduling for Multi-Modal Large Language Model Enhanced Inference

Albert Prescott, Colin Callahan
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Detecting Sentiment Bias in Digital Media and Its Effects on User Belief Formation

Elliot Nolan, Aris T. Vance
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Advancing Quantamental Investment Frameworks through Large Language Model Reasoning Integrating Textual Sentiment Volatility and Structured Financial Statement Analytics

Gordon Hawthorne, Franklin Wainwright
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Accelerating Rapid Task Adaptation via Meta Reinforcement Learning and Large Language Model Prompt Optimization for Dynamic Decision Environments

Oliver Ellsworth, Richard Mercer
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Bridging Numerical Market Dynamics and Narrative Logic for Robust Financial Machine Learning using Cross-Modal Transformer Architectures

Mira K. Beaumont
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Deep Learning-Based Prediction of Neural Ionic Homeostasis Changes During Sleep Pressure Accumulation

Huijia Gao, Jeffrey Taylor, Xiaohai Chen
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Internal Alignment Deficit in Autonomous AI Systems: Reconsidering Governance Beyond External Constraints

Andrew Holloway
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Ensuring Algorithmic Equity via Distributional Alignment Techniques for Reducing Disparate Impact in Automated Hiring Systems

Victor Donovan, Samuel Carmichael
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Optimizing Multi-Modal Financial Intelligence via Resource-Aware Distributed Scheduling for Large Language Model Enhanced Time Series Inference Pipelines

Alistair Vance, Matthew Pennington
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Intelligent Fault Diagnosis in Industrial Systems Using Ensemble Learning Techniques

Dennis Hensley
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Optimizing Risk Parity Portfolios via Hidden Markov Model Empowered Deep Reinforcement Learning under Macroeconomic Regime Switching Scenarios

Jonathan Wainwright
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Implementing Probabilistic Safety Guardrails via Constrained Reinforcement Learning and Large Language Model Reasoning for Risk Aware Autonomous Decision Making

Warren Beaumont
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Streamlining Financial Large Language Models for On-Device Time Series Analytics through Knowledge Distillation and Quantized Inference Architectures

Harrison Vance, Scott Lockwood
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Energy-Efficient Hierarchical Planning and Action Compression for Edge-Deployed Large Language Model Reasoning Systems

Brent Rhodes, Jordan Wood, Noah A. Simmons
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Federated Deep Reinforcement Learning for Adaptive Spectrum Allocation in Dense 5G-A Wireless Networks

Zaid J. Reed, Kriti Grover
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Deep Spectral Feature Aggregation for Hyperspectral–LiDAR Data Fusion in Land Use Classification

Stanley Holm, Terry Phillips, Kartik M. Jha
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Band-Aware Deep Learning for Hyperspectral Image Classification with Auxiliary LiDAR Elevation Features

Zhifei Du, Rohan Mishra, Jakub Lawson
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AI-Enabled Multi-Omics Integration for Characterizing Dynamic Gene Expression Programs in Tumor Cells

Shane Sanders, Ross Gregory, Vishal L. Pandey, Varun Subramanian
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Cross-Modal Adversarial Defense for Medical LLM Agents in Clinical Decision Support Systems

Leif Willis
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Endmember-Aware Feature Learning for Nonlinear Hyperspectral Unmixing

Suraj Tripathi, Uday Tripathi, Warren Burns, Ruben Walters
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Federated Adversarial Training of Large Language Model Agents for Distributed Healthcare Systems

Trevor D. Douglas, Ole Lopez
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Federated Multi-Generator Spatiotemporal Modeling for Privacy-Preserving Autonomous Navigation Prediction

Sagar Arora, Felix Day
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Explainable Fairness Evaluation for Text-to-Image Diffusion Models in Underrepresented Cultural Contexts

Haocheng Hao, Nitin J. Banerjee, Arun Mehra
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Deep Spectral Representation Learning for Hyperspectral Unmixing and Abundance Estimation

Massimo R. Day, Rainer Chandra, Florian Chambers, Pavel Eriksson
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Fairness-Aware Federated Learning Security: Mitigating Backdoor Attacks While Preserving Client-Level Equity via Prototype Constraints

Larry Lowe, Zachary Barnett
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Physics-Guided Spatio-Temporal Neural Fields for Crowd Navigation and Pedestrian Dynamics Modeling

Xin Ding, Noah M. Simmons
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NeuroSymbolic Traffic Reasoning with World-Grounded Multimodal Models for Explainable Autonomous Driving

Dominik M. Holm
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Learning Complementary Spectral and Structural Features from Hyperspectral and LiDAR Data

Fernando Chambers, Ananya Pillai, Rowan D. Gregory, Troy Schwartz
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Privacy-Preserving Vertical Split Learning for Healthcare AI with Prototype-Based Anomaly Detection Against Data Poisoning

Dan Xue, Niklas Barnett
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Hybrid Neuro-Symbolic Architectures for Secure Medical Decision Support Under Attack Conditions

Mateo Hawkins, Benjamin Johnston, Abhay Nair, Leif Vega
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GeoWorldSim: Cross-Modal Geographic World Modeling for Embodied Urban Navigation via Diffusion-Based Spatial Scene Generation

Karan Dutta, Leif R. Mills, Pascal Terry
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Federated Reinforcement Planning for Privacy-Preserving Collaborative Large Language Model Agents

Ruinan Wan, Brendan Lyons
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Graph-Enhanced Clinical Knowledge Injection for Secure and Robust Medical LLM Reasoning

Tobias D. Greene, Zixuanan Wan, Ananya M. Chopra, Kiran Chatterjee
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NeuroSymbolic Clinical Decision Agents with Fast Reactive Policies and Slow Diagnostic Reasoning

Lucas Bailey, Kiran Mishra
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Physics-Guided Multi-Agent Trajectory Prediction with Adaptive Fused Graph Neural Architectures

Jeffrey C. Phillips, Mateo Thornton, Cody Wolfe, Tongjing Wan
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Multi-Modal Robotic World Modeling via Physically Consistent Video Generation and Cross-View Representation Alignment

Lars D. Welch, Sven Watkins, Tarun M. Raman, Massimo Wagner
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Joint Endmember Representation and Abundance Mapping for Hyperspectral Image Analysis

Terry D. Peters, Gaurav Bhatia
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NeuroSymbolic Safety Routing for Explainable Scientific Foundation Models under Uncertain Knowledge Conditions

Jiangyi Yin
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PathGuard-Med: Interpretable Safety Alignment for Clinical Large Language Models via Multi-Hop Reasoning Intervention

Jakub L. Rao
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SafePath-RL: Risk-Constrained Reinforcement Learning with Deliberative Reasoning for Autonomous Decision Agents

Arthur C. Beck
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