Peer-reviewed papers and major-trade-publication articles.
Peer-reviewed papers
10 papers
Published2026
PatternForge: A Multi-Agent Generative AI Framework for Catalog-Driven Orchestration
ECAI 2026 — 18th International Conference on Electronics, Computers and Artificial Intelligence · IEEE Xplore
IEEE peer-reviewed conference. Published in IEEE Xplore (Aug 2026).
Shikher Goel and co-authors
ECAI 2026 · Submission #6585
Proposes a catalog-driven orchestration framework for multi-agent generative AI systems. Treats reusable orchestration patterns as first-class artefacts that downstream agents instantiate, compose, and reason about under enterprise governance.
PolicyAgent: A Multi-Agent Generative AI Framework for Automated Reasoning Checks
ECAI 2026 — 18th International Conference on Electronics, Computers and Artificial Intelligence · IEEE Xplore
IEEE peer-reviewed conference. Published in IEEE Xplore (Aug 2026).
Shikher Goel and co-authors
ECAI 2026 · Submission #4495
Introduces a policy-aware multi-agent layer that performs automated reasoning checks over enterprise AI workflows. Agents evaluate proposed actions against codified policy, surface violations, and provide auditable rationale before downstream execution.
Extends generative-AI agents from reactive recovery into predictive remediation and autonomous security enforcement for Infrastructure-as-Code. Proposes a resilience framework that anticipates configuration drift, surfaces security regressions before exploitation, and applies guarded remediations end-to-end across multi-cloud deployments.
Generative AIInfrastructure as CodePredictive remediationAutonomous securityCloud resilience
Introduces an autonomous-agent architecture in which Large Language Model agents continuously monitor Infrastructure-as-Code deployments, detect configuration drift and security misconfigurations in real time, and execute scoped remediations under explicit governance gates. Evaluates the framework on enterprise-cloud workloads where drift and misconfiguration form a leading source of production incidents.
LLM agentsInfrastructure as CodeConfiguration driftCloud securitySelf-healing systems
Defines a multi-agent AI framework that detects deployment-failure precursors across multi-cloud environments and applies autonomous remediations under bounded policy. Presented at ECAI 2026, Bucharest/Pitești (Jul 2–3, 2026); proceedings published in IEEE Xplore.
Applies zero-trust principles to autonomous Infrastructure-as-Code security remediation. A multi-agent architecture verifies every identity, action, and remediation against an explicit trust boundary before execution — translating zero-trust theory into operational IaC controls. Published in IEEE Xplore as part of the ECAI 2026 proceedings.
Multi-agent AIZero trustInfrastructure as CodeAutonomous remediationCloud security
Presents a reference model for embedding agentic AI inside enterprise customer-relationship platforms. Maps a multi-agent architecture onto Salesforce CRM and AWS data-and-integration infrastructure, addressing identity, tool access, governance, and audit boundaries required for regulated deployment.
Compliance-Driven Security Automation in AI-Augmented CI/CD Pipelines
SCI 2026 — 8th International Conference on Smart Computing & Informatics · Springer LNNS
International peer-reviewed conference, proceedings indexed in Springer LNNS and Scopus. Recognised with the Best Paper award (per author notification).
Synthesises CI/CD pipeline architectures for production enterprise platforms operating under SOX, FINRA, and SEC controls. Embeds AI-augmented stages for segregation of duties, automated control-evidence collection, and audit-traceable change management. Lessons drawn from large-scale Salesforce and AWS deployments inside a Global Systemically Important Bank.
A Pattern Catalog for Multi-Agent Generative AI Orchestration Across Enterprise CRM and Hyperscaler Cloud Platforms
IEEE Access — Journal
IEEE peer-reviewed open-access journal (impact-factor indexed). Manuscript Access-2026-28862 submitted 14 Jun 2026; under associate-editor review.
Shikher Goel and co-authors
IEEE Access · MS Access-2026-28862
Curates a pattern catalog for multi-agent generative-AI orchestration spanning enterprise CRM platforms (Salesforce) and hyperscaler cloud (AWS, Azure). Treats each pattern as a reusable, governed unit that practising architects can compose into production systems.
Forbes Technology Council is an invitation-only community of senior technology leaders; Council articles are editorially reviewed by Forbes staff. Shikher was a Council Member during 2025 and authored the pieces below in that capacity; the articles remain published on Forbes.com.
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This page surfaces only formal scholarly venues and major-trade publications. Long-form essays, walkthroughs, and Medium posts are catalogued separately on the Writing page.