ISSN (Online): 2321-3418
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Author Profile

Harsh Verma

Palo Alto Networks
📍 United States

Harsh Verma is a Principal Software Engineer in AI at Palo Alto Networks, focused on advancing autonomous agent systems and intelligent AI strategies. Harsh is also a Forbes Technology Council member and, as a speaker, mentor, and advisor, he brings both technical depth and strategic guidance to leaders adopting next-generation AI capabilities. He drives responsible, scalable AI adoption. His work influences how enterprises innovate, secure, and operationalize the next generation of intelligent systems. Harsh specializes in offering scalable AI solutions, mentoring aspiring entrepreneurs, delivering impactful conference talks, and advising startups on their AI strategies. Whether it's navigating AI implementation or fostering innovation with AI, Harsh is committed to delivering meaningful results in the tech industry. His contributions have been recognized through globally respected awards and institutions, reinforcing both impact and influence. He is a recipient of the Global Recognition Award (2026) for measurable advances in enterprise AI and cybersecurity, and also the Globee Awards, which recognize excellence & innovation across global business leadership. He acts as a Senior Member of IEEE, which reflects peer-reviewed recognition of his sustained technical and professional contributions to the field, an honor reserved for individuals demonstrating significant performance and impact. Beyond the enterprise, Harsh is actively shaping the broader Data & AI ecosystem. Through mentorship at leading accelerators like UC Berkeley Skydeck, judging global AI innovation forums, and publishing thought leadership in Forbes and HackerNoon as a Technical Council Member, he helps shape how AI leadership is evolving. His work influences not only the organizations he serves but also the next generation of AI systems, leaders, and standards.

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9Publications
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📊 Impact Overview
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📥 Downloads & Citations per Year
Publications (9)
1
Security in Multi-Agent AI Systems: Modeling Emergent Vulnerabilities via Trust Graphs
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 14, No. 04pp. 2863-2874🗓 Jul 2026DOI ↗
0 views162 downloads
2
Clean Attacks: Formalizing Semantically Valid Adversarial Behavior in Autonomous AI Agent Systems
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 13, No. 10pp. 2623-2630🗓 Jul 2026DOI ↗
0 views296 downloads
3
Toward a Unified Security Systems Theory for Autonomous AI Systems
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 14, No. 06pp. 2925-2930🗓 Jun 2026DOI ↗
0 views66 downloads
4
Designing Self-Healing AI Agentic Systems: A Framework for Autonomous Detection and Response
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 14, No. 06pp. 2912-2924🗓 Jun 2026DOI ↗
0 views475 downloads
5
Intent-Based Security: Replacing Identity-Centric Trust in Autonomous AI Agentic Systems
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 14, No. 02pp. 2771-2778🗓 Feb 2026DOI ↗
0 views87 downloads
6
Adversarial Machine Learning: Security Risks and Defense Strategies in AI-Driven Applications
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 14, No. 02pp. 2779-2788🗓 Feb 2026DOI ↗
0 views48 downloads
7
Secure AI Systems Protecting Machine Learning Models from Emerging Cyber Threats
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 13, No. 10pp. 2631-2642🗓 Oct 2025DOI ↗
0 views41 downloads
8
Policy Drift in Learning AI Agents: A Dynamical Systems Perspective on Security Degradation
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 13, No. 07pp. 2457-2464🗓 Jul 2025DOI ↗
0 views76 downloads
9
AI-Powered Anomaly Detection in Cloud-Based Applications
📖 International Journal of Scientific Research and Management (IJSRM)Vol. 12, No. 01pp. 1102-1114🗓 Jan 2024DOI ↗
0 views23 downloads