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Author

Harsh Verma

23 papers indexed here

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Conference Open access Sep 2026

Beyond Models: Building Trusted AI in the Age of Autonomous Agents

This presentation introduces the emerging paradigm of multi-agentic AI in cybersecurity, where systems evolve from passive tools to autonomous decision-making entities. This explores the rise of agentic AI and its transformative impact on modern cybersecurity. As AI systems evolve from assistive tools into autonomous a...

Harsh Verma · 0 citations
#machine learning Conference Jan 2024

An Analysis of Object Detection in Bad Weather Conditions using Deep Learning Models

Object detection, a task, in the field of computer vision faces obstacles when dealing with weather conditions such as fog, rain, snow, and low light situations. This paper provides an overview of advancements in the realm of object detection under challenging weather conditions. It delves into groundbreaking research...

Janvi Verma, Harsh Verma, Supriya Raheja · 1 citation
#machine learning Conference Jun 2024

Exploring the Landscape of Cloud Robotics: A Comprehensive Review

Cloud robotics is an innovative field that leverages cloud technologies-including cloud computing (CC), cloud storage, deep learning, big data, and the Internet of Things to augment the capabilities of robotics. This integration facilitates the execution of robotic functions through a converged infrastructure and share...

Shahnawaz Ahmad, Shahadat Hussain, Khalid Anwar et al. · 2 citations

Future Trends in AI, Machine Learning, and Big Data: Implications for Technical Leadership

There's no denying that Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies are profoundly changing the face of software engineering and organizational leadership. As these technologies keep evolving, the design, deployment, and management of software systems are undergoing unprecedented chan...

Harsh Verma · 1 citation
#data science Open access Apr 2024

Autonomous Multi-Agent Systems for Enterprise Decision-Making

An integrated conceptual framework is presented which maps layers of the MAS architecture to decision postures in the enterprise, a cross domain performance synthesis, and a research agenda for the next generation of enterprise-scale autonomous agent systems are presented.

Harsh Verma · 0 citations
#artificial intelligence Open access Nov 2024

AI Agentic Architectures for Autonomous Data Engineering Pipelines

This study delves into the notion of AI agentic architectures for autonomous data engineering pipelines and investigates the potential benefits of intelligent agents in enhancing automation, resilience, and decision-making processes in contemporary data ecosystems.

Harsh Verma · 0 citations
#artificial intelligence Open access Jun 2025

Economic impact and productivity modeling of AI agents

The paper provides a comprehensive analytical tool to make sense of micro and macro evidence, unpacks scenarios when AI agents will drive inclusive productivity growth, and outlines a policy roadmap focused on complementary investments, incentives for task-redesign, and workforce transition support measures.

Harsh Verma · 1 citation
#machine learning Open access 2025

Policy Drift in Learning AI Agents: A Dynamical Systems Perspective on Security Degradation

Policy drift takes shape through a nonlinear differential equation - framed within the policy state space - with support from Lyapunov stability concepts alongside bifurcation methods alongside bifurcation methods, and the Intent Drift Rate appears: a concrete number per dialogue turn built as the time-based change in...

Harsh Verma · 1 citation
#natural language process... Open access Mar 2025

Agentic workflows for end-to-end software engineering automation

This conceptual paper theorizes agentic workflows systems, where an AI agent or agents proactively perceive, plan, act and reflect throughout the entire software development lifecycle (SDLC); its implications for end to end software engineering automation are discussed.

Harsh Verma · 1 citation
#artificial intelligence Review Open access Sep 2025

AI-driven cybersecurity in software engineering

AI-driven cybersecurity in the software engineering field is discussed, where machine learning, deep learning, natural language processing, and reinforcement learning can be applied throughout the software development lifecycle to provide increased security.

Harsh Verma · 0 citations

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