Dinesh Verma

About

Dinesh Verma is a leading researcher at the intersection of artificial intelligence, cybersecurity, and distributed systems. His work focuses on making complex, autonomous systems—from IoT sensor networks to robotic swarms—both intelligent and secure. Verma’s major contributions are twofold. First, he pioneered techniques for **efficient edge computing**, demonstrating how to prune deep convolutional neural networks to run sophisticated infrastructure assessments directly on resource-constrained devices, a paper that has garnered 99 citations. Second, he is a driving force in **policy-based management**, authoring a highly cited (51 citations) foundational work on tools for analyzing and maintaining reliable policy systems in large-scale, autonomous environments. More recently, Verma has advanced the field with **FLAP**, a novel federated learning framework that enables secure, attribute-based access control policies for collaborative applications. This work addresses the critical challenge of enabling information sharing while protecting data flow. Through his research, Verma is building the essential trust and efficiency frameworks needed for the next generation of autonomous, collaborative systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures

   99 citations · 2019
2. 2
   Methods and Tools for Policy Analysis

   51 citations · 2019
3. 3
   FLAP - A Federated Learning Framework for Attribute-based Access Control Policies

   10 citations · 2023
4. 4
   FLAP -- A Federated Learning Framework for Attribute-based Access Control Policies

   3 citations · 2020

Key Collaborators

Contact & Links