Ping Wang

Associate Professor

York University

Canada

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Ping Wang is an Associate Professor at York University in Canada. His research areas include the integration of generative AI with the Internet of Things, deep reinforcement learning, and optimization techniques for vehicle routing and edge caching. He has authored several articles focusing on advanced machine learning methods and their applications in network management and anomaly detection.

Ping Wang

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Articles (20)

Over-the-Air FEEL With Integrated Sensing: Joint Scheduling and Beamforming Design

Guest Editorial Special Issue on Integration of Generative AI and Internet of Things

Service Function Chain Deployment With VNF-Dependent Software Migration in Multi-Domain Networks

Multiobjective Vehicle Routing Optimization With Time Windows: A Hybrid Approach Using Deep Reinforcement Learning and NSGA-II

DRL-AdCAR: Adaptive Coding-Aware Routing With Maximum Coding Opportunities and High-Quality via Deep Reinforcement Learning in FANET

Attention-Enhanced Prioritized Proximal Policy Optimization for Adaptive Edge Caching

Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey

Edge Caching Optimization With PPO and Transfer Learning for Dynamic Environments

Joint Energy and Computation Workload Management for Geo-distributed Data Centers

Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel Noises

Dense Skip Attention Based Deep Learning for Day-Ahead Electricity Price Forecasting

Mobile Charging Services for the Internet of Electric Vehicles: Concepts, Scenarios, and Challenges

Providing Active Charging Services: An Assignment Strategy with Profit-Maximizing Heat Maps for Idle Mobile Charging Stations

A Deep Reinforcement Learning-Based Caching Strategy for IoT Networks With Transient Data

A Data-Driven Packet Routing Algorithm for an Unmanned Aerial Vehicle Swarm: A Multi-Agent Reinforcement Learning Approach

Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data

Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles With Joint Radar-Data Communications

A Novel ASAPPP Approach to Characterize the SIR Distribution in General Cellular Networks

Hierarchical Blockchain Design for Distributed Control and Energy Trading Within Microgrids

Joint Video Packet Assignment, Power Control and User Scheduling Over Cognitive Multi-Homing Heterogeneous NOMA Networks

Collaborators (2)

Hina Tabassum

Mostafa Fouda

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