Seyyedali Hosseinalipour

Assistant Professor

University at Buffalo

United States

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Seyyedali Hosseinalipour is an Assistant Professor at the University at Buffalo, USA. His research focuses on advanced wireless communication technologies, including the transition from 5G to 6G and innovations in federated learning methodologies. Recent publications highlight his work on UAV-assisted communications, vehicle cloud integration, and resource allocation in dynamic networks. He is also engaged in developing strategies for mobile crowd sensing and image compression techniques.

Articles (27)

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Collaborators (9)

Christopher G. Brinton

Purdue University

UNITED STATES

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Anindya Bijoy Das

Assistant Professor

University of Akron

UNITED STATES

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Jinjun Xiong

Professor

University at Buffalo

UNITED STATES

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Masahiro Fujita

University of Tokyo

JAPAN

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Maria Gorlatova

James N. & Elizabeth H. Barton Associate Professor

Duke University

UNITED STATES

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Nicolo Michelusi

Assistant Professor

Arizona State University

UNITED STATES

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Yun-Wei Chu

Purdue University

UNITED STATES

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James V. Krogmeier

Purdue University

UNITED STATES

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Pubudu Pathirana

Professor

Deakin University

AUSTRALIA

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Seyyedali Hosseinalipour

Research Interests

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Articles (27)

Breaking the Barriers of One-to-One Usage of Implicit Neural Representation in Image Compression: A Linear Combination Approach With Performance Guarantees

A holistic survey of UAV-assisted wireless communications in the transition from 5G to 6G: State-of-the-art intertwined innovations, challenges, and opportunities

Seamless Graph Task Scheduling Over Dynamic Vehicular Clouds: A Hybrid Methodology for Integrating Pilot and Instantaneous Decisions

DNN Partitioning, Task Offloading, and Resource Allocation in Dynamic Vehicular Networks: A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach

Long-Term or Temporary? Hybrid Worker Recruitment for Mobile Crowd Sensing and Computing

Coding for Gaussian Two-Way Channels: Linear and Learning-Based Approaches

Future Resource Bank for ISAC: Achieving Fast and Stable Win-Win Matching for Both Individuals and Coalitions

GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling Over Dynamic Vehicular Clouds

A Decentralized Pilot Assignment Algorithm for Scalable O-RAN Cell-Free Massive MIMO

Asynchronous Multi-Model Dynamic Federated Learning Over Wireless Networks: Theory, Modeling, and Optimization

Delay-Aware Hierarchical Federated Learning

Device Sampling and Resource Optimization for Federated Learning in Cooperative Edge Networks

Energy-Efficient Connectivity-Aware Learning Over Time-Varying D2D Networks

Matching-Based Hybrid Service Trading for Task Assignment Over Dynamic Mobile Crowdsensing Networks

Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics

Multi-Modal Federated Learning for Cancer Staging over Non-IID Datasets with Unbalanced Modalities

Orchestrating Federated Learning in Space-Air- Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover

UAV-Assisted Online Machine Learning Over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach

Decomposition Theory Meets Reliability Analysis: Processing of Computation-Intensive Dependent Tasks Over Vehicular Clouds With Dynamic Resources

Dynamic and Robust Sensor Selection Strategies for Wireless Positioning With TOA/RSS Measurement

Graph-Represented Computation-Intensive Task Scheduling Over Air-Ground Integrated Vehicular Networks

Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point

Parallel Successive Learning for Dynamic Distributed Model Training Over Heterogeneous Wireless Networks

RFID: Towards Low Latency and Reliable DAG Task Scheduling Over Dynamic Vehicular Clouds

Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing

Learning-Based Adaptive IRS Control With Limited Feedback Codebooks

A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions

Collaborators (9)

Christopher G. Brinton

Anindya Bijoy Das

Jinjun Xiong

Masahiro Fujita

Maria Gorlatova

Nicolo Michelusi

Yun-Wei Chu

James V. Krogmeier

Pubudu Pathirana

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