Area of research
Computer Networks and Communications · Artificial Intelligence
Research interest
Research interests include Caching and Content Delivery, Cooperative Communication and Network Coding, Opportunistic and Delay-Tolerant Networks, and Stochastic Gradient Optimization Techniques.
Communication-Efficient Hierarchical Secure Aggregation with Cyclic User Association
Physics-Informed Generalizable Wireless Channel Modeling with Segmentation and Deep Learning: Fundamentals, Methodologies, and Challenges
The Capacity Region of Information Theoretic Secure Aggregation With Uncoded Groupwise Keys
Federated Learning with Flexible Control
SlimFL: Federated Learning With Superposition Coding Over Slimmable Neural Networks
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
A Combinatorial Design for Cascaded Coded Distributed Computing on General Networks
Combination Networks With End-User-Caches: Novel Achievable and Converse Bounds Under Uncoded Cache Placement
Coded Distributed Computing with Heterogeneous Function Assignments
Optimal Throughput-Outage Analysis of Cache-Aided Wireless Multi-Hop D2D Networks
Markov Decision Policies for Dynamic Video Delivery in Wireless Caching Networks
Cascaded Coded Distributed Computing on Heterogeneous Networks
A New Combinatorial Design of Coded Distributed Computing
Order-Optimal Rate of Caching and Coded Multicasting With Random Demands
Wireless Multihop Device-to-Device Caching Networks
Caching and Coded Multicasting in Slow Fading Environment
Fundamental Limits of Caching in Wireless D2D Networks
Collaborative Research: CIRC: Dev: UnionLabs: Facilitating Shared Access to Heterogeneous Wireless Testbeds Through Grassroots-Driven Federation
CAREER: Heterogeneous Elastic Computing over the Cloud - from Theory to Practice
Collaborative Research: U.S.-Ireland R&D Partnership: Integrated Sensing and Telecommunications for Intelligent Connection and Transmission (INSTINCT)
Collaborative Research: CIF: Medium: Fundamental Limits of Cache-aided Multi-user Private Function Retrieval
Collaborative Research: CIF: Medium: Fundamental Limits of Cache-aided Multi-user Private Function Retrieval
CAREER: Heterogeneous Elastic Computing over the Cloud - from Theory to Practice
CIF: Small: Fundamental Limits of Caching Networks with General Topologies