Sicong Liu

Orcid: 0000-0003-4402-1260

Affiliations:
  • Northwestern Polytechnical University, School of Computer Science and Engineering, Xi'an, China
  • Xidian University, School of Computer Science and Technology, Xi'an, China (PhD 2020)


According to our database1, Sicong Liu authored at least 46 papers between 2014 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
CrowdHMTware: A Cross-Level Co-Adaptation Middleware for Context-Aware Mobile DL Deployment.
IEEE Trans. Mob. Comput., August, 2025

AdaScale: Dynamic Context-Aware DNN Scaling via Automated Adaptation Loop on Mobile Devices.
IEEE Internet Things J., June, 2025

AdaEvo: Edge-Assisted Continuous and Timely DNN Model Evolution for Mobile Devices.
IEEE Trans. Mob. Comput., April, 2025

ClassTer: Mobile Shift-Robust Personalized Federated Learning via Class-Wise Clustering.
IEEE Trans. Mob. Comput., March, 2025

DeepSwarm: towards swarm deep learning with bi-directional optimization of data acquisition and processing.
Frontiers Comput. Sci., March, 2025

AdaKnife: Flexible DNN Offloading for Inference Acceleration on Heterogeneous Mobile Devices.
IEEE Trans. Mob. Comput., February, 2025

SURGEON: Memory-Adaptive Fully Test-Time Adaptation via Dynamic Activation Sparsity.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
CrowdLearning: A Decentralized Distributed Training Framework Based on Collectives of Trusted AIoT Devices.
IEEE Trans. Mob. Comput., December, 2024

Size Matters: Characterizing the Effect of Target Size on Wi-Fi Sensing Based on the Fresnel Zone Model.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., November, 2024

UbiHR: Resource-efficient Long-range Heart Rate Sensing on Ubiquitous Devices.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., November, 2024

EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2024

AdaMEC: Towards a Context-adaptive and Dynamically Combinable DNN Deployment Framework for Mobile Edge Computing.
ACM Trans. Sens. Networks, January, 2024

AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control.
CoRR, 2024

AdaBridge: Dynamic Data and Computation Reuse for Efficient Multi-task DNN Co-evolution in Edge Systems.
CoRR, 2024

Enabling Resource-Efficient AIoT System With Cross-Level Optimization: A Survey.
IEEE Commun. Surv. Tutorials, 2024

AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control.
Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024

AdaShadow: Responsive Test-time Model Adaptation in Non-stationary Mobile Environments.
Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024

Deep Learning Inference on Heterogeneous Mobile Processors: Potentials and Pitfalls.
Proceedings of the 2024 Workshop on Adaptive AIoT Systems, 2024

AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices.
Proceedings of the 2024 Workshop on Adaptive AIoT Systems, 2024

2023
Genie in the Model: Automatic Generation of Human-in-the-Loop Deep Neural Networks for Mobile Applications.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2023

A Novel Framework for Adaptive Quadruped Robot Locomotion Learning in Uncertain Environments.
Proceedings of the Green, Pervasive, and Cloud Computing - 18th International Conference, 2023

MoEnlight: Energy-efficient and self-adaptive Low-light Video Stream Enhancement on Mobile Devices.
Proceedings of the ACM Turing Award Celebration Conference - China 2023, 2023

2022
Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic.
Inf. Process. Manag., 2022

CAQ: Toward Context-Aware and Self-Adaptive Deep Model Computation for AIoT Applications.
IEEE Internet Things J., 2022

CrowdIM: Crowd-Inspired Intelligent Manufacturing Space Design.
IEEE Internet Things J., 2022

CrowdHMT: Crowd Intelligence With the Deep Fusion of Human, Machine, and IoT.
IEEE Internet Things J., 2022

AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022

CrowdDesigner: information-rich and personalized product description generation.
Frontiers Comput. Sci., 2022

Weather-oriented Domain Generalization of Semantic Segmentation for Autonomous Driving.
Proceedings of the IEEE Smartworld, 2022

Context-Adaptive Online Reinforcement Learning for Multi-view Video Summarization on Mobile Devices.
Proceedings of the 28th IEEE International Conference on Parallel and Distributed Systems, 2022

FedAux: An Efficient Framework for Hybrid Federated Learning.
Proceedings of the IEEE International Conference on Communications, 2022

2021
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles.
IEEE Trans. Mob. Comput., 2021

Context-aware Adaptive Surgery: A Fast and Effective Framework for Adaptative Model Partition.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021

AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021

Towards information-rich, logical dialogue systems with knowledge-enhanced neural models.
Neurocomputing, 2021

Decentralized Multi-AGV Task Allocation based on Multi-Agent Reinforcement Learning with Information Potential Field Rewards.
Proceedings of the IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems, 2021

JointCS: Joint Search for Deep Model Compression and Segmentation on Heterogeneous IoT Devices.
Proceedings of the 27th IEEE International Conference on Parallel and Distributed Systems, 2021

TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples.
Proceedings of the 7th International Conference on Big Data Computing and Communications, 2021

2020
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles.
CoRR, 2020

CrowdDepict: Know What and How to Generate Personalized and Logical Product Description using Crowd intelligence.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

2018
On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework.
Proceedings of the 16th Annual International Conference on Mobile Systems, 2018

2017
UbiEar: Bringing Location-independent Sound Awareness to the Hard-of-hearing People with Smartphones.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017

Understanding Sensor Data Using Deep Learning Methods on Resource-Constrained Edge Devices.
Proceedings of the Wireless Sensor Networks, 2017

2016
CrowdBlueNet: Maximizing Crowd Data Collection Using Bluetooth Ad Hoc Networks.
Proceedings of the Wireless Algorithms, Systems, and Applications, 2016

Air pollution source estimation profiling via mobile sensor networks.
Proceedings of the International Conference on Computer, 2016

2014
Lightweight construction of the information potential field in wireless sensor networks.
Proceedings of the 23rd International Conference on Computer Communication and Networks, 2014


  Loading...