GDE: a distributed gradient-based algorithm for distance estimation in large-scale networks. - Qingzhi Liu; Andrei Pruteanu; Stefan Dulman (MSWiM, 2011)

Adaptive Online Estimation of Temporal Connectivity in Dynamic Wireless Networks. - Venkat Iyer; Qingzhi Liu; Stefan Dulman; Koen Langendoen (SASO, 2013)

Gradient-Based Distance Estimation for Spatial Computers. - Qingzhi Liu; Andrei Pruteanu; Stefan Dulman (Comput. J., 2013)

Request driven social sensing. - Thomas Christopher King; Qingzhi Liu; Gleb Polevoy; Mathijs de Weerdt; Virginia Dignum; M. Birna van Riemsdijk; Martijn Warnier (AAMAS, 2014)

BLISP: Enhancing backscatter radio with active radio for computational RFIDs. - Ivar in 't Veen; Qingzhi Liu; Przemyslaw Pawelczak; Aaron N. Parks; Joshua R. Smith 001 (IEEE RFID, 2016)

Safe and secure wireless power transfer networks: challenges and opportunities in RF-based systems. - Qingzhi Liu; Kasim Sinan Yildirim; Przemyslaw Pawelczak; Martijn Warnier (IEEE Commun. Mag., 2016)

Green Wireless Power Transfer Networks. - Qingzhi Liu; Michal Golinski; Przemyslaw Pawelczak; Martijn Warnier (IEEE J. Sel. Areas Commun., 2016)

WiPLoc: Perpetual Indoor Localization with RF Wireless Power Transfer. - Qingzhi Liu; Wieger IJntema; Anass Drif; Przemyslaw Pawelczak; Marco Zuniga (CoRR, 2017)

The Ontology of Biological and Clinical Statistics (OBCS)-based statistical method standardization and meta-analysis of host responses to yellow fever vaccines. - Jie Zheng 001; Huan Li; Qingzhi Liu; Yongqun He (Quant. Biol., 2017)

Minimizing Network Traffic for Distributed Joins Using Lightweight Locality-Aware Scheduling. - Long Cheng 003; John Murphy 001; Qingzhi Liu; Chunliang Hao; Georgios Theodoropoulos 001 (Euro-Par, 2018)

Deep Reinforcement Learning for IoT Network Dynamic Clustering in Edge Computing. - Qingzhi Liu; Long Cheng 003; Tanir Ozcelebi; John Murphy 001; Johan Lukkien (CCGRID, 2019)

PCANN: Distributed ANN Architecture for Image Recognition in Resource-Constrained IoT Devices. - Tianyu Bi; Qingzhi Liu; Tanir Ozcelebi; Dmitri Jarnikov; Dragan Sekulovski (Intelligent Environments, 2019)

Performance Evaluation of Thread Protocol based Wireless Mesh Networks for Lighting Systems. - Srikanth Sistu; Qingzhi Liu; Tanir Ozcelebi; Esko Dijk; Teresa Zotti (ISNCC, 2019)

Learning Process Models in IoT Edge. - Long Cheng 003; Cong Liu 003; Qingzhi Liu; Yucong Duan; John Murphy 001 (SERVICES, 2019)

CluFlow: Cluster-based Flow Management in Software-Defined Wireless Sensor Networks. - Qingzhi Liu; Tanir Ozcelebi; Long Cheng 003; Fernando A. Kuipers; Johan Lukkien (WCNC, 2019)

BEH: Indoor Batteryless BLE Beacons using RF Energy Harvesting for Internet of Things. - Qingzhi Liu; Wieger IJntema; Anass Drif; Przemyslaw Pawelczak; Marco Zuniga (CoRR, 2019)

Load-balancing distributed outer joins through operator decomposition. - Long Cheng 003; Spyros Kotoulas; Qingzhi Liu; Ying Wang 001 (J. Parallel Distributed Comput., 2019)

A Novel Multiuser UWB Ranging Scheme in NLOS Indoor Environment. - Qingzhi Liu; Zhilu Wu; Zhendong Yin; Mingyang Wu; Bo Ma (ICT, 2020)

Network-Based Matching of Patients and Targeted Therapies for Precision Oncology. - Qingzhi Liu; Min Jin Ha; Rupam Bhattacharyya 002; Lana X. Garmire; Veerabhadran Baladandayuthapani (PSB, 2020)

cRisk Analysis of Cash on Delivery Payment Method by Social Network Analysis and Fuzzy Petri Net. - Lei Yu 016; Qingzhi Liu; Rong Hua; You Fu (IEEE Access, 2020)

Resource Management Schemes for Cloud-Native Platforms with Computing Containers of Docker and Kubernetes. - Ying Mao 001; Yuqi Fu; Suwen Gu; Sudip Vhaduri; Long Cheng 003; Qingzhi Liu (CoRR, 2020)

Differentiate Quality of Experience Scheduling for Deep Learning Applications with Docker Containers in the Cloud. - Ying Mao 001; Weifeng Yan; Yun Song; Yue Zeng; Ming Chen; Long Cheng 003; Qingzhi Liu (CoRR, 2020)

A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems. - Xuan Chen; Long Cheng 003; Cong Liu 012; Qingzhi Liu; Jinwei Liu; Ying Mao 001; John Murphy 001 (IEEE Syst. J., 2020)

Cluster-based flow control in hybrid software-defined wireless sensor networks. - Qingzhi Liu; Long Cheng 003; Renan C. A. Alves; Tanir Ozcelebi; Fernando A. Kuipers; Guixian Xu; Johan Lukkien; Shanzhi Chen (Comput. Networks, 2021)

A change domain-based model repair method via Petri nets. - Lei Yu 016; Qingzhi Liu; Rong Hua; You Fu (Trans. Emerg. Telecommun. Technol., 2021)

Deep Reinforcement Learning for Communication Flow Control in Wireless Mesh Networks. - Qingzhi Liu; Long Cheng 003; Adele Lu Jia; Cong Liu 012 (IEEE Netw., 2021)

Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers. - Long Cheng 003; Ying Wang 001; Qingzhi Liu; Dick H. J. Epema; Cheng Liu 008; Ying Mao 001; John Murphy 001 (IEEE Trans. Parallel Distributed Syst., 2021)

LSTM Network-based SNR Estimator for DS-UWB Wireless Sensor Network. - Qingzhi Liu; Zhendong Yin; Mingyang Wu; Zhilu Wu; Zhijiang Xu (DSA, 2022)

Performance Evaluation of Resource Management Schemes for Cloud Native Platforms with Computing Containers. - Yuqi Fu; Naseem Machlovi; Ying Mao 001; Jiayin Wang; Long Cheng 003; Qingzhi Liu (IPCCC, 2022)

UWB LOS/NLOS identification in multiple indoor environments using deep learning methods. - Qingzhi Liu; Zhendong Yin; Yanlong Zhao; Zhilu Wu; Mingyang Wu (Phys. Commun., 2022)

Speculative Container Scheduling for Deep Learning Applications in a Kubernetes Cluster. - Ying Mao 001; Yuqi Fu; Wenjia Zheng; Long Cheng 003; Qingzhi Liu; Dingwen Tao (IEEE Syst. J., 2022)

MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems. - Mingming Liu 001; Long Cheng 003; Yingqi Gu; Ying Wang 001; Qingzhi Liu; Noel E. O'Connor (IEEE Trans. Intell. Transp. Syst., 2022)

Deep Reinforcement Learning for Load-Balancing Aware Network Control in IoT Edge Systems. - Qingzhi Liu; Tiancong Xia; Long Cheng 003; Merijn van Eijk; Tanir Ozcelebi; Ying Mao 001 (IEEE Trans. Parallel Distributed Syst., 2022)

BSAS: A Blockchain-Based Trustworthy and Privacy-Preserving Speed Advisory System. - Jianbin Li; Shike Li; Long Cheng 003; Qingzhi Liu; Jiaming Pei; Shen Wang 006 (IEEE Trans. Veh. Technol., 2022)

Securing the Internet of Things Network using a Hierarchical Hyperledger Fabric Model. - Mohammed Ahmad Abuhaliqa; Cagatay Catal; Qingzhi Liu (MetaCom, 2023)

A similarity-enhanced hybrid group recommendation approach in cloud manufacturing systems. - Jian Liu; Youling Chen; Qingzhi Liu; Bedir Tekinerdogan (Comput. Ind. Eng., 2023)

Deep-Learning-Based Rice Phenological Stage Recognition. - Jiale Qin; Tianci Hu; Jianghao Yuan; Qingzhi Liu; Wensheng Wang; Jie Liu; Leifeng Guo; Guozhu Song (Remote. Sens., 2023)

Differentiate Quality of Experience Scheduling for Deep Learning Inferences With Docker Containers in the Cloud. - Ying Mao 001; Weifeng Yan; Yun Song; Yue Zeng; Ming Chen; Long Cheng 003; Qingzhi Liu (IEEE Trans. Cloud Comput., 2023)

Boosting the prediction accuracy of a process-based greenhouse climate-tomato production model by particle filtering and deep learning. - Xiaohan Zhou; Qingzhi Liu; David Katzin; Tian Qian; Ep Heuvelink; Leo F. M. Marcelis (Comput. Electron. Agric., 2023)

Accelerating Scientific Computing Kernels by Fusing the Polyhedral and Tensor Compilers. - Qingzhi Liu; Changbo Chen; Hanwen Dai (Euro-Par Workshops (1), 2024)

MARS: Multi-Agent Deep Reinforcement Learning for Real-Time Workflow Scheduling in Hybrid Clouds with Privacy Protection. - Long Cheng 003; Haoyang He; Yan Gu; Qingzhi Liu; Zhiming Zhao; Fang Fang 007 (ICPADS, 2024)

Comprehensive analysis of hyperspectral features for monitoring canopy maize leaf spot disease. - Yali Bai; Chenwei Nie; Xun Yu; Mingyue Gou; Shuaibing Liu; Yanqin Zhu; Tiantian Jiang; Xiao Jia 017; Yadong Liu; Fei Nan; Liming Li; Bedir Tekinerdogan; et al. (Comput. Electron. Agric., 2024)

Use Self-Training Random Forest for Predicting Winter Wheat Yield. - Yulin Shen; Benoît Mercatoris; Qingzhi Liu; Hongxun Yao; Zongpeng Li; Zhen Chen; Wensheng Wang (Remote. Sens., 2024)

Crop Classification from Drone Imagery Based on Lightweight Semantic Segmentation Methods. - Zuojun Zheng; Jianghao Yuan; Wei Yao; Hongxun Yao; Qingzhi Liu; Leifeng Guo (Remote. Sens., 2024)

Explainable and Effective Process Remaining Time Prediction Using Feature-Informed Cascade Prediction Model. - Na Guo; Cong Liu 012; Caihong Li; Qingtian Zeng; Chun Ouyang 001; Qingzhi Liu; Xixi Lu 001 (IEEE Trans. Serv. Comput., 2024)

Advancements in Accelerating Deep Neural Network Inference on AIoT Devices: A Survey. - Long Cheng 003; Yan Gu; Qingzhi Liu; Lei Yang 018; Cheng Liu 008; Ying Wang 001 (IEEE Trans. Sustain. Comput., 2024)

CASA: cost-effective EV charging scheduling based on deep reinforcement learning. - Ao Zhang; Qingzhi Liu; Jinwei Liu; Long Cheng 003 (Neural Comput. Appl., 2024)

Guest Editorial of the Special Section on Intelligent Computing for Big Data in Consumer Internet of Things. - Long Cheng 003; Qingzhi Liu; Lei Yang 018; John Murphy 001 (IEEE Trans. Consumer Electron., 2024)

Privacy and Integrity Protection for IoT Multimodal Data Using Machine Learning and Blockchain. - Qingzhi Liu; Yuchen Huang; Chenglu Jin; Xiaohan Zhou; Ying Mao 001; Cagatay Catal; Long Cheng 003 (ACM Trans. Multim. Comput. Commun. Appl., 2024)

Deep reinforcement learning for optimal microgrid energy management with renewable energy and electric vehicle integration. - Baoyin Xiong; Lili Zhang 012; Yang Hu 009; Fang Fang 007; Qingzhi Liu; Long Cheng 003 (Appl. Soft Comput., 2025)

Plant stem occlusion inpainting with Deep Reinforcement Learning. - Yameng Jiang; Qingzhi Liu; Wei Lu; Bo Zhou; Katarína Smolenová; Bedir Tekinerdogan; Qichang Yang (Comput. Electron. Agric., 2025)

Fusing the Polyhedral and Tensor Compilers to Accelerate Scientific Computing Kernels. - Qingzhi Liu; Changbo Chen; Hanwen Dai (Concurr. Comput. Pract. Exp., 2025)

Job Scheduling in Hybrid Clouds With Privacy Constraints: A Deep Reinforcement Learning Approach. - Haoyang He; Yan Gu; Qingzhi Liu; Hao Wu; Long Cheng 003 (Concurr. Comput. Pract. Exp., 2025)

Trustworthy AI Psychotherapy: Multi-Agent LLM Workflow for Counseling and Explainable Mental Disorder Diagnosis. - Mithat Can Ozgun; Jiahuan Pei; Koen Hindriks; Lucia Donatelli; Qingzhi Liu; Junxiao Wang (CoRR, 2025)