His primary scientific interests are in Distributed computing, Scheduling, Scalability, Data-intensive computing and Dynamic priority scheduling. Dan Chen combines subjects such as Network architecture, Software deployment, Network packet, Cloud computing and High-level architecture with his study of Distributed computing. His Cloud computing study incorporates themes from Petabyte, Reliability, Workflow and Distributed design patterns.
The various areas that Dan Chen examines in his Scheduling study include Supercomputer, HPC Challenge Benchmark and Resource allocation. Dan Chen has researched Scalability in several fields, including Real-time computing, Data transmission and Warning system. His Data-intensive computing research incorporates elements of Data access, Distributed database, Database, Parallel I/O and Big data.
Dan Chen spends much of his time researching Distributed computing, Artificial intelligence, Pattern recognition, General-purpose computing on graphics processing units and Scalability. His studies deal with areas such as Grid computing, Cloud computing, Workflow and High-level architecture as well as Distributed computing. His work in Workflow covers topics such as Data-intensive computing which are related to areas like File system.
His study in the fields of Entropy under the domain of Artificial intelligence overlaps with other disciplines such as Noise. His Pattern recognition research incorporates themes from Artificial neural network, Hyperparameter, Synchronization and Sensitivity. His Graphics processing unit research focuses on Signal processing and how it connects with Hilbert–Huang transform.
His main research concerns Pattern recognition, Artificial intelligence, Reinforcement learning, Synchronization and Cloud computing. His Pattern recognition study integrates concerns from other disciplines, such as Artificial neural network and Sensitivity. Dan Chen interconnects Stability and Discrete system in the investigation of issues within Artificial neural network.
His Bayesian probability, Hyperparameter and Deep learning study in the realm of Artificial intelligence interacts with subjects such as Noise and Sleep disorder. His Reinforcement learning study combines topics in areas such as Vaccination, Bounded rationality and Risk of infection. Many of his research projects under Cloud computing are closely connected to Service level with Service level, tying the diverse disciplines of science together.
Dan Chen focuses on Pattern recognition, Artificial intelligence, Eeg classification, Sensitivity and Bayesian inference. His Pattern recognition study combines topics from a wide range of disciplines, such as Artificial neural network, Bayesian optimization and Hyperparameter. Depression, Thesaurus, Cloud computing, Information retrieval and Performance improvement are fields of study that intersect with his Eeg classification study.
Dan Chen has included themes like Synchronization, Big data and Identification in his Sensitivity study. His Bayesian inference research overlaps with Factorization, Tensor and Rank. Exponential family, GPU cluster, Algorithm, Massively parallel and Time complexity are fields of study that overlap with his Factorization research.
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G-Hadoop: MapReduce across distributed data centers for data-intensive computing
Lizhe Wang;Jie Tao;Rajiv Ranjan;Holger Marten.
Future Generation Computer Systems (2013)
Crowd modeling and simulation technologies
Suiping Zhou;Dan Chen;Wentong Cai;Linbo Luo.
ACM Transactions on Modeling and Computer Simulation (2010)
Energy-aware parallel task scheduling in a cluster
Lizhe Wang;Lizhe Wang;Samee U. Khan;Dan Chen;Joanna KołOdziej.
Future Generation Computer Systems (2013)
Natural Disaster Monitoring with Wireless Sensor Networks: A Case Study of Data-intensive Applications upon Low-Cost Scalable Systems
Dan Chen;Zhixin Liu;Lizhe Wang;Minggang Dou.
Mobile Networks and Applications (2013)
Agent-based human behavior modeling for crowd simulation
Linbo Luo;Suiping Zhou;Wentong Cai;Malcolm Yoke Hean Low.
Computer Animation and Virtual Worlds (2008)
A survey on resource allocation in high performance distributed computing systems
Hameed Hussain;Saif Ur Rehman Malik;Abdul Hameed;Samee Ullah Khan.
parallel computing (2013)
Quantitative comparisons of the state-of-the-art data center architectures
Kashif Bilal;Samee Ullah Khan;Limin Zhang;Hongxiang Li.
Concurrency and Computation: Practice and Experience (2013)
GPGPU-Aided Ensemble Empirical-Mode Decomposition for EEG Analysis During Anesthesia
Dan Chen;Duan Li;Muzhou Xiong;Hong Bao.
international conference of the ieee engineering in medicine and biology society (2010)
A survey on text mining in social networks
Rizwana Irfan;Christine K. King;Daniel Grages;Sam J. Ewen.
Knowledge Engineering Review (2015)
Comparative study of trust and reputation systems for wireless sensor networks
Osman Khalid;Samee Ullah Khan;Sajjad Ahmad Madani;Khizar Hayat.
Security and Communication Networks (2013)
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