What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His main research concerns Artificial intelligence, Data mining, Cluster analysis, Pattern recognition and Machine learning.
His study in Data mining is interdisciplinary in nature, drawing from both Graph, Gene, Outlier and Data set.
The study incorporates disciplines such as Genetics, Scalability and Set in addition to Data set.
His Cluster analysis study integrates concerns from other disciplines, such as Gene chip analysis, Algorithm and Feature vector.
Aidong Zhang interconnects Feature and Image retrieval in the investigation of issues within Pattern recognition.
His work deals with themes such as Biomolecule, Similarity, Selection bias and Protein protein interaction network, which intersect with Machine learning.
His most cited work include:
- Cluster analysis for gene expression data: a survey (1029 citations)
- WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases (658 citations)
- WaveCluster: a wavelet-based clustering approach for spatial data in very large databases (210 citations)
What are the main themes of his work throughout his whole career to date?
Aidong Zhang focuses on Artificial intelligence, Data mining, Machine learning, Cluster analysis and Pattern recognition.
His research combines Computer vision and Artificial intelligence.
His studies examine the connections between Data mining and genetics, as well as such issues in Gene, with regards to Computational biology.
His research integrates issues of Algorithm and Similarity in his study of Cluster analysis.
His work in Image retrieval covers topics such as Information retrieval which are related to areas like Database and Metadatabase.
Aidong Zhang has researched Image texture in several fields, including Automatic image annotation, Feature detection and Visual Word.
He most often published in these fields:
- Artificial intelligence (42.56%)
- Data mining (29.29%)
- Machine learning (23.11%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (42.56%)
- Machine learning (23.11%)
- Deep learning (5.72%)
In recent papers he was focusing on the following fields of study:
Aidong Zhang mainly investigates Artificial intelligence, Machine learning, Deep learning, Pattern recognition and Data mining.
His research in Artificial intelligence intersects with topics in Functional magnetic resonance imaging and Natural language processing.
His studies deal with areas such as Observational study, Task and Metric as well as Machine learning.
His work carried out in the field of Deep learning brings together such families of science as Health informatics, Set and Task.
His Data mining research integrates issues from Cluster analysis, Gene interaction, Modular design, Ppi network and Community structure.
He works in the field of Cluster analysis, namely Eigengap.
Between 2015 and 2021, his most popular works were:
- A Multi-View Deep Learning Framework for EEG Seizure Detection (53 citations)
- A Correlated Topic Model Using Word Embeddings (53 citations)
- Representation Learning for Treatment Effect Estimation from Observational Data (51 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Artificial intelligence, Machine learning, Deep learning, Feature extraction and Pattern recognition are his primary areas of study.
Aidong Zhang has included themes like Domain and Natural language processing in his Artificial intelligence study.
His Machine learning research incorporates elements of Similarity, Training set and Task.
His studies in Deep learning integrate themes in fields like Artificial neural network, Health informatics and Health records.
His study looks at the intersection of Feature extraction and topics like Electroencephalography with Spectrogram.
The Ranking study which covers Pairwise comparison that intersects with Cluster analysis.
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