What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Optics
- Telecommunications
Kun Xu mainly investigates Optics, Optical fiber, Optoelectronics, Artificial intelligence and Photonics.
His research integrates issues of Optical Carrier transmission rates, Radio frequency, Signal and Phase modulation in his study of Optics.
His research in Optical fiber intersects with topics in Phase, Dynamic range and Interferometry.
His Optoelectronics study integrates concerns from other disciplines, such as Polarization and Hexagonal lattice.
His studies in Artificial intelligence integrate themes in fields like Multimedia and Natural language processing.
Kun Xu combines subjects such as Broadband, Microwave and Optical filter with his study of Photonics.
His most cited work include:
- Significantly enhanced energy storage performance promoted by ultimate sized ferroelectric BaTiO3 fillers in nanocomposite films (188 citations)
- Question Answering on Freebase via Relation Extraction and Textual Evidence (174 citations)
- Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling (158 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Optics, Electronic engineering, Photonics, Optoelectronics and Optical fiber.
His work carried out in the field of Optics brings together such families of science as Microwave, Modulation and Phase modulation.
His research in Modulation tackles topics such as Intermodulation which are related to areas like Digital signal processing.
His Electronic engineering research is multidisciplinary, incorporating elements of Radio frequency and Transmission, Radio over fiber.
Kun Xu has researched Photonics in several fields, including Optical filter and Signal processing.
His study in Optoelectronics is interdisciplinary in nature, drawing from both Polarization, Band-pass filter and Mode-locking, Laser.
He most often published in these fields:
- Optics (48.57%)
- Electronic engineering (24.91%)
- Photonics (17.38%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (7.89%)
- Natural language processing (5.73%)
- Optics (48.57%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Natural language processing, Optics, Artificial neural network and Electronic engineering.
His Artificial intelligence research incorporates themes from Structure and Machine learning.
His Natural language processing research includes themes of Embedding and Word.
His Optics study frequently draws connections to other fields, such as Optical Carrier transmission rates.
His work focuses on many connections between Artificial neural network and other disciplines, such as Photonics, that overlap with his field of interest in Radio frequency.
His study looks at the intersection of Electronic engineering and topics like Signal processing with Radio over fiber and Modulation.
Between 2018 and 2021, his most popular works were:
- Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network (59 citations)
- Machine learning in materials science (52 citations)
- DurIAN: Duration Informed Attention Network For Multimodal Synthesis. (41 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Optics
- Quantum mechanics
His primary areas of study are Artificial intelligence, Natural language processing, Artificial neural network, Graph and Theoretical computer science.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Multimedia.
His Natural language processing research integrates issues from Representation, Embedding, Structure and Categorization.
His Artificial neural network research is multidisciplinary, relying on both Dynamic range, Wideband, Genetic algorithm, Nonlinear distortion and Distortion.
His Graph research is multidisciplinary, incorporating perspectives in Commonsense knowledge, Natural language and Conceptualization.
His Theoretical computer science research focuses on Cross lingual and how it connects with Data mining.
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