What is he best known for?
The fields of study he is best known for:
- Gene
- Artificial intelligence
- Enzyme
Cell biology, Artificial intelligence, Ubiquitin, Fuzzy logic and Ceramic are his primary areas of study.
The Cell biology study combines topics in areas such as Optineurin, BAG3 and Sequestosome-1 Protein.
His study explores the link between Artificial intelligence and topics such as Pattern recognition that cross with problems in Noise, Watermark, JPEG and Filter.
His Ubiquitin study integrates concerns from other disciplines, such as Downregulation and upregulation, HEK 293 cells, Receptor, Receptor complex and Phosphorylation.
His studies deal with areas such as Silicon nitride and Microstructure, Superplasticity as well as Ceramic.
His Metallurgy research includes themes of Charged species and Interlocking.
His most cited work include:
- Formation of tough interlocking microstructures in silicon nitride ceramics by dynamic ripening (390 citations)
- Fuzzy reasoning spiking neural P system for fault diagnosis (141 citations)
- Ubiquitylation of Autophagy Receptor Optineurin by HACE1 Activates Selective Autophagy for Tumor Suppression (136 citations)
What are the main themes of his work throughout his whole career to date?
Hong Peng focuses on Artificial intelligence, Membrane computing, Metallurgy, Fuzzy logic and Topology.
His Artificial intelligence study combines topics from a wide range of disciplines, such as P system and Pattern recognition.
Membrane computing and Cluster analysis are commonly linked in his work.
Metallurgy and Silicon nitride are frequently intertwined in his study.
The Fuzzy reasoning research Hong Peng does as part of his general Fuzzy logic study is frequently linked to other disciplines of science, such as Fault, therefore creating a link between diverse domains of science.
His work investigates the relationship between Topology and topics such as Communication channel that intersect with problems in Computable function.
He most often published in these fields:
- Artificial intelligence (16.07%)
- Membrane computing (13.10%)
- Metallurgy (12.50%)
What were the highlights of his more recent work (between 2019-2021)?
- Topology (8.93%)
- Artificial intelligence (16.07%)
- Nuclear chemistry (5.36%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Topology, Artificial intelligence, Nuclear chemistry, Sodalite and Pattern recognition.
His study in the field of State also crosses realms of Universality, Asynchronous communication and Synapse.
His research in Artificial intelligence is mostly focused on k-nearest neighbors algorithm.
His study on Sodalite also encompasses disciplines like
- Sodium aluminosilicate, Kaolinite, Dissolution, Inorganic chemistry and Sodium most often made with reference to Bayer process,
- Aluminosilicate which is related to area like Transition metal.
His Pattern recognition study combines topics in areas such as Image fusion and Multi modality.
His study in Membrane computing is interdisciplinary in nature, drawing from both Postsynaptic potential and Electric power system.
Between 2019 and 2021, his most popular works were:
- Spiking neural P systems with inhibitory rules (19 citations)
- The ubiquitin-specific protease USP8 directly deubiquitinates SQSTM1/p62 to suppress its autophagic activity. (12 citations)
- The ubiquitin-specific protease USP8 directly deubiquitinates SQSTM1/p62 to suppress its autophagic activity. (12 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Artificial intelligence
- Enzyme
Hong Peng mainly investigates Topology, Artificial intelligence, Cell biology, Universality and Pattern recognition.
The study incorporates disciplines such as Power and Dendrite in addition to Topology.
In general Artificial intelligence study, his work on Deep learning often relates to the realm of Contourlet, thereby connecting several areas of interest.
His research in Cell biology intersects with topics in Deubiquitinating enzyme and Deubiquitination.
His Pattern recognition research includes elements of Multi modality, Feature and Image fusion, Multi focus.
His research on Membrane computing frequently links to adjacent areas such as Electric power system.
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