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Lei Wu
School of Chemistry and Chemical Engineering
h-index
584
Citations
12
h-index
Calculated based on number of publications stored in Pure and citations from Scopus
2013
2024
Research activity per year
Overview
Fingerprint
Network
Research output
(34)
Fingerprint
Dive into the research topics where Lei Wu is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Weight
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Engineering
Soft Sensor
66%
Batch Process
41%
B Cell
33%
Local Model
28%
Gaussians
20%
Experimental Result
19%
Formability
19%
Leukocyte
17%
Microfluidic Device
16%
Magnetic Field
16%
Photonics
16%
Moisture Retention
16%
Machine Learning Algorithm
16%
Fault Diagnosis
16%
Relaxation Time Spectrum
16%
Fermenter
16%
Wireless Sensor Node
16%
Induced Heating
16%
Energy Gap
16%
Nuclear Magnetic Resonance
16%
Chemical Engineering
16%
Lymphocyte
16%
Photonic Band
16%
Max
16%
Amplifier
16%
Wireless Communication
16%
Scheduling Strategy
16%
Data Field
16%
Electric Power Utilization
16%
Quantization (Signal Processing)
16%
T Cell
16%
Sugar Concentration
16%
Sensor Node
16%
Gaussian Mixture Model
16%
Hydrodynamics
16%
Millimeter Wave
16%
Nanosensor
16%
Monitoring System
16%
Nonlinearity
13%
System-in-Package
13%
Signal-to-Noise Ratio
12%
Similarities
12%
Logging Tool
10%
Thermal Resistance
10%
Histogram
8%
Input Parameter
8%
Heat Source
8%
Normalizing Factor
8%
Microstructure
8%
Boundary Condition
8%
Material Science
Photonic Crystal
100%
Hydrogel
52%
Tumor
50%
T-Cells
50%
Amorphous Material
30%
Optical Property
20%
Tensile Strain
17%
Lymphocyte
16%
Photonic Band Gap
16%
Cell Membrane
16%
Three Dimensional Printing
16%
Carbon Fiber
16%
Ferrofluid
12%
Theoretical Calculation
11%
Photochromics
8%
Reflectivity
8%
Thermochromics
6%
Poly Methyl Methacrylate
6%
Hydrogen Bonding
6%
Scanning Electron Microscopy
5%
Materials Property
5%
Polystyrene
5%
Nanoparticle
5%
Oxidation Reaction
5%
Computer Science
Just-in-Time
25%
Gaussian Mixture Model
16%
Real Time Performance
16%
Predictive Distribution
16%
Probabilistic Analysis
16%
de-noising
16%
Mutual Information
16%
Estimation Accuracy
16%
image denoising
16%
Support Vector Regression
16%
Learning Framework
12%
Replacement Rule
11%
Experimental Result
8%
peak signal to noise ratio
8%
Performance Improvement
8%
Image Gradient
8%
Posterior Probability
8%
Computational Load
8%
Process State
8%
Thermal Resistance
8%
Recognition Result
8%
Modeling Framework
8%
Computational Time
8%
Model Adaptation
8%
Mean Algorithm
8%
Singular Value
8%
Adaptation Mechanism
8%
Adaptive Parameter
8%
Texture Information
8%
Time Complexity
8%
