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Hongfei Hou
PeerJ Editor & Author
900 Points

Contributions by role

Author 100
Editor 800

Contributions by subject area

Environmental Impacts
Spatial and Geographic Information Science
Algorithms and Analysis of Algorithms
Artificial Intelligence
Data Mining and Machine Learning
Neural Networks
Computer Vision
Data Science
Computer Networks and Communications
Mobile and Ubiquitous Computing
Optimization Theory and Computation
Natural Language and Speech
Sentiment Analysis

Hongfei Hou

PeerJ Editor & Author

Summary

Hongfei Hou, a senior scientist at Pacific Northwest National Laboratory, has attained a Ph.D. in Computer Science from Washington State University. His research area includes cloud computing and machine learning.

Adaptive & Self-Organizing Systems Artificial Intelligence Autonomous Systems Bioinformatics Data Mining & Machine Learning Data Science Databases Internet of Things

Editorial Board Member

PeerJ Computer Science

Work details

Senior Data Scientist

Pacific Northwest National Laboratory
Energy and Environment Directorate
Hongfei Hou is the Principal Investigator of the Industrial Hygiene Data Analysis and Visualization (IDAV) suite of applications for the Hanford site to ensure the that Industrial Hygiene (IH) quality and conditioning requirements are met. His research area includes cloud computing and machine learning.

Websites

  • PNNL-staff
  • Orcid

PeerJ Contributions

  • Articles 1
  • Edited 5
January 18, 2023
A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources
Hongfei Hou, Huiying Ren, Patrick Royer, Xiao-Ying Yu
https://doi.org/10.7717/peerj.14664 PubMed 36691483

Academic Editor on

July 16, 2025
Optimising AI writing assessment using feedback and knowledge graph integration
Ci Zhang
https://doi.org/10.7717/peerj-cs.2893
April 22, 2025
Numerical dispersed flow simulation of fire-flake particle dynamics and its learning representation
Jong-Hyun Kim, Jung Lee
https://doi.org/10.7717/peerj-cs.2836
July 25, 2024
Prediction model of stock return on investment based on hybrid DNN and TabNet model
Tonghui Zhang, Ming Da Huo, Zhaozhao Ma, Jiajun Hu, Qian Liang, Heng Chen
https://doi.org/10.7717/peerj-cs.2057
June 14, 2024
Deep learning-driven dyslexia detection model using multi-modality data
Yazeed Alkhurayyif, Abdul Rahaman Wahab Sait
https://doi.org/10.7717/peerj-cs.2077
March 25, 2024
Offloading the computational complexity of transfer learning with generic features
Muhammad Safdar Ali Khan, Arif Husen, Shafaq Nisar, Hasnain Ahmed, Syed Shah Muhammad, Shabib Aftab
https://doi.org/10.7717/peerj-cs.1938