World's Best Scientists 2026 revealed!

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Computer Science

D-Index
38
Citations
5857
World Ranking
10270
National Ranking
645

Overview

Weisi Guo is affiliated with Cranfield University in the United Kingdom. Their research spans multiple fields including Engineering and Computer Science, with a focus on several subfields such as Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Biomedical Engineering, and Aerospace Engineering.

The scientist has contributed to main research topics including Molecular Communication and Nanonetworks, Advanced Biosensing and Bioanalysis Techniques, Adaptive Dynamic Programming Control, Reinforcement Learning in Robotics, Wireless Body Area Networks, Adversarial Robustness in Machine Learning, and Complex Network Analysis Techniques.

Weisi Guo's recent scholarly articles include:

  • Explainable Artificial Intelligence for 6G: Improving Trust between Human and Machine (2020, IEEE Communications Magazine)
  • A Survey of Online Data-Driven Proactive 5G Network Optimisation Using Machine Learning (2020, IEEE Access)
  • Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms (2020, Signal Processing)
  • Trustworthy Deep Learning in 6G-Enabled Mass Autonomy: From Concept to Quality-of-Trust Key Performance Indicators (2020, IEEE Vehicular Technology Magazine)
  • Deep Reinforcement Learning for Optimal Hydropower Reservoir Operation (2021, Journal of Water Resources Planning and Management)

The scientist frequently publishes in venues such as arXiv (Cornell University), IEEE Transactions on Molecular Biological and Multi-Scale Communications, IEEE Communications Magazine, IEEE Access, and Scientific Reports.

Co-authorship collaborations are notable with researchers including Zhuangkun Wei, Adolfo Perrusquía, Antonios Tsourdos, Bin Li, and Mengbang Zou.

Weisi Guo has also contributed to book publications, notably the volume titled Bio-inspired Information and Communication Technologies, published in 2020 by the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Best Publications

  • A Comprehensive Survey of Recent Advancements in Molecular Communication

    Nariman Farsad;H. Birkan Yilmaz;Andrew Eckford;Chan-Byoung Chae

  • Coexistence of Wi-Fi and heterogeneous small cell networks sharing unlicensed spectrum

    Haijun Zhang;Xiaoli Chu;Weisi Guo;Siyi Wang

  • Tabletop molecular communication: text messages through chemical signals.

    Nariman Farsad;Weisi Guo;Andrew W. Eckford

  • Explainable Artificial Intelligence for 6G: Improving Trust between Human and Machine

    Weisi Guo

  • Heterogeneous Cellular Networks: Theory, Simulation and Deployment

    Xiaoli Chu;David Lopez-Perez;Yang Yang;Fredrik Gunnarsson

  • Molecular communications: channel model and physical layer techniques

    Weisi Guo;Taufiq Asyhari;Nariman Farsad;H. Birkan Yilmaz

  • Relay Deployment in Cellular Networks: Planning and Optimization

    Weisi Guo;T. O'Farrell

  • Automated small-cell deployment for heterogeneous cellular networks

    Weisi Guo;Siyi Wang;Xiaoli Chu;Jie Zhang

  • Molecular Versus Electromagnetic Wave Propagation Loss in Macro-Scale Environments

    Weisi Guo;Christos Mias;Nariman Farsad;Jiang-Lun Wu

  • A Survey of Online Data-Driven Proactive 5G Network Optimisation Using Machine Learning

    Bo Ma;Weisi Guo;Jie Zhang

  • Device-to-device meets LTE-unlicensed

    Yue Wu;Weisi Guo;Hu Yuan;Long Li

  • Three-dimensional SOlar RAdiation Model (SORAM) and its application to 3-D urban planning

    Róbert Erdélyi;Yimin Wang;Weisi Guo;Edward Hanna

  • Performance analysis of micro unmanned airborne communication relays for cellular networks

    Weisi Guo;Conor Devine;Siyi Wang

  • RACH Preamble Repetition in NB-IoT Network

    Nan Jiang;Yansha Deng;Massimo Condoluci;Weisi Guo

  • Simultaneous Information and Energy Flow for IoT Relay Systems with Crowd Harvesting

    Weisi Guo;Sheng Zhou;Yunfei Chen;Siyi Wang

  • Deep learning methods for solving linear inverse problems: Research directions and paradigms

    Yanna Bai;Wei Chen;Jie Chen;Weisi Guo;Weisi Guo

  • Dynamic Cell Expansion with Self-Organizing Cooperation

    Weisi Guo;T. O'Farrell

  • Trustworthy Deep Learning in 6G-Enabled Mass Autonomy: From Concept to Quality-of-Trust Key Performance Indicators

    Chen Li;Weisi Guo;Schyler Chengyao Sun;Saba Al-Rubaye

  • Local Convexity Inspired Low-Complexity Noncoherent Signal Detector for Nanoscale Molecular Communications

    Bin Li;Mengwei Sun;Siyi Wang;Weisi Guo

  • Stable Distributions as Noise Models for Molecular Communication

    Nariman Farsad;Weisi Guo;Chan-Byoung Chae;Andrew Eckford

  • Transposition Errors in Diffusion-Based Mobile Molecular Communication

    Werner Haselmayr;Syed Muhammad Haider Aejaz;A. Taufiq Asyhari;Andreas Springer

  • Green cellular network: Deployment solutions, sensitivity and tradeoffs

    Weisi Guo;Tim O'Farrell

  • Google Trends can improve surveillance of Type 2 diabetes.

    Nataliya Tkachenko;Sarunkorn Chotvijit;Neha Gupta;Emma Bradley

  • Learning-Based Spectrum Sharing and Spatial Reuse in mm-Wave Ultradense Networks

    Chaoqiong Fan;Bin Li;Chenglin Zhao;Weisi Guo

  • Analyzing Large-Scale Multiuser Molecular Communication via 3D Stochastic Geometry

    Yansha Deng;Adam Noel;Weisi Guo;Arumugam Nallanathan

Frequent Co-Authors

Andrew W. Eckford
Andrew W. Eckford York University
Chan-Byoung Chae
Chan-Byoung Chae Yonsei University
Xiaoli Chu
Xiaoli Chu University of Sheffield
Arumugam Nallanathan
Arumugam Nallanathan Queen Mary University of London
Yansha Deng
Yansha Deng King's College London
Stephen A. Jarvis
Stephen A. Jarvis University of Birmingham
Maged Elkashlan
Maged Elkashlan Queen Mary University of London
Guangtao Fu
Guangtao Fu University of Exeter
Andrea Goldsmith
Andrea Goldsmith Stony Brook University
Miaowen Wen
Miaowen Wen South China University of Technology

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