Muhammad Shahzad

Electrical and Electronic Engineering · ACM/IEEE International Conference on Mobile Computing and Networking · 2015–2017

A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

Whom Muhammad Shahzad trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Souvik Sen
  2. Fadel M. Adib
  3. Yuxi Wang
  4. Daniel Halperin
  5. Chih-Jen Lin
  6. Kaishun Wu
  7. Yan Wang
  8. Koji Yatani
  9. Youngwook Kim
  10. Guan-Ru Wang

Who trusts Muhammad Shahzad overall

  1. Jian Liu
  2. Wen Wang
  3. Kun Qian
  4. Yue Zheng
  5. Yi Zhang
  6. Chen Chen
  7. Yuanying Chen
  8. Gang Zhou
  9. Hongbo Liu
  10. Zehua Sun

Papers from Muhammad Shahzad's perspective

Ordered by how strongly the researchers Muhammad Shahzad trusts endorse each paper. Same corpus, a different order for every researcher.

  1. See through walls with WiFi! (Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication)
  2. 3D Tracking via Body Radio Reflections (Symposium on Networked Systems Design and Implementation)
  3. Whole-home gesture recognition using wireless signals (ACM/IEEE International Conference on Mobile Computing and Networking)
  4. Fundamentals of Wireless Communication
  5. You are facing the Mona Lisa: spot localization using PHY layer information (ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services)
  6. Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine (IEEE Transactions on Geoscience and Remote Sensing)
  7. Avoiding multipath to revive inbuilding WiFi localization (ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services)
  8. WiGest: A ubiquitous WiFi-based gesture recognition system (IEEE Conference on Computer Communications)
  9. LIBSVM: A library for support vector machines
  10. Understanding and Modeling of WiFi Signal Based Human Activity Recognition (ACM/IEEE International Conference on Mobile Computing and Networking)

Their papers