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Associate Professor Philip Branch

Associate Professor
PhD (Computer Systems Engineering), Monash University, Australia; MTech (Computer Systems), University of Tasmania, Australia; BSc, University of Tasmania, Australia


Philip Branch is an Associate Professor in Engineering at Swinburne University of Technology interested in anomaly detection, sensor networks, Internet of Things, network security, and network architectures. Before joining Swinburne he was Development Manager with Ericsson AsiaPacific Labs.

Research interests

Internet of Things; IT Security Systems; Mesh Networks; Mobile communications; Surveillance; BGP Anomaly Detection; 5G Networks

PhD candidate and honours supervision

Higher degrees by research

Accredited to supervise Masters & Doctoral students as Principal Supervisor.

PhD topics and outlines

5G for Underground Mining: 5G Radio Access Network design and performance, and 5G Network Slicing for underground mining.

Accountability in Aged Care using Passive Sensor Networks: Blockchain and other technologies to improve accountability in aged healthcare.

Anomaly Detection in Internet Protocols: Use techniques from nonlinear time series analysis to rapidly detect potentially damaging behaviour of network protocols.

Fall Detection amongst elderly using Passive Sensor Networks: Use data from Ambient Assisted Living systems to reduce likelihood and damage of falls among elderly.

Mesh and Relay Networks: Design and performance of robust and adapable mesh networks, particularly linear or near linear networks.

Networking for Autonomous Vehicles in Underground Mining: Development of frameworks and analysis of performance of communications networks for AVs in underground mining.

Using Passive Sensors to Detect Health Changes in Aged Care: Applications of anomaly detection to passive sensors used in Ambient Assistive Living systems, in particular detecting changes in health.


Available to supervise honours students.

Honours topics and outlines

CUBESAT: Applications of low cost CUBESAT for the Internet of Things.

Drone based networks: Stability, performance, functionality of aerial based LPWANs.

Fields of Research

  • Communications Engineering - 400600
  • Electronics, Sensors And Digital Hardware - 400900


  • 2023, Swinburne, Vice Chancellor's Research Excellence Award (Team / Early Career)), Swinburne University of Technology
  • 2023, International, Best Student Paper, International Telecommunications, Networks and Applications Conference
  • 2021, National, Gold Winner for Halley Assist (TM), Good Design Awards Australia
  • 2019, Swinburne, Vice-Chancellor's Research Excellence Award (Team), Swinburne University of Technology
  • 2019, Swinburne, FSET Research Translation Award , Faculty of Science, Engineering and Technology

Further information



Also published as: Branch, Philip; Branch, P.; Branch, P. A.; Branch, Philip A.
This publication listing is provided by Swinburne Research Bank. If you are the owner of this profile, you can update your publications using our online form.

Recent research grants awarded

  • 2023: Accurate carbon and water accounting for agriculture: Fusing mobile eddy covariance tower measurements with Earth observation satellite data *; SmartSat CRC Fund Scheme
  • 2023: Emergency Buddy System *; SmartSat CRC Fund Scheme
  • 2022: Explosive Detonation System *; The University of New South Wales
  • 2021: Manufacturing solution for remote data communication *; mDetect Pty Ltd
  • 2019: Seniors Staying Well at Home: The S-Well project *; Australian Government Department of Health
  • 2018: Remote/Wireless Explosives *; NewCrest Mining Ltd (Cadia Holdings Pty Ltd)
  • 2017: Enterprise Network Routing Security *; DATA61
  • 2015: A partial PhD stipend to support research into BGP Anomaly Detection using VIRL *; Silicon Valley Community Foundation
  • 2015: Holly Smart Home - Phase 3 *; SP TechSolutions

* Chief Investigator

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