Imaging, Data and Communications

Research Associate in Signal Processing for Sensing and Communications
shassan@ed.ac.uk
Imaging, Data and Communications
Honorary Fellow
iain.butler@ed.ac.uk
Imaging, Data and Communications
Postgraduate
s2332794@sms.ed.ac.uk
1.05 Alexander Graham Bell Building
Imaging, Data and Communications
Research Associate (C1) (ACAD - Researcher)
Linus.Ericsson@ed.ac.uk
1.05 Alexander Graham Bell Building
Imaging, Data and Communications
Research Associate in Sensor Data and Resource Management for Autonomous Airborne Platforms
rgan@ed.ac.uk
https://runzegan.github.io
Imaging, Data and Communications

My research includes methodologies for approximate inference, particularly variational inference and Monte Carlo methods, as well as stochastic modelling for time series data. On the applied side, I primarily work on multi-object tracking, distributed sensor fusion, and intent inference.

I obtained my PhD in Information Engineering from the University of Cambridge, and previously held research associate positions at the Alan Turing Institute and the University of Cambridge.

I have served as a reviewer for international journals and conferences, including IEEE Transactions on Aerospace and Electronic Systems and IEEE Transactions on Signal Processing. I also organised a special session at the IEEE Statistical Signal Processing Workshop 2025.

Postgraduate
A.T.Don@sms.ed.ac.uk
3.08 Scottish Microelectronics Centre, 2.01 Alexander Graham Bell Building
Imaging, Data and Communications
Senior Lecturer and Discipline Programme Manager
elliot.j.crowley@ed.ac.uk
1.12 Alexander Graham Bell Building
Electronics and Electrical Engineering
Imaging, Data and Communications
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Elliot
Research Associate
emoroshk@ed.ac.uk
Imaging, Data and Communications
Research Associate in Signal Processing for Sensing and Communications
Yli29@ed.ac.uk
1.05 Alexander Graham Bell Building
Imaging, Data and Communications
Senior Lecturer in Electronic Engineering
c.liu@ed.ac.uk
+44(0)131 6502563
1.09 Alexander Graham Bell Building
Electronics and Electrical Engineering
Imaging, Data and Communications
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Dr Chang Liu

Dr Chang Liu received the B.Sc. degree in automation from Tianjin University, China, in 2010, and the Ph.D. degree in testing, measurement technology and instrument in Beihang University, China, in 2016. From April 2016 to January 2018, he was a postdoctoral researcher in the department of air pollution and environmental technology, Empa-Swiss Federal Laboratories for Materials Science and Technology (ETH Domain), Dübendorf, Switzerland. He is now a Senior Lecturer in the Agile Tomography Group at the School of Engineering, University of Edinburgh.

Dr Liu’s current research interests include laser spectroscopy, laser imaging, data-driven imaging techniques and their applications to reacting flow-fields diagnostics and environmental monitoring. His expertise is in design of near/mid infrared LAS sensing systems, and development of high-sensitivity and data-driven laser imaging methodologies. It covers fundamental spectroscopic modeling, inverse problem solving, machine learning, hardware acceleration, signal processing and embedded system. In collaboration with worldwide industrial and academic partners, Dr Liu and his team focus on providing cutting-edge laser-based sensing solutions for various challenging problems in both the industry and academia.

  • 2016 Doctor of Philosophy (Ph.D.), School of Instrumentation and Opto-Electronic Engineering, Beihang University, Beijing, China.
  • 2010 Bachelor of Science (B.Sc.), School of Electrical Engineering and Automation, Tianjin University, Tianjin, China
  • IEEE Senior Member
  • Digital System Design 4 (ELEE10007)
  • Analogue Circuits 3 (ELEE09026)
  • Digital System Design and Digital Systems Laboratory 3 (ELEE09035)
  • Digital System Design 2 (ELEE08015)
  • Data-driven imaging towards high spatial/temporal resolution
  • Cutting-edge laser-based sensing solutions
  • Sensor design for ultra-weak optical and electrical signals detection
  • Embedded system design and hardware/software interface