Research output per year
Research output per year
Personal profile
Biography
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 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, signal processing, embedded system and hardware/software interface design. 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.
Research Interests
- 2D/3D data-driven optical imaging
- Laser sensing for combustion diagnosis and environmental monitoring
- Inverse problem
Research Groups
Agile Tomography Group
Education/Academic qualification
Testing, measurement technology and instrument, Doctor of Philosophy (PhD), Beihang University
Award Date: 15 Jan 2016
Automation, Bachelor of Science, Tianjin University
Award Date: 1 Jul 2010
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Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Spatially Driven Chemical Species Tomography with Size-Adaptive Hybrid Meshing Scheme
Zhang, R., Si, J., Enemali, G., Bao, Y. & Liu, C., 18 May 2022, (E-pub ahead of print) In: IEEE Sensors Journal.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
CSTNet: A Dual-Branch Convolutional Neural Network for Imaging of Reactive Flows using Chemical Species Tomography
Jiang, Y., Si, J., Zhang, R., Enemali, G., Zhou, B., McCann, H. & Liu, C., 24 Mar 2022, (E-pub ahead of print) In: IEEE Transactions on Neural Networks and Learning Systems.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
Cost-Effective Quasi-Parallel Sensing Instrumentation for Industrial Chemical Species Tomography
Enemali, G., Zhang, R., Mccann, H. & Liu, C., Feb 2022, In: IEEE Transactions on Industrial Electronics. 69, 2, p. 2107-2116Research output: Contribution to journal › Article › peer-review
Open AccessFile -
Flow Regime Transition in Countercurrent Packed Column Monitored by ECT
Li, Z., Chen, Y., Yang, Y., Liu, C., Lucquiaud, M. & Jia, J., 16 Apr 2021, (E-pub ahead of print) In: Chemical Engineering Journal. 420, Part 1, 11 p., 129841.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
Relative Entropy Regularised TDLAS Tomography for Robust Temperature Imaging
Bao, Y., Zhang, R., Enemali, G., Cao, Z., Zhou, B., McCann, H. & Liu, C., 16 Nov 2020, In: IEEE Transactions on Instrumentation and Measurement. 70, 9 p., 4501909.Research output: Contribution to journal › Article › peer-review
Open AccessFile
Activities
- 2 Invited talk
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Tomographic Absorption Spectroscopy for Combustion Diagnosis
Chang Liu (Invited speaker)
13 Aug 2018Activity: Academic talk or presentation types › Invited talk
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Aero-Engine Combustion Diagnosis and Trace Gas Sensing
Chang Liu (Invited speaker)
27 Dec 2018Activity: Academic talk or presentation types › Invited talk
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Laser Imaging of Turbine Engine Combustion Species (LITECS)
Mccann, H., Liu, C. & Polydorides, N.
1/09/20 → 31/08/24
Project: Research
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Cost-effective CO2 and CO monitoring with laser absorption spectroscopy
1/10/18 → 30/09/19
Project: Research Collaboration with external organisation
Datasets
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Data set for " CNN-aided Flooding Prognostic in Packed Column using Electrical Capacitance Tomography."
Yang, Y. (Creator), Jia, J. (Creator), Chen, Y. (Creator), Liu, C. (Creator) & Lucquiaud, M. (Creator), Edinburgh DataShare, 1 Feb 2023
DOI: 10.7488/ds/3151
Dataset