Dr. Yun Wu
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Research Interests
- Approximate Computing
- Embedded Systems & Reconfigurable Architectures
- Energy-Efficient System Design
- Computer Vision & Machine Learning
- Autonomous Vehicles & Sensor Fusion
- Hardware Security
Work experience
Lecturer (Assistant Professor)
Queen’s University Belfast, UK (Jun 2023 – Present)
Teaching and research in embedded systems, computer vision, and hardware security
Assistant Professor
University of Essex, UK (Jan 2023 – May 2023)
Lecturer in computer vision and embedded systems
Assistant Professor (Part-time)
Heriot-Watt University, UK (Jan 2022 – Jan 2023)
Teaching: Parallel & Distributed Programming, Software Engineering, Industrial Programming
Research Associate
Heriot-Watt University, UK (May 2019 – Jan 2023)
Research on approximate co-processors for mathematical optimization, FPGA-based accelerators, and embedded DSP for Lidar
Research Fellow
Cranfield University, UK (Mar 2018 – May 2019)
Embedded systems for autonomous vehicle infrastructure and sensor fusion (Lidar, Radar, GPS)
- Research Fellow
Queen’s University Belfast, UK- Dec 2016 – Feb 2018: Soft-core processor IP design on FPGA (Zedzynq 7020), 5G receiver prototyping
- Jan 2014 – Nov 2016: Power-proportional computing on hybrid ARM/FPGA SoC (Zynq 7000)
- Wireless Algorithm Engineer
ZTE Corporation, China (Dec 2008 – Aug 2010)
System-level optimization for TD-SCDMA/TDD-LTE, parallel computing, and dynamic simulation
Education
Ph.D. in Electronic, Electrical & Information Engineering
Queen’s University Belfast, UK (2010–2013)
Research: System-level design methodology for soft-core streaming processors on FPGA and MIMO receiver algorithm design
M.Sc. in Radio Frequency Communication Systems
University of Southampton, UK (2007–2008)
M.Sc. in Circuit & System
Hunan University, China (2004–2007)
B.Sc. in Electronic & Information Engineering
Dalian Minzu University, China (1999–2003)
Awards and Recognition
- Associate Fellowship, Higher Education Academy (2025)
- EPS Innovation in Teaching Funding (2023)
- NVIDIA Academic Grant Program (2020/2021)
Service and leadership
- Member, Institute of Electrical and Electronics Engineers
- Member, EPSRC Peer Review College
- Reviewer, IEEE Transactions on Computers
- Reviewer, IEEE Nanotechnology Magazine
- EPS (QUB) Summer Internship Supervisor
Skills
- Programming: C/C++, Python, MATLAB, VHDL/Verilog, Java, OpenCL/OpenMP/OpenMPI
- Tools: Vitis/Vivado, Git, Docker, LaTeX
- Platforms: FPGA, ARM, CUDA
- Research: Numerical Analysis, System Optimization, Design Automation, Signal Processing
Publications
Yuhang Hao, Yun Wu, Minmin Jiang, Maire O`Neill, Chongyan Gu. (2025). "Rowhammer Mitigation by Approximate Computing: A Compressed Sensing Case Study." IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2025: Proceedings. IEEE.
Yuhang Hao, Yun Wu, Ziying Ni, Jack Miskelly, Maire O`Neill, Chongyan Gu. (2025). "AxRA: approximate Rowhammer attack for modern DRAM systems." IEEE International Symposium on Circuits and Systems (ISCAS) 2025: Proceedings. IEEE.
Sahoo, S. S., Deveautour, B., Traiola, M., Gu, C., Wu, Y., Japa, A., Ullah, S. & Kumar, A. (2025). “Emerging scope and design challenges for approximate computing: optimizing accuracy-PPA trade-offs and beyond.” ACM Transactions on Embedded Computing Systems. (Accepted 5 June 2025).
Wang, X. & Wu, Y. (2025). “Universal approximated real-valued Fast Fourier Transform for image blur detection.” In *Proceedings of the 2025 36th Irish Signals and Systems Conference (ISSC)*, IEEE.
Wu, Y. & McAllister, J. (2025). “Efficient co-approximate parallel compressive depth reconstruction on FPGA.” In *2025 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025: Proceedings)*. IEEE.
Wu, Y. & McAllister, J. (2024). “Efficient approximate checkerboard K-SVD for resource constrained embedded systems.” In *Proceedings of the 35th Irish Signals and Systems Conference (ISSC 2024)*. IEEE.
Hamadouche, A., Wu, Y., Wallace, A. M., & Mota, J. F. C. (2024). “Sharper Bounds for Proximal Gradient Algorithms with Errors.” *SIAM Journal on Optimization*, 34(1), 278-305.
Wu, Y., Wallace, A. M., Mota, J. F. C., Aßmann, A., & Stewart, B. (2022). Efficient Reconfigurable Mixed Precision ℓ₁ Solver for Compressive Depth Reconstruction. *Journal of Signal Processing Systems*, 94(10), 1083–1099. https://doi.org/10.1007/s11265-022-01766-3
Wu, Y., Mota, J. F. C., & Wallace, A. M. (2022). Joint undervolting and overclocking power scaling approximation on FPGAs. In *Proceedings of the 11th International Conference on Sensor Signal Processing for Defence (SSPD 2022)*. IEEE. https://doi.org/10.1109/SSPD54131.2022.9896229.
Wu, Y., Zhang, Y., Hamadouche, A., Mota, J. F. C., & Wallace, A. M. (2022). “Automatic approximation for 1-Dimensional Feedback-Loop Computations: a PID Benchmark.” In *2022 Sensor Signal Processing for Defence Conference (SSPD 2022)*. IEEE. DOI:10.1109/SSPD54131.2022.9896191
Wu, Y. (2022). Energy Efficient Approximate 3D Image Reconstruction. *IEEE Transactions on Emerging Topics in Computing*, 10(2), 1234–1245. https://doi.org/10.1109/TETC.2022.09559866
Wu, Y., & McAllister, J. (2021). Energy-Efficient Adaptive Modulated Fixed-Complexity Sphere Decoder. In *Proceedings of the 2021 IEEE Workshop on Signal Processing Systems (SiPS 2021)* (pp. 82–87). IEEE. https://doi.org/10.1109/SiPS52901.2021.9595145
Wu, Y., Wallace, A. M., Aßmann, A., & Stewart, B. (2021). Mixed Precision ℓ₁ Solver for Compressive Depth Reconstruction: An ADMM Case Study. In *Proceedings of the 2021 IEEE Workshop on Signal Processing Systems (SiPS 2021)* (pp. 70–75). IEEE. https://doi.org/10.1109/SiPS52901.2021.9595141
Hamadouche, A., Wu, Y., Wallace, A. M., & Mota, J. F. C. (2021). Approximate Proximal-Gradient Methods. In *Proceedings of the 2021 Sensor Signal Processing for Defence Conference (SSPD)*. IEEE. https://doi.org/10.1109/SSPD51364.2021.9541509
Wu, Y., & McAllister, J. (2021). Configurable Quasi-Optimal Sphere Decoding for Scalable MIMO Communications. *IEEE Transactions on Circuits and Systems I: Regular Papers*, 68(6), 2021–2032. https://doi.org/10.1109/TCSI.2021.9375712
Aßmann, A., Wu, Y., Stewart, B., & Wallace, A. M. (2020). Accelerated 3D Image Reconstruction for Resource-Constrained Systems. In *Proceedings of the 28th European Signal Processing Conference (EUSIPCO 2020)* (pp. 565–569). IEEE. https://doi.org/10.23919/Eusipco47968.2020.9287749
Wu, Y., Mota, J. F. C., & Wallace, A. M. (2020). Approximate LASSO Model Predictive Control for Resource-Constrained Systems. In *Proceedings of the 2020 Sensor Signal Processing for Defence Conference (SSPD)*. IEEE. https://doi.org/10.1109/SSPD47486.2020.9272000
Wu, Y., Wang, P., & McAllister, J. (2020). Programmable Dataflow Accelerators: A 5G OFDM Modulation/Demodulation Case Study. In *ICASSP 2020 - IEEE International Conference on Acoustics, Speech, and Signal Processing* (pp. 1728–1732). IEEE. https://doi.org/10.1109/ICASSP40776.2020.9053529
Wu, Y., & McAllister, J. (2019). On Modified Squared Givens Rotations for Sphere Decoder Preprocessing. In *ICASSP 2019 - IEEE International Conference on Acoustics, Speech, and Signal Processing* (pp. 1528–1531). IEEE. https://doi.org/10.1109/ICASSP.2019.8683283
Wu, Y., & McAllister, J. (2018). Architectural Synthesis of Multi-SIMD Dataflow Accelerators for FPGA. *IEEE Transactions on Parallel and Distributed Systems, 29*(1), 43–55. https://doi.org/10.1109/TPDS.2017.2753038
Wu, Y., & McAllister, J. (2017). Bounded Selective Spanning With Extended Fast Enumeration for MIMO-OFDM Systems Detection. *IEEE Transactions on Circuits and Systems I: Regular Papers, 64*(9), 2556–2568. https://doi.org/10.1109/TCSI.2017.2716710
Wu, Y., Gillan, C., Minhas, U., Barbhuiya, S., Novakovic, A., Tovletoglou, K., Tzenakis, G., Vandierendonck, H., Karakonstantis, G., & Nikolopoulos, D. (2017). Heterogeneous Servers based on Programmable Cores and Dataflow Engines. In *Workshop on Energy-Efficient Servers for Cloud and Edge Computing 2017*. Queen’s University Belfast. https://pureadmin.qub.ac.uk/ws/files/123397592/HiPEAC_ESCEC_2016.pdf
Wu, Y., Nikolopoulos, D. S., & Woods, R. (2017). Runtime Support for Adaptive Power Capping on Heterogeneous SoCs. In *Proceedings of the International Conference on Embedded Computer Systems: Architecture, Modeling and Simulation (SAMOS XVI)* (pp. 71–78). IEEE. https://doi.org/10.1109/SAMOS.2017.7818333
Barbhuiya, S., Wu, Y., Murphy, K., Vandierendonck, H., Karakonstantis, G., & Nikolopoulos, D. S. (2016). Accelerating Data Center Applications with Reconfigurable DataFlow Engines. In *Proceedings of the Heterogeneous High-Performance Reconfigurable Computing (H2RC) 2016 Workshop*. https://h2rc.cse.sc.edu/2016/papers/paper_9.pdf
Kelly, C., Siddiqui, F. M., Bardak, B., Wu, Y., Woods, R., & Rafferty, K. (2016). FPGA Soft-Core Processors, Compiler and Hardware Optimizations Validated Using HOG. In *Applied Reconfigurable Computing - 12th International Symposium, ARC 2016, Proceedings* (Vol. 9625, pp. 78–90). Springer. https://doi.org/10.1007/978-3-319-31462-4_7
Wu, Y., Nunez-Yanez, J., Woods, R., & Nikolopoulos, D. S. (2014). Power Modeling and Capping for Heterogeneous ARM/FPGA SoCs. In *Proceedings of the 2014 International Conference on Field-Programmable Technology (FPT)* (pp. 231–234). IEEE. https://doi.org/10.1109/FPT.2014.7082782
Wu, Y., & McAllister, J. (2014). FPGA-based Tabu Search for Detection in Large-Scale MIMO Systems. In *Proceedings of the 2014 IEEE Workshop on Signal Processing Systems (SiPS)* (pp. 1–6). IEEE. https://doi.org/10.1109/SiPS.2014.6986073
Wu, Y., McAllister, J., & Wang, P. (2013). High performance real-time pre-processing for fixed-complexity sphere decoder. In *2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP)* (pp. 1250–1253). IEEE. https://doi.org/10.1109/GlobalSIP.2013.7086073
Wu, Y., McAllister, J., & Wang, P. (2013). Cooperative Actor Oriented Synthesis for FPGA-based MIMO-OFDM Detection. In *2013 Software Defined Radio (SDR)-WInnComm*. Wireless Innovation Forum.
Wu, Y., & McAllister, J. (2013). Bounded Selective Spanning with Extended Fast Enumeration for MIMO-OFDM Systems Detection. In *2013 Proceedings of the 21st European Signal Processing Conference (EUSIPCO 2013)* (pp. 1–5). IEEE. https://doi.org/10.1109/EUSIPCO.2013.6811656
Wang, P., McAllister, J., & Wu, Y. (2013). Soft-core stream processing on FPGA: An FFT case study. In *2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)* (pp. 2756–2760). IEEE. https://doi.org/10.1109/ICASSP.2013.6638261
Zheng, C., Wu, Y., McAllister, J., & Woods, R. (2011). Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems. In *2011 IEEE Workshop on Signal Processing Systems (SiPS)* (pp. 107–113). IEEE. https://doi.org/10.1109/SiPS.2011.6111848
Zheng, C., McAllister, J., & Wu, Y. (2011). A kernel interleaved scheduling method for streaming applications on soft-core vector processors. In *2011 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)* (pp. 278–285). IEEE. https://doi.org/10.1109/RTCSA.2011.6006617
Talks
June 10, 2025
Talk at Irish Signals & Systems Conference (ISSC 2025), ATU Donegal, Ireland
April 10, 2025
Talk at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Online
July 13, 2024
Talk at Irish Signals and Systems Conference (ISSC), Belfast, UK
September 27, 2023
Tutorial at Cranfield University, Cranfield, UK
Teaching