The University of Southampton
Telephone:
+442380592774
Email:
c.leech@soton.ac.uk

Charles Leech

Research Staff

Github

Charles Leech is a Senior Research Assistant on the EPSRC-funded PRiME Programme in the Cyber Physical Systems Research Group based in the School of Electronics and Computer Science. He was awarded his first class honours degree in Electronic Engineering from the University of Southampton in 2013 where he is currently completing a PhD entitled "Runtime Energy Management of Multi-core Processors".

His work focuses on power and performance optimisation of computer vision applications on heterogeneous embedded systems. Additionally, he is involved in the development of software frameworks for runtime management of many-core systems. He has interests in approximate computing, stereo vision, and machine learning for embedded devices.

Professional

Qualifications

BEng Electronic Engineering (Southampton, 2013) - 1st Class (Hons)

Publications

Leech, Charles and Kazmierski, T J (2014) Energy Efficient Multi-Core Processing. ELECTRONICS,, 18 (1), 3-10. (doi:10.7251/ELS1418003L).

Kazmierski, T J and Leech, Charles (2014) Synthesis of application specific processor architectures for ultra-low energy consumption. Small Systems Simulation Symposium, Serbia.

Leech, Charles, Raykov, Yordan P., Ozer, Emre and Merrett, Geoff V. (2017) Real-time room occupancy estimation with Bayesian machine learning using a single PIR sensor and microcontroller. IEEE Sensors Applications Symposium (SAS) 2017, Glassboro, United States. 13 - 15 Mar 2017. 6 pp.

Leech, Charles, Raykov, Yordan P., Ozer, Emre and Merrett, Geoffrey (2017) Dataset supporting the conference paper entitled "Real-time Room Occupancy Estimation with Bayesian Machine Learning using a Single PIR Sensor and Microcontroller". University of Southampton [Dataset]

Leech, Charles, Basireddy, Karunakar Reddy, Singh, Amit, Merrett, Geoffrey and Al-Hashimi, Bashir (2017) Dataset for Learning-based Run-time Power and Energy Management of Multi/Many-core Systems: Current and Future Trends. University of Southampton doi:10.5258/SOTON/D0109 [Dataset]

Vala, Charan Kumar, Immadisetty, Koushik, Acharyya, Amit, Leech, Charles, Balagopal, Vibishna, Merrett, Geoffrey and Al-Hashimi, Bashir (2017) High Speed Low Complexity Guided Image Filtering Based Disparity Estimation. University of Southampton doi:10.5258/SOTON/D0170 [Dataset]

Singh, Amit, Leech, Charles, Basireddy, Karunakar Reddy, Al-Hashimi, Bashir and Merrett, Geoffrey (2017) Learning-based run-time power and energy management of multi/many-core systems: current and future trends. Journal of Low Power Electronics.

Tenentes, Vasileios, Leech, Charles, Bragg, Graeme, Merrett, Geoffrey, Al-Hashimi, Bashir, Amrouch, Hussam, Henkel, Jörg and Das, Shidhartha (2017) Hardware and software innovations in energy-efficient system-reliability monitoring. In IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems. IEEE. 5 pp. (In Press) (doi:10.1109/DFT.2017.8244435).

Leech, Charles, Vala, Charan Kumar, Acharyya, Amit, Yang, Sheng, Merrett, Geoffrey and Al-Hashimi, Bashir (2017) Dataset supporting the paper entitled "Run-time Performance and Power Optimization of a Parallel Disparity Estimation Algorithm on Many-Core Platforms". University of Southampton doi:10.5258/SOTON/D0221 [Dataset]

Leech, Charles, Vala, Charan Kumar, Acharyya, Amit, Yang, Sheng, Merrett, Geoffrey and Al-Hashimi, Bashir (2017) Run-time performance and power optimization of parallel disparity estimation on many-core platforms. ACM Transactions on Embedded Computing Systems. (In Press)

Vala, Charan Kumar, Immadisetty, Koushik, Acharyya, Amit, Leech, Charles, Balagopal, Vibishna, Merrett, Geoff V. and Al-Hashimi, Bashir (2017) High-speed low-complexity guided image filtering-based disparity estimation. IEEE Transactions on Circuits and Systems - I. (doi:10.1109/TCSI.2017.2729084).

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