Projects per year
I am an expert in adaptive and energy efficient computing as evidenced by my research grants as principal investigator that result in technology used at an international scale, my publications as first author in high-quality journals, conference publications that receive best papers awards and my industrially sponsored research with leading multinational companies in the field of microelectronics. One of my objectives since joining Bristol has been to have a strong industrial relevance in both teaching and research. I have followed a hands-on approach towards research and aimed at conducting part of my research within industry to follow best industrial practices and methods. The research at ST,Italy during my Marie Curie fellowship in reconfigurable processors and interconnect lead to further funding from EPSRC (PI £500K) together with Manchester University following my progression to SL in 2007. Key components of this work were made publicly available in open-source format to increase the dissemination of the research and strengthen the impact of publications. The work done with the Innovation Triangle Initiative created by European Space Agency (PI £50K) during 2010 build on previous EPSRC research and resulted in a family of high-performance reconfigurable compressors that can adapt in real-time to the data type being compressed. Currently, this work is being used in different industrial and academic projects around the world as a reference system. Energy efficiency is one of mine main areas of interest and key in the semiconductor. In this topic I obtained a Royal Society fellowship working at ARM, Cambridge (a world leader in microprocessor intellectual property) for one year. The work done at ARM investigated a new modelling approach using high-level information to understand how power and energy is used in modern complex system-on-chips. This work was published in several journals and conferences and it is currently one of the most downloaded papers in the Elsevier Microprocessors and Microsystems journal. ARM is using the results in the EuroCloud project and in their own system simulator called Gem5. In 2013 I obtained an industrial CASE award (£100K) funded by ARM and EPSRC to investigate how the techniques created during my fellowship can be used in ARM big.LITTLE heterogeneous processors that combined processing cores of different complexity. Also at the end of 2013 I obtained as PI an EPSRC grant worth £900K in the area of energy proportional and adaptive computing working with programming experts from QuB with Bristol as lead institution and £75K from DSTL to explore how this technology can be used in military signal processing applications. Examples of CI include the collaboration in the EU funded ENTRA project (£700K) and work with the TSB, DSTL and MoD in energy-efficient signal processing (£150K). In 2014 I have aimed at increasing the impact of my research and establish a research collaboration with defense company Qioptiq to create the first low-power and low-cost data fusion system for man portable applications. The first work package sponsored by the company (£5K) will be delivered in December and further work is expected. A similar collaboration has been built with University of Oxford and the SKA (Square Kilometer Array) multinational project.
5/01/16 → 4/01/20
Entropy-Driven Adaptive Filtering for High-Accuracy and Resource-Efficient FPGA-Based Neural Network SystemsNunez-Yanez, J. L., 15 Nov 2020, In : Electronics.
Research output: Contribution to journal › Article (Academic Journal) › peer-reviewOpen AccessFile27 Downloads (Pure)
Nikov, K. & Nunez-Yanez, J., 28 Apr 2020, In : International Journal of Embedded Systems. 12, 3
Research output: Contribution to journal › Article (Academic Journal) › peer-review
Performance and Energy Trade-Offs for Parallel Applications on Heterogeneous Multi-Processing SystemsCoutinho Demetrios, A. M., Sensi, D. D., Lorenzon, A. F., Georgiou, K., Nunez-Yanez, J., Eder, K. & Xavier-de-Souza, S., 11 May 2020, In : Energies. 13, 9, 24 p., 2409.
Research output: Contribution to journal › Article (Academic Journal) › peer-reviewOpen AccessFile25 Downloads (Pure)