May 2020 – Sep 2021 · 1 yr 4 mos · United Kingdom

• My main responsibility was to provide novel algorithmic solutions and intellectual property in the field of capacitive touch sensing and signal processing. Daily duties include blue sky research for specific problems in: high noise sensing; adaptive filtering and noise cancellation; mixed signal processing and dataflow; control systems and modelling. I also provide mentorship and training and offer consultation, insight and advice to the rest of the R&D team on matters of mathematical modelling using Simulink. Most modelling is currently performed under the Matlab- Simulink- Simscape framework alongside python (for real time applications) and R (for specialist statistical analysis) when required. I also collect requirements and make engineering decisions ensuring KPIs are met.

Mar 2019 – Apr 2020 · 1 yr 1 mo · Greater Cambridge Area

• My main responsibility has been to assist in the development of the company’s new generation flagship project. Firstly, I have taken lead in algorithm development using Matlab for statistical analysis, curve fitting, system identification and process modelling. I was also the go-to person for EMC related testing following 60601 standards for medical devices. I have been heavily involved in electronic (schematic and PCB) and rapid prototyping of ideas and test equipment. I also provided key signal processing insight in magnetic materials projects.
• I took an active management role managing external projects. I was the main liaison between software consultants and the R&D team, ensuring correct implementation of the appropriate algorithms. I have also taken a leading role in the transfer of the product to manufacture. Lastly, I was actively involved in other company projects that have enabled me to work in a multidisciplinary environment.

Jun 2018 – Oct 2021 · 3 yrs 4 mos

• Continuing the BAE Systems and EPSRC funded work that commenced in Loughborough University. A novel, model based, fault tolerant method has been developed to prevent generator systems from overheating whilst maintaining functionality. Using System Identification techniques, Machine Learning and Control algorithms faults are incorporated in the modelling and prediction process in order to provide an accurate prognosis of the thermal state of the systems and hence accurate action can be taken.
• This body of work focuses on developing patents that stemmed from the conducted reserach.

Oct 2015 – Jun 2018 · 2 yrs 8 mos · Loughborough

• In order to increase efficiency and decrease aircraft weight, hydraulic, pneumatic and mechanical
• systems are being substituted by electrical, which has increased the need for uninterrupted supply of power to such systems. The generators are limited by the amount of power they can supply. An excess current demand can result to overheating which if it persists it can cause catastrophic failures.
• This PhD focuses on intelligent load management as a method of preventing overheating (instead of the conventional thermal fuse). This is done by predicting the future temperature of the generators and making decisions on which loads should be online based on the predictions.

Aug 2012 – Sep 2012 · 1 mo

Jun 2011 – Sep 2011 · 3 mos