About Me
Hello! my name is Tarek
I am a Lead Machine Learning Research Engineer at the Alan Turing Institute. The Alan Turing Institute is the United Kingdom's national institute for data science and artificial intelligence, founded in 2015 and largely funded by the UK government. It is named after Alan Turing, the British mathematician and computing pioneer.
I did my PhD in Applied Machine Learning at the Centre for Data Intensive Science at University College London (UCL). My PhD research focused on the application of Deep Learning and Model Compression algorithms for real-time classification of Astronomical transient events.
My thesis, for which I won the Perren prize for best CDT thesis 2022, can be freely downloaded from the UCL archives here.
Towards the end of my PhD I was one of the 7 research students that were nominated by UCL to apply for the Schmidt Science Fellowship. While I was ultimately unsuccessful, my research proposal on "Efficient Learned Image Reconstruction and Compression Algorithms for Real-time Medical Image Analysis" is a good reflection of some of the areas of research I find most interesting.
Through my role at the ATI, I get to continue my applied research by investigating how the latest techniques in statistical signal processing and probabilistic machine learning can be used for Neural Compression 
to better enable low-latency energy efficient inference of machine learning models in resource constrained Embedded Systems -- a.k.a #tinyML
I am also a Research Software Engineering Fellow at the Software Sustainability Institute, where I help academics leverage tools and software engineering best practises for better research software : #bettersoftwarebetterscience