This website contains a summary of some of my personal projects, technical skills, experiences, and education.
This website contains a summary of some of my personal projects, technical skills, experiences, and education.
MODULES
Applied Machine Learning, Intro to Machine Learning, Bayesian Statistics, Statistics for HDS, Advanced Biostatistics, Applied Data Analysis, Geostatistical Modelling, Infectious Diseases Modelling, Public Health, Epidemiology, Research Skills
AWARDS
EXTRACURRICULAR
MODULES
AI Principles, AI Practice,
Machine Learning, Signal Processing, Constraint Programming, Language and Computation,
Interactive Software and Hardware
AWARDS
Dean's list
RELEVANT MODULES
Bioinformatics, Mathematics
for Computer Science, Database Technology, Web Technologies, Software Engineering,
Cryptography, Human-Computer Interaction, Mobile Development
AWARDS
ncl+ award
A. Priddey, M. Chen-Xu, D. Cooper, S. MacMillan, G. Meisl, C. Xu, M. Hosmillo, I. Goodfellow, R. Kollyfas, R. Doffinger, J. Bradley, I. Mohorianu, R. Jones, T. Knowles, R. Smith, V. Kosmoliaptsis
A. Jacob, I. Moutsopoulos, A. Petchey, R. Kollyfas, V. Knight-Schrijver, I. Mohorianu, S. Sinha, C. Smith
I recently worked on a variety of projects, and I would like to showcase a selection of them here. However, if you're interested in seeing more, you can check out my Github profile where you can find a more comprehensive list of my work (even though not all of my projects are public).
R package (flufftail), designed for single-cell data analysis through the angle of fuzzy community-detection clustering that aims to characterise fuzzy cells/genes and subsequently uncover insights on mechanisms that drive cellular plasticity and GRN dynamics.
A Python package for data-driven parameter values selection across all stages (dimensionality reduction, graph construction, clustering) of graph-based community detection clustering in single-cell datasets.
Use of machine learning to identify biomarkers that can predict sensitivity or resistant to a new anti-cancer drug (NUC-7738) using extremely high dimensional multi-omics data.
Context-free grammar (CFG) for parsing English sentences, extended with number agreement and subcategorization features to improve linguistic accuracy. Tested the grammar with positive and negative sentences for validation.
Quantum Quack makes a random choice in a list of options you provide. The choice is made using quantum random numbers, which are truly random, as opposed to ordinary random numbers.
An interactive software and hardware project that rewards the users by automatically watering their favourite plant whenever they study. Oh, and it also involves a holographic timer!
Personal Email: rafaelkoll98@gmail.com
Academic Email: rk720@cam.ac.uk
Mobile: +44 7999437959