Data Champions Search

Ali Abbas, PhD

Senior Data Scientist, MRC Epidemiology Unit

Areas Of Expertise:

Python, R language, Git, SQL, C/C++/C# language, Java, Data visualisation, Big data, Data mining, Machine learning, Statistical analysis, Version control, Data sharing, Code sharing, Open data, FAIR Data, Writing/publishing data papers, Geospatial data

Contact Information

aa797@cam.ac.uk

Biography

Ali is Senior Data Scientist and public-health/transport modeller in the Public Health Modelling (PHM) group at the MRC-Epidemiology Unit, University of Cambridge. He is interested in active travel, specifically cycling research.

Coming from a Computer Science background, with a focus on modelling in his PhD, for over a decade, he has been doing data-driven research and development. This includes Exploratory Data Analysis (EDA), Statistical Modelling (or Machine Learning), Interactive Visualization, all with a focus on collaborative, transparent and reproducible research. In addition, he leads in project management and managing, training, guiding, and teaching of junior staff in his Unit. His work can be seen on GitHub at https://github.com/usr110.

Andrew Thwaites, PhD

Visiting Scientist

Department of Psychology

Areas Of Expertise:

Bioinformatics, Data sharing, Big data, Coding, Python, R language, SQL, Git, Matlab, Java, Data visualisation, Machine learning, Statistical analysis, Data Management Plans, Data policies, Data archiving, Code sharing, Open data, Imaging, Illustration, Website development

Contact Information

acgt2@cam.ac.uk

ORCiD:

0000-0002-6237-7140

Biography

Additional areas of expertise:

Neuroscience data

Arian Jamasb

PhD student

Department of Biochemistry

Department of Computer Science and Technology

Areas Of Expertise:

Python, R language, Git, Data visualisation, Big data, Machine learning, Statistical analysis, Version control, Discipline-specific repositories, Data sharing, Code sharing, Open data, Cheminformatics, Bioinformatics

Contact Information

ORCiD:

Biography

My research focuses on the applications of machine learning to problems in structural biology and drug discovery.

Hugo Tavares, PhD

Postdoctoral Research Associate

Department of Genetics

Bioinformatics Training Facility

Areas Of Expertise:

Bioinformatics, Coding, Python, R language, Git, Data analysis, Data visualisation, Big data, Data mining, Machine learning, Statistical analysis, Data collection, Experimental design, Data storage, Institutional repositories, Discipline-specific repositories, Data sharing, Code sharing, Open data, Workshop delivery

Contact Information

hm533@cam.ac.uk

Biography

Additional areas of expertise:

Plant science, Quantitative genetics.

Jason Gellis, PhD

Research Associate

Department of Archaeology

Areas Of Expertise:

Python, R language, Git, Data visualisation, Big data, Machine learning, Statistical analysis, Data Management Plans, Data collection, Database design, Version control, Data storage, Discipline-specific repositories, General repositories, Data sharing, Code sharing, Open data, FAIR Data

Contact Information

jg760@cam.ac.uk

My LinkedIn Profile

Biography

I am a researcher and educator in paleoanthropology and biology. Currently, I am developing machine learning and AI applications for human evolutionary studies with the University of Cambridge Leverhulme Center for Human Evolutionary Studies and the Alan Turing Institute.

Qi Wang, PhD

Bioinformatician

Department of Plant Sciences

Areas Of Expertise:

Big data, Data analysis, Bioinformatics, Coding, Python, R language, SQL, Git, Data visualisation, Data mining, Machine learning, Statistical analysis, Experimental design, Data storage, Discipline-specific repositories, Data sharing, Code sharing, Writing/publishing data papers, Workshop delivery

Contact Information

qw254@cam.ac.uk

ORCiD:

0000-0002-6420-1720

Biography

Qi received her PhD at the University of California, Los Angeles, where she developed computational methods to study alternative splicing and the evolution of HIV. Later she joined the UCLA Division of Dermatology to help identify the resistance mechanisms of targeted cancer therapies using computational tools.

In 2011 she was awarded the Humboldt Research Fellowship to work in the Division of Theoretical Bioinformatics, and later the Division of Applied Bioinformatics, at the German Cancer Research Centre. There she worked on diverse bioinformatics projects with NGS data, such as studying genome-wide epigenetic regulation of cell differentiation, developing sequencing protocols and detecting somatic mutations from whole-genome sequencing data, as well as data integration and predictive modelling.

Currently, she provides bioinformatics training and support to PhD students and postdoctoral researchers in the lab of Professor Beverley Glover.

Raquel Manzano

Bioinformatician

Cancer Research UK Cambridge Institute

Areas Of Expertise:

Big data, Sensitive data, Code sharing, Data analysis, Bioinformatics, Coding, Python, R language, Git, Data visualisation, Data mining, Machine learning, Statistical analysis, Electronic Lab Notebooks, Data collection, Version control, Data storage, Institutional repositories, Discipline-specific repositories, Data sharing, Data archiving, Workshop delivery

Contact Information

raquel.manzanogarcia@cruk.cam.ac.uk

My LinkedIn Profile

ORCiD:

0000-0002-5124-8992

Biography

I am bioinformatician who has been working in Cancer Research UK Cambridge Institute since 2017. I have a background in biology and have experience with HPC, version control, R and python, and confidential data. I work with big volumes of cancer patient data on a daily basis.

Additional areas of expertise:

High Performance Computing (HPC) - cluster.

Ali Abbas, PhD

Contact Information

Biography

Andrew Thwaites, PhD

Contact Information

Biography

Arian Jamasb

Contact Information

Biography

Hugo Tavares, PhD

Contact Information

Biography

Jason Gellis, PhD

Contact Information

Biography

Qi Wang, PhD

Contact Information

Biography

Raquel Manzano

Contact Information

Biography

Filter by area of expertise

Filter by research communities:

Study at Cambridge

About the University

Research at Cambridge