Dr Daniel Stamate

Department of Computing
Goldsmiths, University of London
London SE14 6NW, United Kingdom
Email: d.stamate AT gold.ac.uk Tel: +44(0)2079197864

Profile and activity

  • I am a Machine Learning scientist, research team leader, Data Science MSc Programme Director, and Data Science, Machine Learning & Artificial Intelligence industry expert speaker and consultant. I established and lead the Data Science & Soft Computing Lab, and initiated, designed and run the MSc in Data Science at Goldsmiths - which inspired and was mostly replicated into similar online programme to come at University of London. I have a background in Computer Science and Mathematics, holding an MSc degree in Computer Science & Mathematics from University of Iasi - Faculty of Mathematics, and a PhD in Computer Science from University of Paris-Sud - LRI Computer Science Laboratory, Orsay.

  • Research profile
    My current research concerns the broader areas of Data Science and Artificial Intelligence. In particular I am interested in Machine Learning, Statistical Learning, and Predictive Modelling with a particular focus on: (a) Classification algorithms of novel decision trees and ensemble based methods based on newly proposed parameterised impurity families and statistical pruning approaches; (b) Sentiment analysis & stock market forecasting; (c) Predictive modeling and computational psychiatry – ongoing work in collaboration with Institute of Psychiatry, Psychology and Neuroscience at King’s College London, and Department of Psychiatry and Neuropsychology at Maastricht University Medical Centre; (d) Novel machine and statistical learning approaches to understand heterogeneous manifestations of asthma in early life, work in collaboration with the Department of Medicine, Imperial College London; (e) Predicting risk of dementia using routine primary care records, work in collaboration with University of Manchester and other partner universities (f) Mobility big data analytics – in particular focusing on analysing smart card Oyster data of Transport for London. Another component of my research focuses on data uncertainty approaches, and soft computing. I previously worked in statistical databases, databases with uncertain information, and information integration.
    For more details see research work and selected publications.

  • Research projects:

    January 2018 – January 2020, Chief Co-Investigator at Goldsmiths: Development of a Prediction Tool for Identifying Patients at High Risk of Subsequently Developing Dementia, Using Routine Primary Care Records. ARUK grant £240,000 in collaboration with University of Manchester – PI David Reeves, and partner universities, with £110,000 share for my team at Goldsmiths. I am leading on the Machine Learning aspects of this Alzheimer's Research UK funded study of Predicting Risk of Dementia covered on BBC News.

    September 2017-September 2019, Project Coordinator: Data Science Research and PG Mobility. EU Erasmus+ funded, 54,000 Euro. Partner institution National Research Tomsk State University.

    ◆ April 2014- April 2018,
    Project Coordinator: Prediction Modelling Approaches to Data-driven Computational Psychiatry. Funding body: Saudi Government, value £175,000+, supporting PhD work of Wajdi Alghamdi.

    ◆ April 2000- March 2002,
    Principal Investigator: Integrating imperfect information from multiple web sources, EU funded, 108,000 Euro Marie Curie Individual Grant.

Recent activities and roles

PhD supervision

  • Rapheal Olaniyan, part time PhD candidate in Computer Science – Machine Learning Approaches to Sentiment Analysis & Stock Market Forecasting. Currently Core Modeller Data Scientist at Deutsche Bank (1st supervisor)

  • Jiri Marek, part time PhD candidate in Computer Science - Behavioural Finance (1st supervisor)

  • Mihai Ermaliuc, part time PhD candidate in Computer Science - Data Science, to start September 2018 (1st supervisor)


  • Wajdi Alghamdi, PhD in Computer Science (Data Science), Goldsmiths, completed June 2018, (1st supervisor)

  • Majed Alsanea, PhD in Computer Science, Goldsmiths, completed 2015, (2nd supervisor)

  • Yann Loyer, PhD in Computer Science, University of Paris-Sud, France, completed 2001, (2nd advisor)

Current or recent courses

BSc Computing:
Data Mining

MSc Data Science:
Machine Learning & Statistical Data Mining
Data Science Research Topics
Final Project

Past recent courses:
Advanced Database Technologies - Data Warehousing and Data Mining,
in BSc and MSc Computing
Database Systems,
in BSc Computing
Databases, Networks and the Web,
in BSc Computing
Digital Research Methods: Computational Statistics and Data Mining; Statistical Data Mining,
in MA/MSc Digital Sociology
MA/MSc Digital Journalism
MA/MSc Creating Social Media
MSc Digital Entrepreneurship