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Dr Raquel Iniesta

  • Academics
  • Supervisors

BRC Lecturer in Statistical Learning for Precision Medicine


Raquel Iniesta joined King’s College London in 2013, after being working for several years in research and teaching in Barcelona. At King’s, she is a Lecturer in statistical learning and precision medicine, and leads the Topological Data Analysis interest group at the Department of Biostatistics and Health Informatics. Raquel’s academic background is in mathematics and statistics. Her interest is applying statistical and machine learning methods to identify clinical and genetic predictors of risk to complex disorders and response to treatment. Her work includes the development of novel models to predict the response to antidepressant treatments at the individual level, and to estimate the effect of genetic ancestry measures in the response to treatments. Raquel is an active and dedicated lecturer, and teaches regularly in introductory and advanced courses on statistics and machine learning for MSc and PhD students, in UK and abroad. She organises very popular monthly seminars on Machine Learning and the annual workshop in Machine Learning for health Informatics and Bioinformatics at King’s. This has made her an effective advocate for machine learning and big data methods in psychiatry.  

Research Interests:

  • Computational Statistics 
  • Machine Learning 
  • Bioinformatics 
  • Precision Medicine 
  • Genetic Epidemiology 
  • Topological Data Analysis


Raquel is teaching Research Methods and Statistics at the MSc in Affective disorders, and the MSc in Clinical Neuropsychiatry. 

She is organiser and lecturer at the Machine Learning module in the PGCert program on Applied Statistical Modelling and Health Informatics. 

She is lectured on the Prediction Modelling module from the same PGCert programme.

Expertise and Public Engagement:

Raquel is an active disseminator of research and teaching outputs from the BHI department. Aside from having worked in radio for years, she followed training on Scientific Communication at the University of Bristol and on video journalism at the University of Arts London. She works as the Scientific Communicator from the Prediction Modelling group, for which she designed a website, writes web content, manage social media accounts and produces video interviews to advertise teaching programs and leverage the public profile of the research group. She is also producing video interviews for other research groups and courses at the BHI, that are used at King’s site and in social media to promote the department.