Sebastian Zeki

Sebastian Zeki

Gastroenterology consultant

Guy's and St Thomas' NHS Trust


Dr Sebastian Zeki is a consultant gastroenterologist at St Thomas’ Hospital in London. His research interests include upper gastrointestinal physiology, upper gastrointestinal cancer, natural language programming and quality metrics in endoscopy. He co-leads the Gastroenterology data sciences Institute in London


  • Endoscopic therapy
  • Oesophageal and stomach cancers/Barrett’s oesophagus
  • Oesophageal physiology
  • Heartburn; chest pain; indigestion; bloating; spasm; dyspepsia; irritable bowel syndrome; swallowing disorders; hoarse voice; chronic cough and throat clearing
  • Eosinophilic oesophagitis
  • High quality endoscopy
  • Machine learning/R/Natural language programming
  • Genomics


  • PhD - Genomics of Barrett's related malignancy, 2013

    University of London

  • Member of the Royal College of Physician, 2006

  • MSc Health Informatics, 2003

    City University

  • MBBS MBChir Medicine, 2001

    University College London

  • MA in experimental psychology, 1998

    Cambridge University


General Gastroenterology

Endoscopic therapy

Gastrointestinal cancer

Eosinophilic oesophagitis

Oesophageal physiology

Gastroenterology data science/ R / NLP



Honorary Senior Clinical Lecturer, King’s College London

King’s College

Oct 2019 – Present London

Co-head of the Gastroenterology Data Sciences Institute

Guy’s & St Thomas’ NHS Trust

Jan 2017 – Present London

Honorary Senior Clinical Lecturer, Bart’s Cancer Institute

Bart’s Cancer Institute

Jan 2017 – Present London

Consultant Gastroenterologist

Guy’s & St Thomas’ NHS Trust

Apr 2015 – Present London

Clinical Lecturer

Cambridge University: MRC Hutchison

Jun 2013 – Apr 2015 Cambridge

PhD student

Queen Mary University of London

Jan 2010 – Jun 2013 London

Gastroenterology registrar

North West Thame’s Training Rotation

Jun 2006 – Jan 2016 London

Postgraduate internal medicine training

Jun 2001 – Jun 2006 London




A basic tutorial on data science methods as applied to gastroenterological data

Improving Lesion Recognition using text

Health Foundation grant to use endoscopic and pathological free text merge with images to improve lesion recognition in trainees by automating individual metrics


A package written in R to automate extraction of endoscopic metrics from free text reports

MiFlo- a single page patient flow manager

A Shiny app that visually represents a patients timeline of investigations with summarised results as well as appointments