Research and Outputs

Our research team have created a range of outputs over the years.

Researchers at HESRI have a variety of strengths across many fields. We bring a wealth of experience and insight to our research projects.

Prof Zachary Munn

Professor Zachary Munn is an expert evidence synthesis, implementation and guideline methodologist who has led the development of dozens of systematic review and guideline projects for a diverse range of policymakers, guideline developers and others. He further specialises in many other evidence synthesis methods, multi-stakeholder engagement, and making trustworthy recommendations.

Dr Timothy Barker

Dr Tim Barker is an expert in multiple evidence synthesis types in addition to reviews of interventions. He is skilled at meta-analysis, risk-of-bias assessment, and the GRADE approach. Dr Barker also works with groups to develop trustworthy guidelines and recommendations.

Dr Danielle Pollock

Dr Pollock is a lived experience researcher who has significant experience with end-user and public engagement in evidence synthesis. She is a world-leader in the conduct of scoping reviews, and other qualitative and mixed-methods reviews.

Dr Raju Kanukula

Dr Kanukula specialises in systematic reviews and meta-analysis. He has a wealth of experience with risk of bias assessments and research methodologies. 

Ms Sabira Hasanoff

Ms Hasanoff's research interests include risk of bias assessments, scoping reviews, and the GRADE approach.

Ms Grace McBride

Ms McBride has expertise in guideline development, clinical trials, and pregnancy research. She excels at conducting evidence synthesis projects and qualitative research.

Dr Mafalda Dias

Dr Dias is a health evidence researcher with expertise in the critical appraisal of medical literature, methods for assessing the certainty of evidence, evidence synthesis, and both quantitative and qualitative research.

HESRI are a trailblazing research group, whose highly cited and impactful publications have been widely influential in the field of evidence synthesis.

See our work below: