Salmaan Ansari
About
Salmaan joined CHSS in February 2023 as a Ph.D. candidate in Applied Health Research, affiliated with the University of Kent and financially supported by the NIHR Applied Research Collaboration, Kent, Surrey, and Sussex (ARC KSS).
In addition to his doctoral studies, he expanded his role in September 2023 by taking on the position of Assistant Lecturer (Graduate Teaching Assistant – GTA) on a contract basis. In this capacity, he leads seminars within the module “A Year in Data Analytics”, further contributing to his academic pursuits and sharing his expertise with students.
He is currently pursuing his PhD, with a research focus on understanding the epidemiology of multimorbidity and service utilization among individuals living with long-term conditions, specifically in coastal communities in England. His principal objectives encompass investigating the prevalence and patterns of multimorbidity in the coastal towns, and examining how health and social care services are utilized by this population. Through this research, he aims to shed light on the unique health-related challenges faced by individuals living with one or more long-term conditions, particularly in coastal areas.
Education
• B.Sc. Hons. in Statistics from Aligarh Muslim University in India
• M.Sc. and M.Phil. in Biostatistics & Demography from International Institute for Population Sciences (IIPS) in Mumbai, India.
Fellowships
• Salmaan has received the prestigious NIHR ARC KSS Studentship to support his doctoral studies.
• He also has earned a Government of India (GOI) fellowship for his M.Sc. and M.Phil. degrees at IIPS Mumbai, India.
Research interests
His research is centered on quantitative population health research, with a specific focus on:
- Epidemiology of chronic non-communicable diseases and multimorbidity
- Exploration of challenges faced by individuals with long-term health issues, spanning physical and mental health.
- Cognitive health and psychological well-being of ageing population
- Inequalities in non-communicable diseases and associated health outcomes
In addition to his research focus, he possesses strong quantitative skills and specializes in the application of advanced statistical methods. He is proficient in utilizing a range of software tools, including R programming, Stata, SQL, and advanced Excel.
Teaching
Assistant Lecturer (Graduate Teaching Assistant - GTA)
seminars : "A Year in Data Analytics"
Supervision
Professor Lindsay Forbes (Main supervisor)
Dr Maja Niksic (Co-supervisor)
Dr Ashley Mills (Co-supervisor)