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Neha Bansal

Neha Bansal

(she/her)

Teams and roles for Neha Bansal

Overview

I am a PhD student at Cardiff University with the OneZoo CDT program. My research focuses on developing deterministic and stochastic mathematical models to explore the transmission of viruses in indoor spaces. These models are intended to assist policymakers and indoor space managers in making informed decisions during epidemics. My Master's thesis delved into characterising reproductive value in age-structured population models, which was applied to understand disease dynamics under varying environmental conditions. Prior to my Master's program, I worked as a data science professional in industry for 6 years.

Publication

Research

Stochastic modeling of biological systems. 

Biography

Education - 

  1. PhD in Applied Mathematics, Cardiff University, UK (Oct'2023 - current)
  2. MSc in Applied Mathematics, University of British Columbia, Okanagan, Canada (Jan'2021 - Aug'2023)
  3. B.Eng. in Pulp and Paper Technology, Indian Institute of Technology, Roorkee, India (July'2011 - May'2015)

Work Experience - 

  1. Data Scientist, HP R&D Center, Bengaluru, India (Aug'2018 - Aug'2021)
  2. Functional and Strategy Analyst, Accenture Inc, Bengaluru, India (Aug'2017 - July'2018)
  3. Senior Business Analyst, Affine Analytica Pvt. Ltd., Bengaluru, India (May'2015 - July'2017)

Scholarships - 

  1. Studentship for PhD by OneZoo CDT
  2. University Graduate Fellowship for MSc in Canada
  3. Merit-cum-Means Scholarship for B.Eng in India

 

News articles

Neha Bansal, Dr Katerina Kaouri and Dr Thomas E. Woolley’s newly published study could inform public health policy decisions.

Researchers from the School of Mathematics propose new approach that more accurately predicts the evolution of epidemics

30 April 2026

Neha Bansal, Dr Katerina Kaouri and Dr Thomas E. Woolley’s newly published study could inform public health policy decisions.

Contact Details

Email [email protected]

Campuses Abacws, Floor 2, Room 2.65, Senghennydd Road, Cathays, Cardiff, CF24 4AG

Specialisms

  • Stochastic analysis and modelling
  • Applied statistics
  • Applied mathematics
  • Epidemic modelling
Neha Bansal, Dr Katerina Kaouri and Dr Thomas E. Woolley’s newly published study could inform public health policy decisions.

Researchers from the School of Mathematics propose new approach that more accurately predicts the evolution of epidemics

30 April 2026

View all news articles