Skip to main content
School of Mathematical Sciences

Dr Weini Huang


Reader in Mathematical Biology

Telephone: +44 (0)20 7882 2965
Room Number: Mathematical Sciences Building, Room: MB-116
Office Hours: Math Social Hub (B11) Thursday 14:00-15:00 (in term)


Weini Huang currently works on modelling cancer evolution and species interactions in biological systems. Before being a lecturer in mathematical biology in 2018, she worked as a postdoctoral researcher in the Barts Cancer Institute, QMUL for modelling cancer spatial heterogeneity and the evolution of tumour resistance. She obtained her PhD in 2012 in Evolutionary Theory in the Max Planck Institute of Evolutionary Biology in north Germany.

Currently, Weini supervises 3 PhD students in the topics of evolutionary theory with application in species coevolution and cancer dynamics and 2 postdoctoral researchers. Weini is interested in understanding how diversity and population patterns are formed and maintained in nature/human cell populations through theoretical approaches as well as their connections with experimental/clinical observations. She collaborates with experimental evolution groups and cancer biologists/clinicians, such as the evolution of trade-offs in a bacteria-ciliate system and drug resistance in ovarian cancer, extrachromosal DNA, mtDNA dynamcis in healthy liver. 


Undergraduate Teaching

Differential Equations (2017-2018,2019-2020, 2020-2021)

Vectors and Metrices (2023-2024)

Postgraduate Teaching

Complex Systems (2018-2019)


Examples of research funding:

Life Science Initiative, QMUL (2018-2021), PI, 50,000 pounds
“Reconstructing tumour growth history by one-time sampled spatial informationthrough computational and mathematical modelling”
The Alan Turing Institute, ATI Data Science for Science Programme: Molecular Biology (2020-2021), PI, 49,056 pounds
Commission of the European Community, “EvoGamesPlus - ITN 2020” (2021-2025), CoPI and QMUL lead, 216,298 pounds
"Impact of different resistance mechanisms on the outcomes of cancer treatment game"
Cancer Grand Challenge, eDyNAmiC team, Cancer Research UK & National Cancer Institute (2022-2027), CoPI and QMUL lead, 717,475 pounds
"Extrachromosomal DNA: Understand the biology of ecDNA generation and action, and develop approaches to target these mechanisms in cance"






Google Scholar Profile 

  1. Moeller et al. (2023). Measures of genetic diversification in somatic tissues at bulk and single cell resolution. eLife. (joint corresponding author)
  2. Li et al. (2023, in print) Mutation divergence over space in tumour expansion. Journal of the Royal Society Interface. (joint corresponding author)
  3. A. Passman et al. (2023) Hepatocytes undergo punctuated expansion dynamics from a periportal stem cell niche in normal human liver. Journal of Hepatology. (joint corresponding author)
  4. Haughey et al. (2023). First passage time analysis of spatial mutation patterns reveals sub-clonal evolutionary dynamics in colorectal cancer. PLoS Comput. Biol. (joint corresponding author)
  5. J. Lange et al. (2022). The evolutionary dynamics of extrachromosomal DNA in human cancers. Nature Genetics, 54:1527-1533. (joint corresponding author)
  6. Evans et al. (2022) Clonal transitions and phenotypic evolution in Barrett’s Esophagus. Gastroenterology, 162:1197-1209.
  7. Lakatos et al. (2021) LiquidCNA: tracking subclonal evolution from longitudinal liquid biopsies using somatic copy number alterations. iScience, 24:102889.
  8. Werner et al. (2020) Measuring single cell divisions in human cancers from multi-region sequencing data. Nat. Comm., 11, 1035.
  9. Retel, Kowallik, Huang et al. (2019) The feedback between selection and demography shapes genomic diversity during coevolution. Science Advances 5 (10), eaax0530.
  10. Chkhaidze et al. (2019) Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data. Plos Computational Biology, 5(7):e1007243.
  11. Park, Pichugin, Huang et al. (2019) Population size changes and extinction risk of populations driven by mutant interactors. Physical Review E 99 (2), 022305
  12. Boddy, Huang, Aktipis. (2018) Life History Trade-Offs in Tumors. Current pathobiology reports 6 (4), 201-207. (Invited Review)
  13. Baker A-M, Huang et al. (2017). Robust RNA-based in situ mutation detection delineates colorectal cancer subclonal evolution. Nat. Comm., 8 (1), 1998.
  14. Huang et al. (2017) Dynamical trade-offs arise from antagonistic coevolution and decrease intraspecific diversity. Nat. Comm 8 (1), 2059. (corresponding author)
  15. Amado, Fernández, Huang et al. (2016) Competing metabolic strategies in a multilevel selection model. Royal Society Open Science, 3:160544.
  16. Huang et al. (2016). A resource-based game theoretical approach for the paradox of the plankton. PeerJ, 4:e2329. (joint corresponding author)
  17. Huang, Hauert, Traulsen. (2015) Stochastic game dynamics under demographic fluctuations. Proceedings of the National Academy of Sciences, 112:9064-9069.
  18. Amado, Huang et al. (2015). Learning process in public goods games. Physica A: Statistical Mechanics and its Applications, 430:21-31.
  19. Huang, Werner, Traulsen. (2012) The impact of random frequency-dependent mutations on the average fitness. BMC Evolutionary Biology, 12:160.
  20. Huang et al. (2012) Emergence of stable polymorphisms driven by evolutionary games between mutants. Nature Communications, 3:919.
  21. Huang, Traulsen. (2010). Fixation probabilities of random mutants under frequency dependent selection. Journal of Theoretical Biology, 263(2):262∼ 268
  22. Zhang, Liu, Huang et al (2008). Occurrence of Nematode parasites in raptors in Beijing, China. Journal of Raptor Research, 42(3):204∼209.



Current supervision:

Iftikhar Ahmed (2020.01- Modeling genetic diversity in hierarchical structured human tissues)

Iftikhar is from Pakistan and holds an MPhil degree in Mathematics from Abdul Wali Khan University, Mardan, Pakistan. His area of research was Fluid Dynamics and worked on a thesis titled “Some Exact Solutions of the Boundary Layer Equation and Electro-magnetic Body Force”. Studying the infectious disease models has developed his interest in Mathematical Biology. Now he is working on the deterministic model and stochastic simulation of tumor accumulation in hierarchically organized tissue structures.

Elisa Scanu (2020.09 - Modeling ecDNA dynamcis in human cells)

Before joining Queen Mary University, Elisa studied in “La Sapienza” University of Rome, Italy, where she graduated (both BSc and MSc) in Applied Mathematics with the highest marks, and she spent a semester in Queen Mary University as an Erasmus+ student. She is also working in the Biology Department of “Tuscia” University of Viterbo, Italy, as a contract teacher for a 1st year module in Mathematics.

Elisa’s PhD project is to use stochastic models based on simple mechanistic assumptions to explain observed ecDNA patterns in human cells, including healthy tissues and tumours. The project will be done in cooperation with Barts Cancer Institute at the School of Medicine and Dentistry in Queen Mary University of London.

Christo Morison (2021.09 - Cancer dynamics and mutation burden distribution)

Funded by EU ITN programme, Christo works on modeling the mutation accumulation in birth-death processes. He also work on coevolution of cancer and immune cells as well as the progenitor cell dynamics in prostate cancer.

Alan Scaramangas (2023. 02 - Postdoctoral Researcher)

Funded by Cancer Grant Challenges (eDyNAmic), Alan works on modeling ecDNA dynamics in constant population. Before joining qmul, Alan did his PhD in applying evolutionary game theory for modeling aposematic prey populations.

Poulami Ganguly (2023. 03 - Postdoctoral Researcher)

Funded by Cancer Grant Challenges (eDyNAmic), Poulami works on stochastic models of ecDNA and RNA copy number dynamics. Prior to joining Queen Mary, Poulami completed a PhD in applied mathematics in the area of inverse problems and convex optimization.

Past members:

Dr. Nathaniel Mon Pere (2020.12 - 2021. 05)

Nathaniel is a theoretical physicists worked in our group as a Postdoctoral researcher on the topic of somatic evolution and mutation burden dynamics. Now he is a postdoctoral researcher in Barts Cancer Institute, QMUL.

Dr. Magnus Haughey (2018.11 -2022.09) studied in physics and was a PhD student in our group modeling spatial dynamics in cancer evolution and is now a postdoctoral researcher in Barts Cancer Institute, QMUL.

Dr. Marius Moeller (2018.05 - 2022.12) studied applied mathematics and was a PhD student in our group working on the topic of random mutation accumulation in healthy tissue. He is currently a postdoctoral researcher in a bioinformatic group at the University of Lübeck. 


Back to top