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Consultant Profile

Min Sun

Areas of Consultancy:
Applied operational research
Bayesian methods
Bioassay
Clinical trials
Design and analysis of experiments
Exploratory data analysis
GLMs and other non-linear models
Graphics
Multivariate analysis
Neural networks and genetic algorithms
Non-parametric statistics
Numerical analysis and optimisation
Pattern recognition and image analysis
Probability
Sampling
Simulation
Statistical computing
Statistical inference
Survival analysis

Region of consultancy:
Worldwide

Profile

~10 years experience in pharms R&D, spanning from discovery to early clinical phase. From first principles, my work designs modelling languages that reveal the underlying structure of complex systems. Statistics, mathematics, machine learning, and dynamical reasoning serve not as separate toolkits, but as coherent expressions of shared logical foundations. These frameworks allow learning algorithms to emerge naturally from real-world problems, producing models that are both expressive and interpretable. Modelling in this view, becomes a process of uncovering the rules, dynamics, and stochastic systems that generate data – more than merely fitting patterns within it.

Background

Mathematics and Statistics by training. Extensive experience with omics (RNAseq + proteomics), PKPD (pharmacokinetics/pharmacodynamics), high dimensional biomarker (flow cytometry, cytokine, HLA etc), microscopy image, preclinical/clinical efficacy and safety data

Specialisms

Data science in general, including but not limited to - Statistical modelling on multivariate and infinite dimensional variables with dimensional reduction, e.g. functional data analysis, GLM, mixed effect model, LASSO, Bayesian inference, survival analysis, circular statistics - Power/sample size calculation - Simulation - Statistical computing - Machine learning and deep learning, e.g. classification, clustering and image analysis - Non-parametric statistics - Applied operational research - System of differential equations - Graph theory & abstract algebra with applications to data analysis - Optimisation, with custom loss function

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