Data Science

I am interested in an interdisciplinary research that includes applying mathematical techniques on language modeling, natural languages processing, machine learning, data mining, and data visualization. In particular, I employ techniques such as principal component analysis and markov chain models.

Natural Language

The foundations of human culture is a linguistic enigma. I am interested in research problems involving mathematical modeling and statistical analysis of natural languages. I seek to develop models that describes how language - its word meanings and syntax - evolved in time using machine learning algorithms and evolutionary models. I use modern natural languages processing techniques and data science methods to extract information from available linguistic data.


As part of my interdisciplinary research interests, I am also interested in modeling biological phenomena involving dynamic predation movements of individual agents of a particular species. My collaborators and I developed a spatio-temporal stochastic model that describes the predation movements of the subsocial arachnid Anelosimus studious using stochastic partial differential equations.



  • Quijano, A.J., Joyner, M. L., Ross, C., Watts, J. C., Seier, E., & Jones, T. C. (2016). Spatio-temporal analysis of foraging behaviors of Anelosimus studiosus utilizing mathematical modeling of multiple spider interaction on a cooperative web. Journal of theoretical biology, 408, 243-259.


  • Quijano, A.J., Joyner, M. L., Seier, E., Hancock, N., Largent, M., & Jones, T. C. (2015). An aggregate stochastic model incorporating individual dynamics for predation movements of anelosimus studiosus Mathematical biosciences and engineering: MBE, 12(3), 585-607.