AMLSS Graduate Students

Armando Salinas

Armando Salinas

  • Ecology
  • Epidemiology

Baltazar Espinoza Cortes

Baltazar Espinoza Cortes

  • Dynamical systems
  • Epidemiology
  • Game theory
  • Economics

Bechir Amdouni

Bechir Amdouni

Applying mathematical modeling techniques as as well as statistical tools to understand and possibly explain social and behavioral issues such as dropout, bullying, peer interactions in schools, crimes, etc. 

Caleb Ignace

Caleb Ignace

Modeling of topics in areas such as social insects and epidemiology.

Carlos Cruz

Carlos Cruz

My interests lie in Mathematical Biology and Epidiomiology. Other things like Agent-based Modeling are also of interest to me. 

Cesar Montalvo

Cesar Montalvo

  • Mathematical modeling
  • Economics to end poverty
  • Public policy for Infrastructure
  • Health and Sanitation
  • Higher Education
  • Politics for majorities

Dustin Padilla

Dustin Padilla

  • Population dynamics
  • Differential equations
  • Ecological modeling
  • Epidemiology
  • Evolution
  • Stochastic process
  • Complexity
  • Sustainability
  • Robustness of social-ecological systems

Fan Yu

Fan Yu

  • Hype-performance Computational Analysis.
  • Data Mining.
  • Probabilistic Modeling and Statistical Method.
  • Stochastic Process.
  • Predictive Modeling.
  • Optimization.
  • Demand Forecasting and Promotion Analysis.
  • Customer Behavior Study.
  • Genetic Sequencing.
  • Genetic Population Modeling.

Joffa Applegate

Joffa Applegate

Joffa's interests are in modeling an interdisciplinary mix of theory of the firm, political economy, institutional and policy analysis, and participatory governance.

Joffa is working toward developing a theory of firms as an ecological system comprised of for profit, non-profit and other NGO and hybrid constructs, focusing on the interplay of capital access, infrastructure, governance and employment. She believes that a healthy firm ecology will be dynamic, robust and diverse, leading to increased productivity, well-being and engagement.

Her focus is on applying dynamic and agent based modeling techniques to understand and explain how firms form and interact and the degree to which institutional arrangements support that activity, as well as how to develop and communicate these models to enhance decision making.

Jordan Bates

Jordan Bates

  • Computational social science
  • Modeling human social systems with the goal of improving institutional design

Josean Velazquez Molina

Josean Velazquez Molina

  • To Be Announced

Juan Melendez Alvarez

Juan Melendez Alvarez

  • Mahematical Biology
  • Physiology
  • Numerical Analisys
  • Epidemiology

Juan Renova

Juan Renova

  • Computational mathematics
  • Inverse problems, and image processing
  • Mathematical modeling
  • Dynamical systems

Jun Chen

Jun Chen

  • Animal behavior of ants and honey bees 
  • Dynamic system
  • Optimization 
  • Epidemiology 

Karen Funderburk

Karen Funderburk

  • Mathematical Modeling 
  • Epidemiology
  • Molecular Biology

Michael Lin

Michael Lin

  • Behavior of ant colonies as interacting particle systems
  • Information flow
  • Task allocation
  • The process by which self-organized structures emerge
  • Image analysis
  • Particle tracking
  • Network analysis
  • Agent-based modelling
  • Statistical mechanics
  • Machine leaning techniques

Mugdha Thakur

Mugdha Thakur

  • Mathematical Modelling
  • Public Health
  • Gender and Interpersonal Relations

Steven Madler

Steven Madler

  • Resource distribution
  • Societal outcomes
  • The tragedy of the commons
  • The impact of increased interconnectivity of society and information
  • Approaches grounded in agent-based modeling
  • Complex adaptive systems
  • Epidemiology
  • Game theory
  • Systems analysis
  • How such approaches may create policy insights to help strengthen a vibrant social fabric.

Victor Moreno

Victor Moreno

  • Epidemiology
  • Geometric Number Theory
  • Graph Theory

Byong Kwon

Byong Kwon

  • Autonomous systems
  • Evolutionary algorithms
  • Evolutionary robotics
  • Machine learning
  • Nonlinear optimization