CV

Education

• B.S. in Electrical Engineering, Rice University, 2013
• M.S. in Computational and Mathematical Engineering, Stanford University, 2017
• Ph.D in Computer Science, Carnegie Mellon University, 2023 (expected)
• PostDoctoral Fellow in Genetics, Stanford University,

Work experience

• Summer 2022: Quant Research Intern
  • Atalaya Capital Management
  • Duties included: Predicting returns on high risk personal loans. Built an ML model that correlated highly what industry at larged valued these loans.
• August 2017 - June 2018: Senior Data Scientist
  • Arnhold Institute
  • Duties included: Explored ways to use data science for social good
  • Supervisor: James Faghmous

Courses at CMU

• Convex Optimization, Advanced Introduction to Machine Learning, Computational Genomics,Cellular Systems Modelling, Laboratory Methods, Intro Computational Structural Biology, Quantum Integer Programming, Linear Programming

Courses at Stanford and Rice

• Numerical Linear Algebra, Discrete Mathematics and Algorithms, Convex Optimization, Stochastic Methods in Engineering, Stochastic Modeling, Deep Learning for Vision, Deep Learning for NLP, Machine Learning, Stochastic Graphical Models, Applied Statistical Learning, Theory of Statistics, Structure of Social Data, Decision Making Under Uncertainty, Rein- forcement Learning, Information Theory, Advanced Matrix Analysis