Google, PNNL internships in data science


Jul 29, 2021
Google, PNNL internships in data scienceBy Shawn Hutchins

Data science is a crucial area of research that is significantly impacting computational finance and economics, energy, manufacturing and supply chain logistics, health care, and many other industrial arenas. 

A new partnership with Google, Nancy Dunlap, and Rice University’s Department of Computer Science offers research experiences for undergraduates (REU) in data science. The 10-week summer program is competitive and provides hands-on data science projects to students who are enrolled in North American colleges and universities. Dunlap provided the funding required to permit more Rice University students to attend the program.

This summer, 16 undergraduate students, participated in the REU program. Specific data science research opportunities included working with computational finance concepts, reproducing portfolio construction results, designing and implementing new machine learning algorithms, applying machine learning algorithms to solve specific problems, and developing methods to manage huge data sets. 

Students in the REU program are guided by faculty mentors and work closely with doctoral students as they perform cutting-edge research.

John Dobelman and Jabes GallardoJohn Dobelman, a professor in the practice of statistics and associate director of the Center for Computational Finance and Economic Systems (CoFES), and statistics doctoral student Alejandro Aguilar advised Jabes Gallardo, an undergraduate student from the Rio Grande Valley in south Texas who is majoring in finance and applied mathematics at MIT.

Pictured here are Dobelman and Gallardo at the Data Science REU poster session and reception.

For his summer REU project, Gallardo implemented a momentum and fundamentals-based portfolio selection algorithm called the MaxMeasures with a factor analysis (FA) model to examine key financial ratios combined with a ranking-based momentum identification technique for the S&P 500 stocks. Momentum was measured over the prior 12 months and fundamental trends over the past five years.  

While serving as a mentor in the REU program, Aguilar worked on a data science research project of his own as an intern with Pacific Northwest National Laboratory (PNNL), a U.S. Department of Energy national laboratory. 

Aguilar, a fifth-year doctoral student in the Department of Statistics, is also from the Rio Grande Valley. His research in CoFES under Katherine Ensor’s direction combines topological data analysis and statistical algorithms to study the multidimensional landscape of stock market volatility. Ensor is the Noah G. Harding Professor of Statistics and director of CoFES.

Aguilar was recently awarded a GEM Fellowship from the National GEM Consortium. Designed to foster opportunities for graduate students to enter careers in industry, GEM Fellows benefit from work experiences through an employer sponsor and a portable academic year fellowship of tuition, fees, and a stipend.

He has a B.S. and M.S. in applied mathematics from the University of Texas-Pan American, and a B.A. in economics and a minor in German from the University of Michigan-Ann Arbor.

For future applications to the REU data science program, visit