Los Alamos students receiving awards Tuesday at the 29th Annual New Mexico Supercomputer Challenge awards ceremont are, from left, Logan Dare, Los Alamos Middle School, Robert Straus, Los Alamos High School, Lillian Petersen, Los Alamos High School, Christie Djidjev, Los Alamos High School and Rishi Tikare Yang, Albuquerque High School. Not pictured is Garyk Brixi, Winston Churchill High School. Courtesy photo
SUPERCOMPUTING CHALLENGE NEWS
Tuesday was the culmination of the 29th Annual New Mexico Supercomputing Challenge held in Albuquerque at the Central New Mexico (CNM) main campus and the University New Mexico (UNM) Science and Technology Park.
Lillian Petersen from Los Alamos High School and Garyk Brixi from Winston Churchill High School, Potomac, Maryland won first place for their project, “A Novel Computational Tool to Inform Cost-Effective Nutrition Interventions in Sub-Saharan Africa”. See their final report. https://www.supercomputingchallenge.org/18-19/finalreports/28/Supercomputing_Challenge_Report.pdf .
They have presented their prior work at international, professional conferences on nutrition in Africa. Their research has three components. From their executive summary:
Malnutrition contributes to nearly half of childhood deaths, while treatment reaches a small fraction of those in need. Treatment delivery is hampered by costly ingredients and inefficient supply chains. Here we develop a three-component tool to inform acute malnutrition treatment interventions.
First, we forecast the geospatial demand for acute malnutrition treatment using a
machine learning algorithm.
Second, we optimize low-cost recipes for specialized nutritious foods while meeting
nutritional standards. Recipes were optimized for both international production and local production in 24 sub-Saharan African countries, and both achieved ingredient cost
reductions of up to 60% compared to current recipes.
Third, we model a supply chain of the optimal production and distribution of acute
malnutrition treatment with both international and local factories while accounting for
production and transportation costs.
Their machine learning algorithm uses 41 data sources ranging from real-time satellite imagery to static demographic data. The most significant predictor turned out to be female education level. They have partnered with Valid Nutrition an NGO from Kenya (ww.validnutrition.org) to prototype their recipes and verify the cost and nutritional content.
Second place went to Robert Strauss from Los Alamos High School and Logan Dare, Los
Alamos Middle School. The title of their project is “Simulation as a Tool for Risk Assessment of Coastal Areas”.
See their final report at:
Their model was used to study the 2018 tsunami which devastated Palu city, Indonesia and the 2018 Anak Krakatoa tsunami. Their computational model successfully predicts both the areas of extreme damage and safe areas with little damage.
Our first and second place teams did astonishing professional level work!
We highly recommend you follow the above links and take a closer look at these projects.
There was a tie for third place: Rishi Tikare Yang from Albuquerque High with a “Traffic Model” See the final report at https://www.supercomputingchallenge.org/18-19/finalreports/4/TrafficModelFinalReport.pdf
And, Christie Djidjev from Los Alamos High with a “Data-Based Approach to Estimating
Ice-Shelf Melt Rates. See the final report –
Scholarships and Other Awards
For a complete list of all winning student teams –
Scholarships worth $27,400 were awarded at the Supercomputing Challenge Awards
Ceremony. Many other awards were distributed ranging from random $100 gifts for finishing the academicmarathon to team prizes for teamwork, programming prowess, and environmental impact, etc.
All final reports are online at