June 6, 2023

SMC Data Challenge Info Session

Looking for a new project for your CV / resume? Whether you are a recent UTRGV grad or currently taking summer classes, you are invited to participate in the 7th Annual Smoky Mountains Computational Sciences Data Challenge (SMCDC23). This is a great way to publish a paper, present at a conference, and get the attention of national labs. 

Here is a list of the challenges:  

Challenge 1: Machine Learning approaches to High Throughput Phenotyping 

Challenge 2: Diamonds and ice: when is H2O no longer a molecule? 

Challenge 3: HPC Power and Thermal Characteristics in the Wild   

Challenge 4: Automating signal extraction – scientist vs computer     

Challenge 5: AI-Driven Discovery using Science Knowledge Graphs 

Challenge 6: Sustainable Cities- Socioeconomics, Building Types, and Urban Morphology 

Challenge 7: EAGLE-I Outage Data 2014-2022  

The info session will give an overview of the challenges, and a participant in SMCDC22 will offer her perspective about the experience. For help being matched to a team and/or faculty mentor from UTRGV, fill out this form: https://forms.gle/GPdW4zMxaEpZZtKb8

About the speakers

Ms. Kristen Hallas is a second-year graduate student pursuing a PhD in Mathematics and Statistics with Interdisciplinary Applications at the University of Texas Rio Grande Valley (UTRGV). She earned her B.S. in Applied Mathematics with Computer Science minor at UTRGV in Spring 2022, graduating Summa Cum Laude. Kristen interned with the High-Performance Computing (HPC) Security Analytics & Monitoring Group at Oak Ridge National Lab in 2022, designing a full-stack, interactive visualization of an HPC system. She participated in the 6th Annual Smoky Mountains Computational Sciences Data Challenge (SMCDC22), presented her preliminary findings, and was recognized as a Runner Up for Best Lightning Talk. Her current research interests include developing smart manufacturing technologies, optimizing mathematical and statistical models, creating reliable/long-lasting HPC systems, and furthering inclusive/accessible STEM education. After graduating, Kristen envisions herself building systems towards positive aims, such as expanding environmental sustainability or protecting digital connectivity, on a team dedicated to advancing scientific progress.

Dr. Mike Lindstrom is an Assistant Professor at UTRGV's SMSS School of Mathematical And Statistical Sciences as of Fall 2022. He completed his undergrad (BSc. Physics and Mathematics combined honours) and grad studies (MSc and PhD in Applied Math) at University of British Columbia, Vancouver, BC, Canada. He conducted postdoctoral work as an Assistant Adjunct Professor for the Program in Computing at UCLA (University of California, Los Angeles). His research areas include mathematical modelling, applied differential equations, scientific computing, formal asymptotics, and data science. Currently, he is Faculty Advisor for The Mathematical Contest in Modeling (MCM) and he has initiated an informal Ultimate Frisbee group at UTRGV's Edinburg campus. Anyone in the Math & Stats department on either campus is welcome: grad students, postdocs, staff, and faculty, plus friends.