Penn State’s Institute for Computational and Data Sciences awarded this year’s seed grant program, offering more than $500,000 to Penn State scientists. The seed grants will fund 14 different proposals from researchers who represent five different colleges, including 3 proposals from the Eberly College of Science.
Some of the seed grants will fund carbon capture technology, ultrasonics, galaxy surveys, artificial intelligence, equitable disease prediction and quantum machine learning.
This year’s funded projects from the college are:
Galaxy Survey Moonshot
Computers are helping astronomers map the vastness of space, prompting new discoveries, as well as inspiring new questions. Joel Leja and Ashley Villar, both assistant professors of astronomy and astrophysics and both ICDS co-hires, have been awarded seed grant funding for to use a machine learning technique that promises to be about 10 million times faster than traditional analyses to better interpret galaxy imaging.
Quantum Machine Learning
Quantum computing, which uses the principles of quantum mechanics to make calculations, is an emerging technology that promises to unleash massive computational power on certain tasks, including machine learning. Xiantao Li, professor of mathematics in Penn State’s Eberly College of Science, will serve as the primary investigator to explore quantum computer-based machine-learning, specifically in the use of quantum computing algorithms to accelerate the training of machine-learning models.
Equitable Disease Prediction
Developing novel statistical methods to integrate various genomic data sets may pave the way for more equitable — and more effective — disease prediction in diverse human populations. Xiang Zhu, assistant professor of statistics and ICDS associate, will serve as the primary investigator for the project, “Powerful and equitable disease prediction from large-scale DNA biobanks and single-cell multiomics.”
Find out more about the ICDS seed grant program at the ICDS website.