-
Notifications
You must be signed in to change notification settings - Fork 5
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
2 changed files
with
43 additions
and
3 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,42 @@ | ||
--- | ||
title: "NSF CAREER Award" | ||
excerpt: "NSF CAREER Award." | ||
categories: | ||
- grants | ||
image: | ||
thumbnail: /images/grants/nsf.png | ||
caption: "" | ||
tags: | ||
- ai | ||
- robotics | ||
--- | ||
|
||
Published on: February 2023 | ||
|
||
> [CAEE News](https://caee.utexas.edu/news/1132-krishna-kumar-receives-nsf-career-award) | ||
# HayaRupu: Accelerating Scientific Discoveries in Natural Hazard Engineering | ||
|
||
Natural hazards such as landslides, floods, and earthquakes pose significant risks to communities worldwide, challenging the resilience of critical infrastructure and the safety of populations. In the face of these threats, the HayaRupu project emerges as a groundbreaking initiative aimed at harnessing the power of Artificial Intelligence (AI) to transform natural hazard engineering. Funded by forward-thinking organizations seeking to leverage technological advancements for societal benefit, HayaRupu is spearheaded by a team of dedicated researchers and engineers committed to innovation and excellence in scientific discovery. | ||
Advancing Natural Hazard Engineering through AI | ||
|
||
The core ambition of HayaRupu is to accelerate advancements in engineering and scientific research with a specific focus on landslide hazards. This initiative is pioneering an AI-accelerated scientific discovery loop, an innovative framework that integrates AI into every stage of scientific inquiry. By employing machine learning (ML) techniques for advanced pattern recognition and anomaly detection, HayaRupu aims to unearth new insights from complex datasets, addressing pivotal knowledge gaps in natural hazard engineering. | ||
|
||
## Key Objectives of the HayaRupu Project | ||
|
||
HayaRupu is driven by three main objectives: | ||
|
||
- Development of Context-Aware Knowledge Graphs: These knowledge graphs act as reasoning engines, enabling data-driven discoveries and facilitating the derivation of fundamental equations through geometric deep learning. This represents a significant leap forward in our understanding and prediction of natural hazards. | ||
|
||
- Creation of NextGen AI-Accelerated Simulators: By integrating AI into numerical simulations, HayaRupu is developing optimization strategies that combine the speed of AI with the accuracy of traditional simulations. This innovative approach aims to revolutionize the way engineers and scientists approach problem-solving in natural hazard engineering. | ||
|
||
- Fostering an Integrated Workflow with Large Language Models: The project seeks to demonstrate the potential of AI in enhancing scientific workflows. By automating design processes and decision-making, HayaRupu is setting new standards for efficiency and effectiveness in research and development. | ||
|
||
## Educational Outreach and Community Building | ||
|
||
A cornerstone of HayaRupu's mission is its commitment to education and community engagement. By developing AI-assisted, personalized learning experiences for engineering students, the project is cultivating a new generation of engineers skilled in AI and natural hazard management. Educational outreach efforts, including collaborations with public libraries and high school programs, aim to inspire young minds and promote diversity in STEM fields. | ||
|
||
As we look to the future, the promise of AI-driven advancements offers hope and direction in our ongoing efforts to protect and serve communities threatened by the unpredictable forces of nature. | ||
|
||
|
||
[NSF Awards page](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339678&HistoricalAwards=false) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters