Apache Airavata

2024 ~ Present | Georgia Tech Center for Artificial Intelligence in Science and Engineering Georgia Tech Institute for Data Engineering and Science Computational Science and Engineering, College of Computing Sponsored by the National Science Foundation (NSF) and National Aeronautics and Space Administration (NASA)

Goals

Airavata 2.0 is a cutting-edge project that aims to revolutionize computational experiments. Students interested in contributing to a groundbreaking initiative at the intersection of technology and science should consider this project.
 
Key goals include:
● Computing Continuum: Funded by the National Science Foundation (NSF) Cybershuttle project and NASA's Visualization, Exploration, and Data Analysis (VEDA) initiative Airavata 2.0 integrating various computational resources, ranging from local hardware to supercomputers, creating a computing continuum. This provides an innovative opportunity for students to work with advanced distributed systems concepts.
● AI-based: Airavata 2.0 is developing a novel, user-friendly Natural Language Interface and AI-based automation. The NL interface will allow users to communicate with the system using conversational language, making it easier to use. Further, leveraging recent advances in large language models, airavata’s AI will automate and optimize complex workflows, dataset management, and model performance evaluation, providing students with practical experience in AI and machine learning.
● Open Source: Students will participate in a top-level Apache Software Foundation’s open-source project following the popular “Apache Way” governing principles. Significant Contributions to Apache Airavata has the potential to become Apache Committers, a reputed recognition while gaining experience in collaborative software development, community engagement, and the open-source ecosystem.
● Interdisciplinary: Airavata 2.0 is a multidisciplinary initiative that connects technology with various scientific domains. Students from different fields can collaborate, learn from each other, and see how computational science is applied in diverse research areas.
● Impact: Contributions to Airavata 2.0 can significantly impact scientific research, offering students a chance to be part of a project with real-world applications and benefits.

Issues Involved or Addressed

Computing Continuum, simplifying the interaction with diverse and advanced computational resources;
● AI Integration, Implementing AI for workflow automation and model optimization.
● Natural Language Interfaces: Enhancing the system's ability to understand and process user commands in natural language
● User Interface Design: Developing a user-friendly interface for complex computational systems.
● Data Security: Ensuring high standards of data security and privacy.
● Scalability and Performance: Optimizing the system for handling large-scale tasks efficiently.
● Interoperability: Ensuring new features work seamlessly with existing Apache Airavata components.
● Documentation: Creating clear, comprehensive guides and user documentation.

 

Methods and Technologies

  • AI
  • Distributed Systems
  • Cloud Native Systems
  • Open Source Development

Academic Majors of Interest

  • ComputingComputational Science and Engineering
  • ComputingComputer Science
  • ComputingCybersecurity
  • ComputingHuman-Centered Computing
  • EngineeringApplied Systems Engineering
  • EngineeringComputer Engineering
  • EngineeringElectrical Engineering
  • EngineeringMechanical Engineering

Preferred Interests and Preparation

Interests:

● Computational Science: A keen interest in computational experiments and scientific research.

● Software Development: Passion for developing software solutions and working on open-source projects.

● AI and Machine Learning: Fascination with AI, machine learning, and natural language processing technologies.

● Data Security: Interest in the challenges of data security and privacy in software systems.

● User Experience Design: Enthusiasm for creating user-friendly interfaces and improving user interaction.
 
Preparation:

● Academic Background: Coursework or knowledge in computer science, data science, or related fields.

● Research: Familiarity with scientific research processes and computational experiments.

● Open-Source Projects: Experience or familiarity with contributing to open-source projects is beneficial.
 
Suggested Skills:

● Programming: Proficiency in programming languages like Python, Java, or similar.

● AI and ML Knowledge: Understanding of basic AI and machine learning concepts and algorithms.

● NLP Basics: Knowledge of natural language processing techniques.

● UI/UX Design: Skills in user interface design and experience with UI design tools are a plus.

● Data Security Principles: Awareness of fundamental data security and privacy practices.

● Software Development Tools: Familiarity with version control (e.g., Git), testing frameworks, and CI/CD pipelines.

● Communication and Collaboration: Good communication skills for collaborative development and documentation.

Meeting Schedule & Location

Time 
11:00-11:50
Meeting Location 
Klaus 1440
Meeting Day 
Friday

Team Advisors

Suresh Marru
Dimuthu Wannipurage

Partner(s) and Sponsor(s)

Georgia Tech Center for Artificial Intelligence in Science and Engineering Georgia Tech Institute for Data Engineering and Science Computational Science and Engineering, College of Computing Sponsored by the National Science Foundation (NSF) and National Aeronautics and Space Administration (NASA)

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