Addi Malviya Thakur
Group Leader - Software Engineering Group
Bio
Addi (Aditi) Malviya-Thakur serves as Group Leader for the Research Software Engineering Group in the Computer Science and Mathematics Division's Advanced Computing Systems Research Section at the 91°µÍø. In this role, Addi aspires to innovate and inspire the next generation of cutting-edge scientific software, thus enabling 91°µÍø (ORNL) to host the world's premier scientific software engineering group and transform science with software defined solutions that are reliable, usable, and trustworthy. This includes lab-wide engagements on core and cross-cutting initiatives to gauge how scientific software can advance programs and projects and collaborations on efforts such as Exascale computing, AI Initiative, information systems, federated data and platform management, geospatial intelligence, cyber-physical systems, national security, and others.
Addi is an experienced leader with a strong background in leading teams and architecting large-scale scientific software design and development. She has more than 16 years of experience in the design, architecture, development, testing, and maintenance of software applications. Her research interests are interconnected science and federated systems, scientific software design, operational workflows, frameworks, and ecosystems for science, software analytics, empirical software engineering, mining software repositories, and metrics and standards for scientific and research software. Addi leads the Scientific Software Development for Neutron Science Team for the Neutron Scattering Division, which is responsible for designing, developing, and deploying data reduction and data analysis software for the neutron science community at ORNL's High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS). Her work enables scientists to efficiently process and analyze complex neutron scattering data, accelerating scientific discoveries and advancing innovation in neutron science.
Her research and technical interests include:
- Interconnected science and federated systems.
- Scientific software design, workflows, frameworks, and ecosystems for science.
- Software analytics, Empirical software engineering, Mining software repositories, Research software engineering.
- Metrics and standards for scientific and research software.
- Software engineering, data architecture, design patterns, and test-driven processes for the development and maintenance of scientific software applications.
- Software quality assurance, integration, validation, and verification for scientific computing applications.
- Automated and scalable machine learning and artificial intelligence services for data-intensive applications.