Announcing New Thematic Labs
Security, Privacy, and Resilience for Trusted AI (SPARTA) Lab
Generative AI for Science and Engineering (GAISE) Lab
The Texas A&M Institute of Data Science (TAMIDS) is excited to announce that two new cutting-edge labs are joining its Thematic Lab Program: the Security, Privacy, and Resilience for Trusted AI (SPARTA) Lab and the Generative AI for Science and Engineering (GAISE) Lab. For its 2025 Request for Proposals, TAMIDS received 15 exceptional Thematic Lab proposals, including 85 researchers from 15 divisions, colleges, schools, and agencies. The selection process was highly competitive, with each outstanding submission reviewed by three experts. The selected labs will position Texas A&M University at the forefront of AI-driven innovation, addressing critical national and state priorities in energy security, advanced manufacturing, and cybersecurity.
The SPARTA Lab: Securing and Strengthening AI for Critical Infrastructure
Co-sponsored by the Texas A&M Global Cyber Research Institute (GCRI), SPARTA will focus on developing capabilities for advanced data-driven cybersecurity and resilience enhancements across disciplines, with a particular emphasis on critical infrastructures, trustworthy human-AI interactions, and cyberinfrastructure for scientific research.
SPARTA Lab Team:
- Eman Hammad (Lab Director), Engineering Technology and Industrial Distribution, College of Engineering
- Sandip Roy, Electrical and Computer Engineering, College of Engineering, Director, Texas A&M Global Cyber Research Institute (GCRI)
- Katherine Davis, Electrical and Computer Engineering, College of Engineering, Assistant Director for Education, Texas A&M Smart Grid Center
- Dwayne Whitten, Information and Operations Management, Mays Business School
- Marcus Botacin, Computer Science & Engineering, College of Engineering
- Laszlo Kish, Electrical & Computer Engineering, College of Engineering
Key research thrusts include a system-of-systems approach to cybersecurity and research, focused on strengthening existing systems and building secure, resilient innovation. SPARTA’s objectives include hardening machine learning models in operational and SCADA environments, conducting risk assessments and security testing, and ensuring AI model resilience during disruptions. The lab also aims to develop AI-driven disaster awareness and incident response, secure data pipelines, analyze risk propagation in AI pipelines, and advance AI for threat detection, adversarial defense, and anti-digital forensics.
The GAISE Lab: Accelerating AI-Discovery in Nuclear Energy and Materials Science
The GAISE Lab unites nuclear engineering, materials science, and computer science to fuel scientific discovery and engineering innovation. Its interdisciplinary research will integrate complex graph data, large-scale simulations, digital twins, and expert knowledge into AI-driven analytical frameworks. GAISE’s work supports rapid materials discovery, intelligent system control, and workforce development to bolster energy security and drive next-generation innovation.
GAISE Lab Team:
- Yang Liu (Lab Director), Nuclear Engineering, College of Engineering
- Shuiwang Ji, Computer Science and Engineering, College of Engineering
- Raymundo Arróyave, Materials Science and Engineering, College of Engineering
- Xiaofeng Qian, Materials Science and Engineering, College of Engineering
Key research thrusts include developing adaptive invariant-equivariant architectures for large-scale graph neural networks, efficient multimodal data fusion, and intelligent agentic workflow techniques leveraging large language models. Expected outcomes include validated generative AI models that enable real-time predictive analytics, intelligent system control, and explainable decision-making tools.
About the Thematic Labs Program
TAMIDS funds research labs for two years, providing seed funding, administrative and research support, and engagement opportunities across the broader data science community. The mission of each Lab is to develop knowledge, resources, and community around its focus area of Artificial Intelligence (AI), incorporating elements of Machine Learning and Data Science.
TAMIDS program leaders will work with the new lab directors to promote their engagement with TAMIDS activities and programs, support their growth, and help develop synergies with the existing Thematic Labs.