As companies commit billions of dollars to artificial intelligence, questions about the technology’s technical demands, practical applications and effects on workers and society are taking on greater urgency.
Rice University experts are available to discuss the infrastructure needed to support AI, its applications in science and industry and its implications for workers, privacy and public trust.
The new hybrid workforce
Human resources will begin evolving into “human and machine resources,” integrating AI workers alongside humans in hybrid teams.
Margaret E. Beier is the Autrey Professor and chair of the Department of Psychological Sciences. She studies the predictors of success in organizational settings and continuous development in the modern workplace. She can also speak to how technology and AI are changing the nature of work with a particular emphasis on reskilling and upskilling.
Scaling AI infrastructure
Chris Jermaine is the chair and Victor E. Cameron Professor of Computer Science in the George R. Brown School of Engineering and Computing. His work focuses on building scalable infrastructure for AI models, data privacy for large-scale AI and agentic AI with a particular emphasis on developing AI agents for autonomous science.
Expert AI and large model consolidation
Industry-specific, highly specialized AI models can leverage proprietary company data to excel in fields such as medicine, finance and robotics. As with cloud infrastructure or Formula One engines, the complexity of maintaining frontier AI models will likely lead to a handful of dominant providers.
Anshumali Shrivastava is a professor of computer science, electrical and computer engineering and statistics. Shrivastava specializes in large-scale machine learning and scalable, sustainable deep learning. He leads a Rice generative AI research cluster examining how large language models can manage larger knowledge bases while addressing computational costs, hallucinations and explainability.
Todd Treangen, an associate professor of computer science, develops AI methods for pathogen identification, biosurveillance and microbiome analysis with applications in biosecurity, health care and biotechnology.
AI-powered robotic breakthroughs
By learning through physical-world experiences, AI will gain reasoning abilities, bridging the gap between digital models and real-world applications.
Sanjoy Paul, executive director of Rice Nexus and director of the Artificial Intelligence Houston Institute, investigates AI’s role in space exploration, including decision-making, robotic operations and data analysis for lunar, Martian and Earth studies. His work also encompasses cybersecurity for in-space computing.
Localized AI regulation
Companies will prioritize self-regulation with responsible AI principles, complementing broader national or sectoral frameworks.
Rodrigo Ferreira, assistant teaching professor of computer science, specializes in the ethical dimensions of AI, focusing on integrating ethics into computer science education and examining the cultural and policy implications of AI technologies.
Generative AI models and synthetic data
Richard Baraniuk, the C. Sidney Burrus Professor of Electrical and Computer Engineering, is a leading expert in multiscale computational signal and image processing, data science and neuroengineering systems. He investigates the challenges and risks of training deep learning models on synthetic data, including issues such as model collapse and amplified biases.
His research includes developing novel training paradigms for generative models, large language models and other machine learning systems to improve robustness and alignment with real-world data, ensuring models are less impacted by synthetic data artifacts.
AI in computational biology
Beyond chatbot hype, this is where AI creates real-world impact — turning complex genetic data into medical breakthroughs and life-saving treatments.
Luay Nakhleh is the dean of Rice’s George R. Brown School of Engineering and Computing. His work utilizes advanced computing and statistical modeling to analyze complex biological and genetic data. His work shows how AI and machine learning solve intricate, real-world scientific problems across disciplines.
AI and misinformation
Addressing the human side of AI — specifically showing how algorithm-driven misinformation reshapes public belief and how corrections actually work in practice — is just as important.
Alyssa “Allie” Sinclair
Sinclair, assistant professor of psychological sciences, studies how people update their beliefs and how misinformation online can be corrected or counteracted. She can discuss why misleading claims may persist and how people respond to corrections. She can also discuss the local impact of recent federal science funding cuts.
Ethics of emerging technology
Robert Howell is department chair and the Yasser El-Sayed Professor of Philosophy. The majority of his work has been on issues surrounding consciousness, subjectivity and the metaphysics of mind. He can speak to the importance of philosophy with regard to technological projects — from social media to AI — and to the impact of AI use on the augmentation of intellectual and moral virtues.
To schedule an interview with Rice’s experts, contact media relations specialists Jamie Groh at jamie.groh@rice.edu or Kat Cosley Trigg at kat.cosley.trigg@rice.edu.