Theta EdgeCloud selected for AI research by Stanford Assistant Professor Ellen Vitercik’s AI Lab

We’re thrilled to announce that the AI research lab of Stanford Engineering Assistant Professor Ellen Vitercik will use Theta EdgeCloud’s hybrid cloud infrastructure to support its AI research in discrete optimization and algorithmic reasoning. EdgeCloud’s decentralized GPU provides access to scalable, high-performance computing power at a reasonable cost to accelerate AI model training and research.

Other US and global academic institutions utilizing EdgeCloud’s hybrid GPU infrastructure to enhance AI research productivity include Seoul National University, KAIST, Korea University, Yonsei University, the University of Oregon, Michigan State University, Singapore’s NTU and many more.

About Ellen Vitercik and her Research Lab

Ellen Vitercik, an assistant professor of Management Science & Engineering and Computer Science at the Stanford School of Engineering, conducts research focused on machine learning, algorithmic reasoning, and the intersection of computation and economics.

Supporting AI Research with Theta EdgeCloud

Theta EdgeCloud provides access to scalable and cost-effective on-demand GPU computing power to support various AI research efforts, including:

LLMs for Optimization — Researching how large language models can improve cutting plane separator configuration and equivalence checking of optimization formulations.

Algorithmic Content Selection — Investigating the impact of AI-driven content selection on user engagement and decision-making.

Clustering and Dataset Size Generalization — Exploring machine learning approaches to improve clustering algorithm selection across different dataset sizes.

AI-Driven Economic Decision-Making — Studying the role of AI in pricing, targeted marketing, auctions, and profit-maximization models.