Columbia's Kostis Kaffes Wins Google Junior Faculty Award Again for Agentic AI Work

What the award covers

According to Columbia Computer Science, the Google Machine Learning and Systems Junior Faculty Award supports early-career faculty who are advancing machine learning and computing systems. Recipients receive $100,000 in unrestricted funding to support their research.

Kaffes has now won the award in two consecutive years. The latest recognition is tied to his work on infrastructure for agentic AI, a topic centered on systems in which AI agents carry out tasks on their own.

Research on infrastructure for AI agents

Kaffes develops the computing infrastructure that AI agents need in order to operate safely, reliably, and efficiently. Columbia describes his research as bringing together computer systems, artificial intelligence, and cloud computing.

The aim is to support agents that can carry out complex tasks. The focus is on the underlying systems layer rather than on the agents themselves, which means the work addresses how such agents run and how they can be kept dependable.

Role in Columbia's DAPLab

Kaffes is also a founding member of Columbia's Data, Agents, and Processes Lab, known as DAPLab. According to the university, the lab is building the foundations for AI agents to safely and reliably automate complex work.

The goals of the lab line up with the themes of the award-winning research: safety, reliability and efficiency in agent-based systems.

What it means

The unrestricted nature of the $100,000 funding gives Kaffes flexibility in how he directs his research. The repeat award signals continued industry recognition for work on the infrastructure behind agentic AI, an area where, as the source describes it, safety and reliability are central concerns. The source does not detail specific projects or results funded by the award.