Walter S. Lasecki

Walter S. Lasecki is an Associate Professor at the University of Michigan's School of Information, where he leads research at the intersection of Human-Computer Interaction, Crowdsourcing, and Artificial Intelligence. His work focuses on creating systems that integrate human and machine intelligence to solve complex problems in real-time.

Dr. Lasecki's research interests center on human-AI collaboration, particularly in developing crowd-powered systems that enhance accessibility, improve programming education, and create more effective human-computer interfaces. His work explores how to effectively integrate human intelligence with AI systems, focusing on real-time applications where speed and accuracy are critical. His research has significant implications for accessibility technologies, educational tools, and conversational AI systems. He has pioneered approaches to real-time captioning, crowd-powered interfaces, and human-in-the-loop machine learning systems that adapt to user needs.

Analysis of his recent publications reveals a strong focus on multi-agent conversational AI, human-in-the-loop systems for pose estimation and object recognition, and innovative approaches to programming education through live streaming. His research consistently explores the intersection of human computation and artificial intelligence, with particular attention to how crowd workers can complement and enhance AI capabilities. His work demonstrates a trajectory from foundational crowd-powered systems to more sophisticated integrations of human and machine intelligence in complex tasks.

Dr. Lasecki has collaborated extensively with researchers across multiple institutions, particularly with Jeffrey P. Bigham (earlier in his career) and more recently with colleagues at the University of Michigan including Juho Kim. His research has been supported by substantial grants that have enabled the development of systems like Scribe for real-time captioning and Codeon for on-demand programming assistance. He has mentored numerous graduate students who have gone on to contribute to the fields of HCI and AI.

His laboratory focuses on developing practical applications of crowd-AI hybrid systems, with particular emphasis on creating tools that can be deployed in real-world settings. Current projects explore how to make conversational AI more robust through multi-agent approaches, improve programming education at scale, and create more accessible interfaces for diverse user populations.