Centers and Labs
Human-centered research collaborations start with us. The following interdisciplinary centers and research labs are affiliated with our HCII faculty.
The Knowledge Accelerator is a new center at Carnegie Mellon University that is building tools to help people gather, stitch together, and make decisions on information spread across the internet in 10-100x less time than it takes today. Not only will these tools help people make better and more personalized decisions, but by capturing the work they do they can accelerate future users with similar interests instead of them having to start from scratch, creating a virtuous cycle of knowledge acceleration.
Contact: Niki Kittur
4A (AI Accountability, Awareness, and Action) Lab
4A Lab aims to empower users of AI systems, particularly those who belong to marginalized communities or those users whose decisions impact marginalized communities, to make transparent, fair, and informed decisions in interaction with algorithmic systems.
Contact: Motahhare Eslami
Augmented Design Capability Studio
We use new technology, product design methods, interaction design, human-robot interaction, and mechatronic engineering to build tools and methods that allow designers to understand people better and to create more human-centered products.
Contact: Nik Martelaro
Augmented Perception Lab
We aim to understand how users perceive and interact with digital information beyond the flat displays of PCs and smartphones. Our goal is to create and study enabling technologies and computational approaches that make Augmented Reality and Virtual Reality interfaces beneficial for users.
Details: Augmented Perception Lab
Contact: David Lindlbauer
We develop technology solutions to support, enhance, understand, and celebrate Ability in its many forms. The research we conduct aims to improve the quality of human lives through the thoughtful application of technology and social interventions.
Details: AXLE Lab
Contact: Patrick Carrington
We work to advance Human-AI Collaboration, mostly in (i) accessibility (esp. access technologies), (ii) crowdsourcing and human computation (esp. systems that combine AI and human intelligence together, and work to improve the worker experience), and (iii) dialog systems (esp. those that deeply integrate human computation and dialog together). This is the research lab of Jeffrey Bigham.
Details: Big Lab
Contact: Jeffrey Bigham
Through partnerships with practitioners and community stakeholders, we create new technologies to complement and bring out the best of human ability in fundamentally human endeavors such as social, creative, or care-based work. We study how humans and AI systems can augment each other’s abilities (co-augmentation) and learn from each other (co-learning) to support more effective and responsible human-AI collaborations. We develop new methods that broaden who is able to participate in shaping the design and use of emerging technologies.
Details: CoALA Lab
Contact: Ken Holstein
CMU Data Interaction Group (DIG)
Our group conducts research at the intersection of human-computer interaction, machine learning, data science, programming languages, and data management, with the mission of empowering everyone to analyze and communicate data with interactive systems.
Details: CMU DIG
d.form and d.stable Labs
We explore how people experience emerging and future technology, particularly human-AI interaction and human robot interaction. d.form has fabrication tools for building room sized prototypes including 3D printers, laser cutter, CNC machine, as well as crafting materials and tools. d.stable is where we simulate different environments such as a home, retail store, hospital, or hotel in order to evaluate possible futures.
Future Interfaces Group
We create new sensing and interface technologies that foster powerful and delightful interactions between humans and computers. These efforts often lie in emerging use modalities, such as smart environments, wearable computing, augmented reality, and gestural interfaces.
Details: Future Interfaces Group (FIG Lab)
Contact: Chris Harrison
Human-Centered Data Lab
The Human-Centered Data Lab's research focuses on using big data collected from educational systems to improve student learning and spans several areas: data mining, artificial intelligence, machine learning, intelligent tutoring systems, cognitive modeling, CS education, game development, and instructional design.
Details: Human-Centered Data Lab
Contact: John Stamper
Interactive Structures Lab
We investigate and develop interactive computational design tools that enable digital fabrication of complex structures for novice users. Interactive structures embed functionality within their geometry such that they can react to simple input with complex behavior.
Details: Interactive Structures Lab
Contact: Alexandra Ion
LearnLab brings learning science and technology to bear on real-world challenges in learning, spanning K12 and college topics in math, science, and language learning. We provide innovative techniques and technologies to support iterative engineering of highly effective, efficient, and enjoyable learning experiences.
Contact: Ken Koedinger
The McLearn Lab does research in the areas of Learning Science and educational technology. The lab has developed and conducted experiments with digital learning games, intelligent tutors, and collaborative learning systems. We are interested in supporting education in many novel and impactful ways.
Contact: Bruce McLaren
Smart Sensing for Humans (SmaSH) Lab
The SmaSH Lab develops innovative sensing systems to develop solutions with immediate impact in the fields of health, accessibility, novel interactions, activity recognition, and technologies for the developing world. We are an interdisciplinary team of researchers from ISR and HCII.
Details: Smart Sensing for Humans Lab
Contact: Mayank Goel
My lab focuses on improving our understanding of, and the quality of, collective actions arising from interactions between people and machines within social networks. We aim to yield important scientific insights on human-computer interactions and develop new research tools for social good.
Contact: Hirokazu Shirado
Social AI Group
Social AI Group is an interdisciplinary research group within Carnegie Mellon University. In our research, we aim to study and design socially sensitive AI. We combine in-depth empirical research with design methods in order to create, deploy and evaluate innovative AI tools that better support humans to complete complicated tasks, that promote positive human interactions, and that improve group and community wellbeing.
Contact: Haiyi Zhu
Tech Solidarity Lab
We seek to open new opportunities for community-driven technology development and extend theoretical frameworks that further our understanding of design, politics and justice.
Contact: Sarah Fox
Technology Research for Augmenting Creativity in Educational Spaces (TRACES Lab)
We focus on co-design partnerships with educators in creative learning and project based learning contexts. We collaboratively design learning technologies by bringing together an interdisciplinary team across HCI, design, architecture, educational research and computing.
Details: TRACES Lab
Contact: Marti Louw