Hong Shen

Hong Shen is an Assistant Professor in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University's School of Computer Science, where he directs the CARE (Collective AI Research and Evaluation) Lab and participates in the CMU-NIST Cooperative Research Center on AI Measurement Science & Engineering (AIMSEC).

Education:

• PhD from University of Illinois at Urbana-Champaign

Research Interests: Dr. Shen is an interdisciplinary scholar at the intersection of human-computer interaction, artificial intelligence, and public policy. His work examines the social, ethical, and policy implications of digital platforms and algorithmic systems, with core focus areas in Social Computing, Human-Centered AI, Responsible Computing, Ethics and Policy, Research through Design, and Tools and Programming. His research emphasizes community-centered approaches to AI development and governance.

Publication Trends: His 2025 publications reveal strong interdisciplinary convergence across AI ethics, participatory governance, and real-world AI deployment. Key themes include public involvement in algorithmic decision-making, reparative justice frameworks for AI harms, risk management in AI content work, and cross-cultural studies of algorithmic labor. The work consistently bridges technical AI development with social science methodologies and policy implications, particularly in community-university partnerships and healthcare contexts.

Scientific Awards:

• Best Paper Award at HCOMP'24 (2024) for "Investigating What Factors Influence Users’ Rating of Harmful Algorithmic Bias and Discrimination"
• Google Research Scholar Award in Human-Computer Interaction (2024)
• Microsoft Research AI & Society Fellow (2024) for "Supporting the Responsible AI Red-Teaming Human Infrastructure"
• Best Paper Award at CHI'23 (2023) for "Understanding Frontline Workers’ and Unhoused Populations’ Perspectives on AI Used in Homeless Services"

Advising and Funding: Dr. Shen advises graduate students Jini Kim, Ningjing Tang, Alice Qian Zhang, and Qing Xiao. His research is supported by significant grants including multiple National Science Foundation awards (including July 2025 funding for participatory AI design with behavioral health services), Amazon Research, Cisco Research, Google Research, Microsoft Research, The Public Interest Technology University Network, Block Center for Technology and Society, and CyLab. Recent grants focus on community-centered AI toolkits and mental health organization partnerships.

Labs and Teams: He leads the CARE Lab, which develops collective approaches to AI research and evaluation, and actively contributes to AIMSEC's mission of advancing human-centered AI measurement science through CMU-NIST collaboration. His lab emphasizes participatory methods and infrastructure for ethical AI development.