Welcome to Systems Psychology Lab!
Welcome to the Systems Psychology Lab! Teams are becoming more and more ubiquitous in every day life, and the need to study how to make teams effective is incredibly important. In our research, we seek to apply Dynamical Systems Theory to human behavior in the context of teams and human systems. Teams are not merely the sum of individuals- team members interact with each other to accomplish more than they could alone. We seek to understand how teams interact to become more than the sum of their parts through methods such as communication analysis, movement data analysis, physiological monitoring, and neural approaches.
Announcements
- 🤝 January 2026: Shiwen Zhou and collaborators published “The Spread of Trust and Distrust in Human-AI Teams” in Applied Ergonomics (Vol. 130, Article 104648, Elsevier).
- 🧬 October 2025: Garima Arya Yadav and collaborators published “Bio-behavioral Team Dynamics Measurement System: Multimodal Sensing, Dynamical Systems Modeling, and Machine Learning Pipelines to Predict and Characterize Team Performance” in Nonlinear Dynamics, Psychology, and Life Sciences (Vol. 29, Issue 4, pp. 529–552).
- 📘 October 2025: Xiaoyun Yin co-authored two new papers:
- When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About? — arXiv preprint arXiv:2510.02660
- Birds of a Different Feather Flock Together: Exploring Opportunities and Challenges in Animal-Human-Machine Teaming — arXiv preprint arXiv:2504.13973
- 🧠 September–October 2025: Our lab had a strong presence at the HFES Annual Meeting and ASPIRE 2025 conferences!
- Dr. Elmira Zahmat Doost presented:
- Limited-Teamwork Autonomy in Training: Transfer Effects on Performance and Coordination in Subsequent All-Human Teams.
- BioTDMS: A Multi-Sensor and Data-Driven System for Real-Time Team Performance Assessment.
- Xiaoyun Yin presented:
- Augmented Cognition Meets AI: Enhancing Human Performance with Real-Time, Adaptive, and Trustworthy Intelligence.
- Trust Contagion in Team of Teams (ToT) for Human-Autonomy Teaming.
- Parkhi Malhotra presented “Evaluating Usability of a VR Team Training Environment.”
- Matt Scalia presented “A Dynamic Trust and Distrust Influence Metric that Predicts Team Trustworthiness and Affective Trust in Human Teams and Human-AI Teams.”
- Ray Hao presented “Error Type Influences Communication Recipient Selection: Consistent Patterns During Autonomy and Automation Errors in a Synthetic Task Environment.”
- Shiwen Zhou presented:
- Sensitivity of Self-Report Measures of Trust in Human-Autonomy Teaming
- Different Methods of Team Adaptation in Response to Uncertainty
- The Impact of Communication Timing and Sequencing on Team Performance: A Comparative Study of Human-AI and All-Human Teams
- Development of a Real-Time Trust/Distrust Metric Using Interactive Hybrid Cognitive Task Analysis
- Dr. Elmira Zahmat Doost presented:
- 🎓 August 2025: Congratulations, Parkhi! She has obtained her Master’s Degree in Human Systems Engineering and has now begun her Ph.D. in the same program.
- ✍️ July 2025: Lucrezia presented a poster “Predicting Collaborative Problem-Solving Performance: Empathy, Synchrony, and Emotion in Student-AI Teams.”
- 🎉 May 2025: Congratulations, Dr. Grimm! Dr. David Grimm has officially graduated from Georgia Tech! What an incredible achievement! Wishing you continued success in all your future endeavors. 👏🎓
- 🔊 April 2025: Dr. Elmira Zahmat Doost presented a poster, A Distributed Teaming Testbed for Human-Machine Collaboration in Futuristic Space Missions, showcasing the lab’s research at AAAI 2025 (Association for the Advancement of Artificial Intelligence).
- 📣 March 2025: Dr. Jamie Gorman was invited as a guest on the podcast The Rise of Humanness, where they discussed Human-AI teaming. Check it out!
- 🎉 March 2025: We welcomed our research assistants for our iSAT Strand 2 projects: Gauri, Poorva, and Salsabil. Thank you and welcome!
- 📰 November 2024: Ray Hao, Lucrezia Lucchi, and Jamie Gorman authored a blog post “What is Human-AI Teaming in Three Levels of Complexity in Learning Environments?” on the CU Boulder AI Institute website

