Rifat Mehreen Amin

E-Mail	rifat.amin@ifi.lmu.de
Phone	+49-89 / 2180-75148
Address	Rifat Mehreen Amin LMU Munich Media Informatics Group Frauenlobstr. 7a 80337 Munich, Germany
Room	439 (4th floor)

Research Interests

My research interest lies in the design of human-AI interaction, particularly interfaces for generative systems. I investigate how explicit, non-linear representations of interaction, such as branching, composition, and visualization can improve users' ability to explore, understand, and control generative workflows.

Teaching

Summer Term 2026: Practical Course: Information Visualization, Hauptseminar Media Informatics
Winter Term 2025/26: Practical Course: Information Visualization, Information Visualization, Hauptseminar Media Informatics
Summer Term 2025: Practical Course: Human Computation and Analytics, Hauptseminar Media Informatics
Winter Term 2024/25: Human Computation and Analytics, Information Visualization, Hauptseminar Media Informatics
Summer Term 2024: Practical Course: Human Computation and Analytics, Hauptseminar Media Informatics
Winter Term 2023/24: Human Computation and Analytics, Information Visualization, Hauptseminar Media Informatics
Summer Term 2023: Practical Course: Human Computation and Analytics, Proseminar Media Informatics
Winter Term 2022/23: Human Computation and Analytics, Information Visualization
Summer Term 2022: Practical Course: Human Computation and Analytics

Publications

2026
Download	Jasmina Gajcin, Jovan Jeromela, Joel Wester, Sarah Schoembs, Styliani Kleanthous, Karthikeyan Natesan, Hanna Hauptmann, Rifat Amin CURE2026: Communicating Uncertainty to foster Realistic Expectations via Human-Centered Design Companion Proceedings of the 2026 ACM Conference on Intelligent User Interface (IUI '26). ACM. New York, NY, USA. 2026. (bib)
Download	Rifat Amin, Seyit Baran Oezdemir, Sven Mayer, Andreas Butz EmoArc: Interactive Emotion Graph for Human-AI Collaborative Writing In Proceedings of the 18th International Conference on Advanced Visual Interfaces (AVI '26). ACM. New York, NY, USA. 2026. (bib)
Download	Rifat Amin, Oliver Hans KÃ¼hle, Daniel Buschek, Andreas Butz Structuring Prompt Construction as a Tool for Thought CHI'26 Workshop on Tools for Thought. ACM. New York, NY, USA. 2026. (bib)
Download	Rifat Amin, Oliver Hans KÃ¼hle, Daniel Buschek, Andreas Butz PromptCanvas: Composable Prompting Workspaces Using Dynamic Widgets for Exploration and Iteration in Creative Writing ACM Trans. Interact. Intell. Syst. (TiiS). ACM. New York, NY, USA. 2026. (bib)
2025
Download	Vishwa Mohan Singh, Sai Anirudh Aryasomayajula, Ahan Chatterjee, Beste Aydemir, Rifat Amin Improving AI-generated music with user-guided training The 4th International Conference Series on Hybrid Human-Artificial Intelligence (HHAI'25). ACM. New York, NY, USA. 2025. (bib)
Download	Rifat Amin, Oliver Hans KÃ¼hle, Daniel Buschek, Andreas Butz Composable Prompting Workspaces for Creative Writing: Exploration and Iteration Using Dynamic Widgets Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '25). ACM. New York, NY, USA. 2025. (bib)
Download	Daniel Hartmuth, Rifat Amin, Daniel Schlichting, Svenja Schött, Jonathan Haudenschild, Helmut KÃ¼chenhoff, Birgit J. Neuhaus Developing science teachers' enacted pedagogical content knowledge through integration of student feedback into the Refined Consensus Model of pedagogical content knowledge Cogent Education, Taylor and Francis, 2025 (bib)
2024
Download	Rifat Amin, Feng Chen, Linda Hirsch, Changkun Ou, Tran-Vu La, Andreas Butz Integrating Crowd and Machine Learning in an Intelligent Interface: A Case Study of Oil Spill Detection in Satellite Images In Proceedings of the 17th International Conference on Advanced Visual Interfaces (AVI '24). ACM. New York, NY, USA. 2024. https://doi.org/10.1145/3656650.3656680 (bib)
Download	Rifat Amin, Pia Hammer, Andreas Butz Using Machine Learning to Improve Interactive Visualizations for Large Collected Traffic Detector Data In Proceedings of the 29th International Conference on Intelligent User Interfaces (IUI '24). ACM. New York, NY, USA. 2024. https://doi.org/10.1145/3640543.3645177 (bib)
2023
Download	Rifat Amin Multi-Objective Counterfactuals for Counterfactual Fairness in User Centered AI UCAI'23: Workshop on User-Centered Artificial Intelligence @ Mensch und Computer 2023 (MuC'23), September 3-6, Rapperswil, Switzerland (bib)
Download	Svenja Schött, Rifat Amin, Andreas Butz A Literature Survey of How to Convey Transparency in Co-Located Human-Robot Interaction In Multimodal Technol. Interact. 2023, 7(3), 25 (bib)

Theses (Bachelor/Master)

Open

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In Progress

Aylin Aldemir	master thesis	AI-assisted Context-Aware Document Reader
Anton Rockenstein	master thesis	Dynamic Interfaces for AI-Guided Image Editing

Accomplished

Felicia Saruba	bachelor thesis	Thermal Feedback for Emotional Communication in Human-Robot Interaction
Pia Isabel Hammer	master thesis	Leveraging Machine Learning with Interactive Visualizations for Large Collected Traffic Detector Data
Jonathan Haudenschild	master thesis	A Visualization Tool for Improving Teaching Performance in Dynamic Educational Environments
Feng Chen	master thesis	Oil Spill Detective: Leveraging Machine Learning with Crowd Knowledge to Reduce Experts' Workload
Sandra Busch	bachelor thesis	Designing for Visualising Multiple Counterfactuals for XAI
Anh Dao Phuong	master thesis	LLM for Counterfactual Explanation Generation
	bachelor thesis	Write, Edit, Ripple: Interactive Inline Widgets for Fluid Story Development
Alexander Nuss	MA/BA	Tracing Edits: Interactive Exploration of Conversational Image Editing Histories
Seyit Baran Ozdemir	bachelor thesis	Interactive Emotion Graph for Human-AI Collaborative Text Manipulation
Jinghuai Xiong	bachelor thesis	Image Snapshots for Creative Writing with Dynamic Widgets
Oliver Hans KÃ¼hle	bachelor thesis	Dynamic UI Element Generation for Rapid Prompting
Rudraksha Samdhani	bachelor thesis	Exploring Generative Models' Latent Spaces: Investigating the Influence of UIs on Human-AI Collaboration
Hannah Kindermann	bachelor thesis	A Comparison of Statistical and Counterfactual Fairness Metrics for Explainable AI