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Interactive
Visualization &
Intelligence
Augmentation Lab

Bridging Human and Artificial Intelligence

Illustrative Visual

Our IVIA research lab is part of the Visual Computing Institute at the Department of Computer Science of ETH Zurich. As a group, we are also affiliated with the SWISS AI Initiative, Swiss ACM SIGCHI (SwissCHI), ETH for Development | ETH4D, UN-ETH Partnership, and Human-Computer Interaction at ETH Zurich.

The lab is led by Prof. Mennatallah El-Assady, who works at the intersection of data analysis, visualization, computational linguistics, and explainable artificial intelligence. Besides, Menna is a core faculty member of the ETH AI Center, Design++, and a member of the AI Ethics and Policy Network. She also is an associated faculty member at the Max Planck ETH Center for Learning Systems and an ELLIS Scholar of the ETH Zurich Unit at the European Lab for Learning & Intelligent Systems.

Our main research interest is studying interactive human-AI collaboration interfaces for effective problem-solving and decision-making. In particular, we are interested in empowering humans by teaming them up with AI agents in co-adaptive processes.

Read more about our work on our social media channels:

Our IVIA Team

Portrait of Mennatallah El-Assady

Mennatallah El-Assady

Assistant Professor

Portrait of Rita Sevastjanova

Rita Sevastjanova

PostDoc & Research Associate

Portrait of Matthias Miller

Matthias Miller

PostDoc & IT Coordinator

Portrait of Thilo Spinner

Thilo Spinner

PostDoc & Engineer

Portrait of Pei-Yu Wu

Pei-Yu Wu

PostDoc

Portrait of Furui Cheng

Furui Cheng

PostDoc Researcher

Portrait of Kenza Amara

Kenza Amara

PhD Student

Portrait of Steffen Holter

Steffen Holter

PhD Student

Portrait of Robin Chan

Robin Chan

PhD Student

Portrait of Raphaël Baur

Raphaël Baur

PhD Student

Portrait of Tobias Stähle

Tobias Stähle

PhD Student

Portrait of Markus Portmann

Markus Portmann

Administrator


Teaching / Courses

Web Development Course Icon

Fundamentals of Web Engineering

Learn modern web development from fundamentals to full-stack applications. Master TypeScript, frameworks, and UI/UX design while building real-world projects. Gain hands-on experience with both frontend and backend development in a group setting.

Machine Learning Course Icon

Interactive Machine Learning

Visualization & Explainability

Explore the intersection of human and machine intelligence through interactive ML systems. Learn to design and implement visual interfaces for ML model understanding, diagnosis, and refinement.

AI4GOOD Course Icon

Human-Centered AI for Social Good

Peace, Health, Climate

AI4GOOD — Apply AI to address global challenges in peace, health, and climate. Develop practical solutions using public data while examining ethical implications. Design and implement AI systems for social impact.

Interactive Visualization & Intelligence Augmentation

Our lab conducts research on topics related to human-AI interaction.

We design interactive visualizations and intelligence augmentation approaches combining data mining and machine learning techniques for different application domains, including visual inspection of LLMs, health applications, etc. The lab aims to understand how humans and AI can benefit from each other in solving complex analysis tasks.

Scroll over the figure to find out more!

Featured Publications

Challenges and Opportunities in Text Generation Explainability
Challenges and Opportunities in Text Generation Explainability

K. Amara, R. Sevastjanova, M. El-Assady, 2024.

World Conf. on eXplainable Artificial Intelligence

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RELIC: Investigating Large Language Model Responses using Self-Consistency
RELIC: Investigating LLM Responses using Self-Consistency

F. Cheng, V. Zouhar, ..., M. El-Assady, 2024.

Proc. CHI Conf. on Human Factors in Computing Systems

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🌳-generAItor: Tree-in-the-Loop Text Generation for Language Model Explainability and Adaptation
generAItor: Tree-in-the-Loop Text Generation for LLM Explainability

T. Spinner, R. Kehlbeck, ..., M. El-Assady, 2024.

ACM Transactions on Interactive Intelligent Systems

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Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections
Refining Topics with Semantic Concept Spaces

M. El-Assady, R. Kehlbeck, ..., O. Deussen, 2020.

IEEE Trans. on Visualization and Computer Graphics

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explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning
explAIner: VA for Interactive and Explainable ML

T. Spinner, U. Schlegel, ..., M. El-Assady, 2020.

IEEE Trans. on Visualization and Computer Graphics

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Visual Analytics for Topic Model Optimization based on User-Steerable Speculative Execution
Visual Analytics for Topic Model Optimization

M. El-Assady, F. Sperrle, ..., C. Collins, 2018.

IEEE Trans. on Visualization and Computer Graphics

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ThreadReconstructor: Modeling Reply-Chains to Untangle Conversational Text through Visual Analytics
ThreadReconstructor: Untangling Conversational Text through VA

M. El-Assady, R. Sevastjanova, ..., C. Collins, 2018.

Computer Graphics Forum

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Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework
Visual Analytics Topic Modeling Framework

M. El-Assady, R. Sevastjanova, ..., C. Collins, 2018.

IEEE Trans. on Visualization and Computer Graphics

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Most Recent Publications

Finding Needles in Document Haystacks: Augmenting Serendipitous Claim Retrieval Workflows
Finding Needles in Document Haystacks

M. Dück, S. Holter, ..., M. El-Assady, 2025.

Conf. on Human Factors in Computing Systems

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A Design Space for Intelligent Dialogue Augmentation
Design Space for Dialogue Augmentation

R. S. M. Chan, A. Kim, ..., M. El-Assady, 2025.

ACM Conf. on Intelligent User Interfaces (IUI)

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Reward Learning from Multiple Feedback Types
Reward Learning from Multi-Type Feedback

Y. Metz, A. Geiszl, ..., M. El-Assady, 2025.

International Conference on Learning Representations

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Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
LATEC: Evaluating XAI Methods and Metrics

L. Klein, C. T. Lüth, ..., P. F. Jäger, 2024.

Int. Conf. on Learning Representations

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Adapting LLMs for Structured Natural Language API Integration
Adapting LLMs for API Integration

R. Chan, K. Mirylenka, ..., A. Labbi, 2024.

Conf. on Empirical Methods in Natural Language Processing, Industry Track

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Towards Personal Explanations for Recommender Systems: A Study on the Impact of Familiarity and Urgency
Towards Personal Explanations for Recommender Systems: A Study on the Impact of Familiarity and Urgency

I. Al-Hazwani, N. Ahmed, ..., J. Bernard, 2024.

Proc. Nordic Conf. Human-Computer Interaction

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Feature Clock: High-Dimensional Effects in Two-Dimensional Plots
Feature Clock

O. Ovcharenko, R. Sevastjanova, V. Boeva, 2024.

Proc. of IEEE VIS Visualization and Visual Analytics

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On Affine Homotopy between Language Encoders
On Affine Homotopy between Language Encoders

R. Chan, R. Boumasmoud, ..., R. Cotterell, 2024.

Advances in Neural Information Processing Systems

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Our Partnerships

We are proud to collaborate with leading organizations across various industries. These partnerships enable us to push the boundaries of research and innovation, bringing together expertise from different domains to create impactful solutions.

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