Madhav Sachdeva
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Research and Project Focus
Madhav’s research focuses on improving decision-making in the wild for analysis of high-dimensional data by designing novel methods that integrate human and model expertise in real-time. His work emphasizes relation-discovery, revealing intricate patterns and connections to provide valuable insights. His research has contributed to publishing systems that enhance interoperability in open research data and provide understanding into cause and effect of policy-making decisions.
Short Bio
Madhav has completed his Masters in Computer Science with a focus in Data Science from the University of Zurich. His research interests span the area of applied machine learning, human-centered artificial intelligence (HCAI), and big data analytics.
ZORA Publication List
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Publications
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Tag-Xplore: Interactive Exploration of Annotation Practices in Digital Editions. In: EuroVis Workshop on Visual Analytics (EuroVA), Odense, Denmark, 27 May 2024. The Eurographics Association, online.
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LFPeers: Temporal similarity search and result exploration. Computers & Graphics, 115:81-95.
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How applicable are attribute-based approaches for human-centered ranking creation?. Computers & Graphics, 114:45-58.
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ORD-Xplore: Bridging Open Research Data Collections through Modality Abstractions. In: EuroVis 2023 - Posters, Leipzig, 12 Juni 2021 - 16 Juni 2021. The Eurographics Association, 49-51.
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A Design Space for Explainable Ranking and Ranking Models. In: EuroVis 2022 - Posters, Rome, 13 Juni 2022 - 17 Juni 2022. The Eurographics Association, 35-37.