25 citations · 115 across the 24 of their papers we have counts for
26 papers
Bridging Natural Language and Interactive What-If Interfaces via LLM-Generated Declarative Specifications
Sneha Gathani, Sirui Zeng, Diya Patel +5
What-if analysis (WIA) lets users explore hypothetical scenarios by adjusting parameters, applying constraints, and scoping data through interactive interfaces. Current tools fall…
RUBICON: Agentic AI for Messy Enterprise Data
Fabian Wenz, Felix Treutwein, Çagatay Demiralp +1
Enterprise data exists in many forms, such as tables, text, maps, e-mail, and CAD models, that are access-controlled and hidden behind bespoke interfaces. Current agentic AI system…
PRAXA: A Grammar for What-If Analysis
Sneha Gathani, Kevin Li, Raghav Thind +5
What-if analysis is widely used to explore hypothetical scenarios and evaluate alternative pathways to desired results. However, current approaches are fragmented: systems implemen…
Humboldt: Metadata-Driven Extensible Data Discovery
Alex Bäuerle, Çağatay Demiralp, Michael Stonebraker
Data discovery is crucial for data management and analysis and can benefit from better utilization of metadata. For example, users may want to search data using queries like ``find…
Transactions Make Debugging Easy
Qian Li, Peter Kraft, Michael Cafarella +6
We propose TROD, a novel transaction-oriented framework for debugging modern distributed web applications and online services. Our critical insight is that if applications store al…
What-if Analysis for Business Professionals: Current Practices and Future Opportunities
Sneha Gathani, Zhicheng Liu, Peter J. Haas +1
What-if analysis (WIA) is essential for data-driven decision-making, allowing users to assess how changes in variables impact outcomes and explore alternative scenarios. Existing W…
Machine Learning with DBOS
Robert Redmond, Nathan W. Weckwerth, Brian S. Xia +5
We recently proposed a new cluster operating system stack, DBOS, centered on a DBMS. DBOS enables unique support for ML applications by encapsulating ML code within stored procedur…
Sigma Workbook: A Spreadsheet for Cloud Data Warehouses
James Gale, Max Seiden, Deepanshu Utkarsh +3
Cloud data warehouses (CDWs) bring large-scale data and compute power closer to users in enterprises. However, existing tools for analyzing data in CDWs are either limited in ad-ho…
Augmenting Decision Making via Interactive What-If Analysis
Sneha Gathani, Madelon Hulsebos, James Gale +2
The fundamental goal of business data analysis is to improve business decisions using data. Business users often make decisions to achieve key performance indicators (KPIs) such as…
TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration
Dongjin Choi, Sara Evensen, Çağatay Demiralp +1
Despite rapid developments in the field of machine learning research, collecting high-quality labels for supervised learning remains a bottleneck for many applications. This diffic…
Enhancing Review Comprehension with Domain-Specific Commonsense
Aaron Traylor, Chen Chen, Behzad Golshan +6
Review comprehension has played an increasingly important role in improving the quality of online services and products and commonsense knowledge can further enhance review compreh…
Teddy: A System for Interactive Review Analysis
Xiong Zhang, Jonathan Engel, Sara Evensen +3
Reviews are integral to e-commerce services and products. They contain a wealth of information about the opinions and experiences of users, which can help better understand consume…
Kyrix: Interactive Visual Data Exploration at Scale
Wenbo Tao, Xiaoyu Liu, Çağatay Demiralp +2
Scalable interactive visual data exploration is crucial in many domains due to increasingly large datasets generated at rapid rates. Details-on-demand provides a useful interaction…
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository
Kevin Hu, Neil Gaikwad, Michiel Bakker +7
Researchers currently rely on ad hoc datasets to train automated visualization tools and evaluate the effectiveness of visualization designs. These exemplars often lack the charact…
A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration
Marco Cavallo, Çağatay Demiralp
Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is d…
Developing Design Guidelines for Precision Oncology Reports
Selim Kalaycı, Çağatay Demiralp, Zeynep H. Gümüş
Precision oncology tests that profile tumors to identify clinically actionable targets have rapidly entered clinical practice. Effective visual presentation of the results of these…
Beyond Heuristics: Learning Visualization Design
Bahador Saket, Dominik Moritz, Halden Lin +3
In this paper, we describe a research agenda for deriving design principles directly from data. We argue that it is time to go beyond manually curated and applied visualization des…
Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions
Marco Cavallo, Çağatay Demiralp
With the rapid commoditization of wearable sensors, detecting human movements from sensor datasets has become increasingly common over a wide range of applications. To detect activ…
Data2Vis: Automatic Generation of Data Visualizations Using Sequence to Sequence Recurrent Neural Networks
Victor Dibia, Çağatay Demiralp
Rapidly creating effective visualizations using expressive grammars is challenging for users who have limited time and limited skills in statistics and data visualization. Even hig…
Clustrophile 2: Guided Visual Clustering Analysis
Marco Cavallo, Çağatay Demiralp
Data clustering is a common unsupervised learning method frequently used in exploratory data analysis. However, identifying relevant structures in unlabeled, high-dimensional data…
Clustrophile: A Tool for Visual Clustering Analysis
Çağatay Demiralp
While clustering is one of the most popular methods for data mining, analysts lack adequate tools for quick, iterative clustering analysis, which is essential for hypothesis genera…
Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions
Marco Cavallo, Çağatay Demiralp
Detecting motor activities from sensor datasets is becoming increasingly common in a wide range of applications with the rapid commoditization of wearable sensors. To detect activi…
Foresight: Rapid Data Exploration Through Guideposts
Çağatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy +1
Current tools for exploratory data analysis (EDA) require users to manually select data attributes, statistical computations and visual encodings. This can be daunting for large-sc…
Task-Based Effectiveness of Basic Visualizations
Bahador Saket, Alex Endert, Cagatay Demiralp
Visualizations of tabular data are widely used; understanding their effectiveness in different task and data contexts is fundamental to scaling their impact. However, little is kno…