28 citations · 105 across the 12 of their papers we have counts for
12 papers
Autonomous Data Processing using Meta-Agents
Udayan Khurana
Traditional data processing pipelines are typically static and handcrafted for specific tasks, limiting their adaptability to evolving requirements. While general-purpose agents an…
Towards Feature Engineering with Human and AI's Knowledge: Understanding Data Science Practitioners' Perceptions in Human&AI-Assisted Feature Engineering Design
Qian Zhu, Dakuo Wang, Shuai Ma +4
As AI technology continues to advance, the importance of human-AI collaboration becomes increasingly evident, with numerous studies exploring its potential in various fields. One v…
A Vision for Semantically Enriched Data Science
Udayan Khurana, Kavitha Srinivas, Sainyam Galhotra +1
The recent efforts in automation of machine learning or data science has achieved success in various tasks such as hyper-parameter optimization or model selection. However, key are…
A Survey on Semantics in Automated Data Science
Udayan Khurana, Kavitha Srinivas, Horst Samulowitz
Data Scientists leverage common sense reasoning and domain knowledge to understand and enrich data for building predictive models. In recent years, we have witnessed a surge in too…
How Much Automation Does a Data Scientist Want?
Dakuo Wang, Q. Vera Liao, Yunfeng Zhang +5
Data science and machine learning (DS/ML) are at the heart of the recent advancements of many Artificial Intelligence (AI) applications. There is an active research thread in AI, \…
Semantic Annotation for Tabular Data
Udayan Khurana, Sainyam Galhotra
Detecting semantic concept of columns in tabular data is of particular interest to many applications ranging from data integration, cleaning, search to feature engineering and mode…