18 citations · 74 across the 16 of their papers we have counts for
16 papers
ASMR: Agentic Schema Generation for Ship Maintenance Report Writing
Sohrab Namazi Nia, Amogh Dalal, Ning Sa +6
In this paper, we study the automatic schema generation problem: given a collection of historical ship maintenance and operational reports across multiple form categories, automati…
Human-Data Interaction, Exploration, and Visualization in the AI Era: Challenges and Opportunities
Jean-Daniel Fekete, Yifan Hu, Dominik Moritz +8
The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. In the AI era…
Multi-Attribute Group Fairness in -NN Queries on Vector Databases
Thinh On, Senjuti Basu Roy, Baruch Schieber
We initiate the study of multi-attribute group fairness in -nearest neighbor (-NN) search over vector databases. Unlike prior work that optimizes efficiency or query filterin…
Label Curation Using Agentic AI
Subhodeep Ghosh, Bayan Divaaniaazar, Md Ishat-E-Rabban +2
Data annotation is essential for supervised learning, yet producing accurate, unbiased, and scalable labels remains challenging as datasets grow in size and modality. Traditional h…
Continuous Fairness On Data Streams
Subhodeep Ghosh, Zhihui Du, Angela Bonifati +3
We study the problem of enforcing continuous group fairness over windows in data streams. We propose a novel fairness model that ensures group fairness at a finer granularity level…
Aegis: A Correlation-Based Data Masking Advisor for Data Sharing Ecosystems
Omar Islam Laskar, Fatemeh Ramezani Khozestani, Ishika Nankani +3
Data sharing ecosystems connect providers, consumers, and intermediaries to facilitate the exchange and use of data for a wide range of downstream tasks. In sensitive domains such…
Personalized Top-k Set Queries Over Predicted Scores
Sohrab Namazi Nia, Subhodeep Ghosh, Senjuti Basu Roy +1
This work studies the applicability of expensive external oracles such as large language models in answering top-k queries over predicted scores. Such scores are incurred by user-d…
MISFEAT: Feature Selection for Subgroups with Systematic Missing Data
Bar Genossar, Thinh On, Md. Mouinul Islam +3
We investigate the problem of selecting features for datasets that can be naturally partitioned into subgroups (e.g., according to socio-demographic groups and age), each with its…
Recommending Deployment Strategies for Collaborative Tasks
Dong Wei, Senjuti Basu Roy, Sihem Amer-Yahia
Our work contributes to aiding requesters in deploying collaborative tasks in crowdsourcing. We initiate the study of recommending deployment strategies for collaborative tasks to…
Eliciting Worker Preference for Task Completion
Mohammadreza Esfandiari, Senjuti Basu Roy, Sihem Amer-Yahia
Current crowdsourcing platforms provide little support for worker feedback. Workers are sometimes invited to post free text describing their experience and preferences in completin…
Combating the Cold Start User Problem in Model Based Collaborative Filtering
Sampoorna Biswas, Laks V. S. Lakshmanan, Senjuti Basu Ray
For tackling the well known cold-start user problem in model-based recommender systems, one approach is to recommend a few items to a cold-start user and use the feedback to learn…
Feature Based Task Recommendation in Crowdsourcing with Implicit Observations
Habibur Rahman, Lucas Joppa, Senjuti Basu Roy
Existing research in crowdsourcing has investigated how to recommend tasks to workers based on which task the workers have already completed, referred to as {\em implicit feedback}…
From Group Recommendations to Group Formation
Senjuti Basu Roy, Laks V. S. Lakshmanan, Rui Liu
There has been significant recent interest in the area of group recommendations, where, given groups of users of a recommender system, one wants to recommend top-k items to a group…
"The Whole Is Greater Than the Sum of Its Parts": Optimization in Collaborative Crowdsourcing
Habibur Rahman, Senjuti Basu Roy, Saravanan Thirumuruganathan +2
In this work, we initiate the investigation of optimization opportunities in collaborative crowdsourcing. Many popular applications, such as collaborative document editing, sentenc…
Optimization in Knowledge-Intensive Crowdsourcing
Senjuti Basu Roy, Ioanna Lykourentzou, Saravanan Thirumuruganathan +2
We present SmartCrowd, a framework for optimizing collaborative knowledge-intensive crowdsourcing. SmartCrowd distinguishes itself by accounting for human factors in the process of…
Predicting Risk-of-Readmission for Congestive Heart Failure Patients: A Multi-Layer Approach
Kiyana Zolfaghar, Nele Verbiest, Jayshree Agarwal +7
Mitigating risk-of-readmission of Congestive Heart Failure (CHF) patients within 30 days of discharge is important because such readmissions are not only expensive but also critica…