activity
20192026
most citedHuman-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI

283 citations · 2.1k across the 112 of their papers we have counts for

collaborators
Showing 2021Show all

14 papers · 1 filter

cs.CR2021★ 2 cited

Malicious Selling Strategies in E-Commerce Livestream: A Case Study of Alibaba's Taobao and ByteDance's TikTok

Qunfang Wu, Yisi Sang, Dakuo Wang +1

Due to the limitations imposed by the COVID-19 pandemic, many users have shifted their shopping patterns from offline to online. Livestream shopping has become popular as one of th…

cs.LG2021★ 5 cited

Human-Centered AI for Data Science: A Systematic Approach

Dakuo Wang, Xiaojuan Ma, April Yi Wang

Human-Centered AI (HCAI) refers to the research effort that aims to design and implement AI techniques to support various human tasks, while taking human needs into consideration a…

cs.HC2021★ 4 cited

Organizational Distance Also Matters: How Organizational Distance Among Industrial Research Teams Affect Their Research Productivity

Dakuo Wang, Michael Muller, Qian Yang +3

Geographically distributed teams often face challenges in coordination and collaboration, lowering their productivity. Understanding the relationship between team dispersion and pr…

cs.CL2021★ 1 cited

It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Books

Bingsheng Yao, Dakuo Wang, Tongshuang Wu +4

Existing question answering (QA) techniques are created mainly to answer questions asked by humans. But in educational applications, teachers often need to decide what questions th…

cs.CL2021★ 1 cited

D2S: Document-to-Slide Generation Via Query-Based Text Summarization

Edward Sun, Yufang Hou, Dakuo Wang +2

Presentations are critical for communication in all areas of our lives, yet the creation of slide decks is often tedious and time-consuming. There has been limited research aiming…

cs.HC2021★ 18 cited

Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML

Shweta Narkar, Yunfeng Zhang, Q. Vera Liao +2

Automated Machine Learning (AutoML) is a rapidly growing set of technologies that automate the model development pipeline by searching model space and generating candidate models.…

cs.SE2021★ 4 cited

HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks

Xuye Liu, Dakuo Wang, April Wang +2

Jupyter notebook allows data scientists to write machine learning code together with its documentation in cells. In this paper, we propose a new task of code documentation generati…

cs.LG2021★ 5 cited

Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation

Yi Sun, Abel Valente, Sijia Liu +1

Prior works on formalizing explanations of a graph neural network (GNN) focus on a single use case - to preserve the prediction results through identifying important edges and node…

cs.HC2021★ 23 cited

CASS: Towards Building a Social-Support Chatbot for Online Health Community

Liuping Wang, Dakuo Wang, Feng Tian +7

Chatbots systems, despite their popularity in today's HCI and CSCW research, fall short for one of the two reasons: 1) many of the systems use a rule-based dialog flow, thus they c…

cs.HC2021★ 84 cited

Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks

April Yi Wang, Dakuo Wang, Jaimie Drozdal +6

Computational notebooks allow data scientists to express their ideas through a combination of code and documentation. However, data scientists often pay attention only to the code,…

cs.CY2021★ 138 cited

How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study

David Piorkowski, Soya Park, April Yi Wang +3

The development of AI applications is a multidisciplinary effort, involving multiple roles collaborating with the AI developers, an umbrella term we use to include data scientists…

cs.HC2021★ 78 cited

AutoDS: Towards Human-Centered Automation of Data Science

Dakuo Wang, Josh Andres, Justin Weisz +2

Data science (DS) projects often follow a lifecycle that consists of laborious tasks for data scientists and domain experts (e.g., data exploration, model training, etc.). Only til…

cs.HC2021★ 200 cited

"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment

Dakuo Wang, Liuping Wang, Zhan Zhang +5

Artificial intelligence (AI) technology has been increasingly used in the implementation of advanced Clinical Decision Support Systems (CDSS). Research demonstrated the potential u…

cs.LG2021★ 25 cited

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, \…