2026 Ye-Yi Wang: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	38	10276	9988	4313	4137	120	5830

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Computer Science

10276

9988

4313

4137

120

5830

Overview

Ye-Yi Wang is a researcher affiliated with Microsoft in the United States. Their work primarily falls within the field of Computer Science, with a focus on Artificial Intelligence, Computer Vision and Pattern Recognition, and General Social Sciences as subfields of study.

The main topics of Ye-Yi Wang's research include:

Text and Document Classification Technologies
Topic Modeling
Multimodal Machine Learning Applications
Natural Language Processing Techniques
Computational and Text Analysis Methods

Ye-Yi Wang has contributed to several publications, notably in venues such as arXiv (Cornell University) and the Proceedings of the ACM Web Conference 2022. Recent papers include:

Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification, 2022, Proceedings of the ACM Web Conference 2022
Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification, 2022, arXiv (Cornell University)
Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding, 2023, arXiv (Cornell University)

The researcher collaborates frequently with several coauthors, including:

Z. Shen
Chieh-Han Wu
Junheng Hao
Kuansan Wang
Jiawei Han

These collaborations and publication venues indicate a focus on text classification technologies and contrastive learning methods applied to multi-label and scientific literature domains. The recent work reflects an emphasis on zero-shot and multi-task learning approaches, addressing challenges related to understanding and categorizing large, complex datasets without extensive labeled data.

Best Publications

Multi-Domain Joint Semantic Frame Parsing Using Bi-Directional RNN-LSTM.

Dilek Hakkani-Tür;Gokhan Tur;Asli Celikyilmaz;Yun-Nung Chen

482
Citations
Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval

Xiaodong Liu;Jianfeng Gao;Xiaodong He;Li Deng

459
Citations
Learning query intent from regularized click graphs

Xiao Li;Ye-Yi Wang;Alex Acero

409
Citations
Decoding Algorithm in Statistical Machine Translation

Ye-Yi Wang;Alex Waibel

227
Citations
Is word error rate a good indicator for spoken language understanding accuracy

Ye-Yi Wang;A. Acero;C. Chelba

198
Citations
Statistical classifiers for spoken language understanding and command/control scenarios

Alejandro Acero;Ciprian Chelba;YeYi Wang;Leon Wong

183
Citations
Spoken language understanding

Ye-Yi Wang;Li Deng;A. Acero

180
Citations
Use of a unified language model

Xuedong D. Huang;Milind V. Mahajan;Ye-Yi Wang;Xiaolong Mou

170
Citations
A system for automatically annotating training data for a natural language understanding system

Alejandro Acero;Ye-Yi Wang;Leon Wong

162
Citations
Extracting structured information from user queries with semi-supervised conditional random fields

Xiao Li;Ye-Yi Wang;Alex Acero

162
Citations
Creating a language model for a language processing system

Xuedong D. Huang;Milind V. Mahajan;Ye-Yi Wang;Xiaolong Mou

148
Citations
An introduction to voice search

Ye-Yi Wang;Dong Yu;Yun-Cheng Ju;A. Acero

129
Citations
System for using statistical classifiers for spoken language understanding

Alejandro Acero;Ciprian Chelba;Ye-Yi Wang;Leon Wong

126
Citations
Intent detection using semantically enriched word embeddings

Joo-Kyung Kim;Gokhan Tur;Asli Celikyilmaz;Bin Cao

123
Citations
A unified context-free grammar and n-gram model for spoken language processing

Ye-Yi Wang;M. Mahajan;Xuedong Huang

113
Citations
System with composite statistical and rules-based grammar model for speech recognition and natural language understanding

Ye-Yi Wang;Alejandro Acero;Ciprian Chelba

109
Citations
Discriminative models for spoken language understanding.

Ye-Yi Wang;Alex Acero

94
Citations
Template concatenation for capturing multiple concepts in a voice query

Yun-Cheng Ju;Wei Wu;Ye-Yi Wang;Xiao Li

93
Citations
An Integrative and Discriminative Technique for Spoken Utterance Classification

S. Yaman;Li Deng;Dong Yu;Ye-Yi Wang

90
Citations
Automated Directory Assistance System - from Theory to Practice

Dong Yu;Yun-Cheng Ju;Ye-Yi Wang;Geoffrey Zweig

88
Citations

Frequent Co-Authors

Alejandro Acero Apple (United States)

Li Deng Citadel

Dong Yu Tencent (China)

Xuedong Huang Microsoft (United States)

Kuansan Wang Microsoft (United States)

Ciprian Chelba Google (United States)

Dilek Hakkani-Tur University of Illinois at Urbana-Champaign

Jianfeng Gao Microsoft (United States)

Gokhan Tur Amazon (United States)

Hsiao-Wuen Hon Microsoft Research Asia (China)

External Links

Personal website of Ye-Yi Wang

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Pursuing Computer Science in the USA opens doors to many related online degrees and career paths. For those interested in data analytics and machine learning, exploring the best online data science masters can provide advanced technical training while maintaining flexibility for working professionals.

If you're drawn to the intersection of technology and management, consider a cheapest mba online to build leadership and business skills without high tuition costs. For learners who want to fast-track their education, there are one year masters programs online across various disciplines to help accelerate your entry into specialized roles.

Additionally, those interested in the built environment may benefit from an accelerated online construction management degree, combining project oversight with digital technologies. No matter your interest, these online options offer both affordability and convenience, putting ambitious career goals within reach.