2026 Mark Hasegawa-Johnson: 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	49	5801	5635	2636	2542	396	12222

Research.com Recognitions

2020 - IEEE Fellow For contributions to speech processing of under-resourced languages
2009 - ACM Senior Member

Overview

Mark Hasegawa-Johnson is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their primary research contributions are in the field of computer science, with a focus on artificial intelligence, signal processing, and computer vision and pattern recognition. A smaller portion of their work also touches on pharmacy and experimental and cognitive psychology.

The scientist's work covers several main topics related to speech and audio processing. These include:

Speech Recognition and Synthesis
Speech and Audio Processing
Music and Audio Processing
Natural Language Processing Techniques
Topic Modeling
Multimodal Machine Learning Applications
Infant Health and Development

Selected recent publications by Mark Hasegawa-Johnson include the following:

"Unsupervised Speech Decomposition via Triple Information Bottleneck," 2020, published in arXiv (Cornell University)
"SpeechSplit2.0: Unsupervised Speech Disentanglement for Voice Conversion without Tuning Autoencoder Bottlenecks," 2022, presented at ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
"Unsupervised Text-to-Speech Synthesis by Unsupervised Automatic Speech Recognition," 2022, presented at Interspeech 2022
"ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers," 2022, published in arXiv (Cornell University)
"Speech Technology for Unwritten Languages," 2020, published in IEEE/ACM Transactions on Audio Speech and Language Processing

Frequent co-authors collaborating with Mark Hasegawa-Johnson include:

Chang D. Yoo
Kaizhi Qian
Jialu Li
Nancy L. McElwain
John Harvill

Publication venues where the scientist most often publishes are:

arXiv (Cornell University)
IEEE/ACM Transactions on Audio Speech and Language Processing
Interspeech 2022
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Speech Communication

The scientist has received professional recognitions including being named an IEEE Fellow in 2020 for contributions to speech processing of under-resourced languages. They were also recognized as an ACM Senior Member in 2009.

Best Publications

Semantic Image Inpainting with Deep Generative Models

Raymond A. Yeh;Chen Chen;Teck Yian Lim;Alexander G. Schwing;Alexander G. Schwing

1259
Citations
Joint optimization of masks and deep recurrent neural networks for monaural source separation

Po-Sen Huang;Minje Kim;Mark Hasegawa-Johnson;Paris Smaragdis

530
Citations
Deep learning for monaural speech separation

Po Sen Huang;Minje Kim;Mark Hasegawa-Johnson;Paris Smaragdis

519
Citations
Semantic Image Inpainting with Perceptual and Contextual Losses.

Raymond A. Yeh;Chen Chen;Teck-Yian Lim;Mark Hasegawa-Johnson

473
Citations
Brain anatomy differences in childhood stuttering.

Soo Eun Chang;Kirk I. Erickson;Nicoline G. Ambrose;Mark A. Hasegawa-Johnson

443
Citations
Singing-voice separation from monaural recordings using robust principal component analysis

Po-Sen Huang;Scott Deeann Chen;Paris Smaragdis;Mark Hasegawa-Johnson

422
Citations
Dysarthric speech database for universal access research

Heejin Kim;Mark Hasegawa-Johnson;Adrienne Perlman;Jon Gunderson

399
Citations
AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

Kaizhi Qian;Yang Zhang;Shiyu Chang;Xuesong Yang

275
Citations
Dilated Recurrent Neural Networks

Shiyu Chang;Yang Zhang;Wei Han;Mo Yu

244
Citations
AVICAR: audio-visual speech corpus in a car environment.

Bowon Lee;Mark Hasegawa-Johnson;Camille Goudeseune;Suketu Kamdar

241
Citations
Signal-based and expectation-based factors in the perception of prosodic prominence

Jennifer Cole;Yoonsook Mo;Mark Hasegawa-Johnson

236
Citations
Real-world acoustic event detection

Xiaodan Zhuang;Xi Zhou;Mark A. Hasegawa-Johnson;Thomas S. Huang

224
Citations
Regression from patch-kernel

Shuicheng Yan;Xi Zhou;Ming Liu;M. Hasegawa-Johnson

214
Citations
Acoustic fall detection using Gaussian mixture models and GMM supervectors

Xiaodan Zhuang;Jing Huang;Gerasimos Potamianos;Mark Hasegawa-Johnson

190
Citations
Streaming Recommender Systems

Shiyu Chang;Yang Zhang;Jiliang Tang;Dawei Yin

163
Citations
Prosodic effects on acoustic cues to stop voicing and place of articulation: Evidence from Radio News speech

Jennifer Cole;Heejin Kim;Hansook Choi;Mark Hasegawa-Johnson

161
Citations
Singing-voice separation from monaural recordings using deep recurrent neural networks

Po Sen Huang;Minje Kim;Mark Hasegawa-Johnson;Paris Smaragdis

160
Citations
Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 JHU Summer workshop

K. Livescu;O. Cetin;M. Hasegawa-Johnson;S. King

146
Citations
SIFT-Bag kernel for video event analysis

Xi Zhou;Xiaodan Zhuang;Shuicheng Yan;Shih-Fu Chang

146
Citations
Landmark-based speech recognition: report of the 2004 Johns Hopkins summer workshop

M. Hasegawa-Johnson;J. Baker;S. Borys;K. Chen

139
Citations
Unsupervised Speech Decomposition via Triple Information Bottleneck

Kaizhi Qian;Yang Zhang;Shiyu Chang;David Cox

55
Citations
Zero-Shot Voice Style Transfer with Only Autoencoder Loss.

Kaizhi Qian;Yang Zhang;Shiyu Chang;Xuesong Yang

25
Citations

Frequent Co-Authors

Thomas S. Huang University of Illinois at Urbana-Champaign

Ken Chen The University of Texas MD Anderson Cancer Center

Shiyu Chang University of California, Santa Barbara

Stephen E. Levinson University of Illinois at Urbana-Champaign

Deming Chen University of Illinois at Urbana-Champaign

Daniel G. Morrow University of Illinois at Urbana-Champaign

Najim Dehak Johns Hopkins University

Elliot Saltzman Boston University

Louis Goldstein University of Southern California

Emmanuel Dupoux School for Advanced Studies in the Social Sciences

External Links

Personal website of Mark Hasegawa-Johnson Google Scholar page

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

Related Online Degrees & Career Pathways

Exploring computer science as an academic and career path opens a world of possibilities. For students concerned about their academic history, there are online colleges that accept low gpa, making quality education more accessible and inclusive.

If you’re looking to fast-track your education, consider one of the accelerated cs degree programs. These allow you to earn your credential more quickly, helping you start your career sooner.

Computer science skills are highly transferable and can lead to a variety of career options, including roles outside traditional tech fields. For example, jobs in sustainability and technology intersect, and learning what can you do with an environmental studies degree can highlight unique opportunities in environmental data science or policy analysis.

Students interested in technical solutions to environmental challenges should also review online environmental engineering degree science and engineering programs. These degrees blend computing, engineering, and sustainability, leading to innovative career pathways.