天美传媒

 is a research affiliate at the  and the Division of Disability Resources and Educational Services, or DRES, at the University of Illinois Urbana-Champaign.
He has served as the head coach of the University of Illinois wheelchair track and road racing team since 2005. In that time, his athletes have won 55 medals across four paralympic games while setting 14 world records on the track, and have won the Boston Marathon, London Marathon, Chicago Marathon, and New York City Marathon. In recognition of such performances, he has been named the USOC U.S. Paralympic Coach of the Year on three occasions.
Bleakney conducts research related to assistive technology and devices for individuals with disabilities as well as research related to human performance, specifically for athletes with disabilities. In 2017, he established the UIUC Human Performance and Mobility Maker Lab, an interdisciplinary lab where students with and without disabilities collaborate to design and develop assistive technology. As director of the HPML, Bleakney is faculty in the School of Art + Design at UIUC. He also co-directs the  at the Beckman Institute, which supports interdisciplinary design research centered around the lived experiences of people with disabilities.
He has also consulted with BMW, Toyota, Bridgestone Americas, and several Champaign-based start-ups in advancing racing wheelchair and other accessible technology research and development initiatives.
Education

M.S., print journalism, University of Illinois Urbana-Champaign, 2002
B.A., English literature, University of Illinois at Urbana-Champaign, 2000

Honors

2019: Chancellor's Academic Professional Excellence Award
2016: USPOC U.S. Paralympic Coach of the Year
2015: USOPC Doc Counsilman Science Award
2015: USPOC U.S. Paralympic Coach of the Year
2009: Alexis Wernsing Innovation Award
2007: USPOC U.S. Paralympic Coach of the Year

 is a  and a  at the University of Illinois Urbana-Champaign. He is the William L. Everitt Faculty Scholar in ECE and holds affiliations in the Department of Speech and Hearing Science, Coordinated Science Lab, , and Department of Computer Science. He also leads the , a new research initiative to make voice recognition technology more useful for people with a range of diverse speech patterns and disabilities. 
Hasegawa-Johnson has been on the faculty at the University of Illinois since 1999. His research addresses automatic speech recognition with a focus on the mathematization of linguistic concepts. His group has developed mathematical models of concepts from linguistics including a rudimentary model of pre-conscious speech perception (the landmark-based speech recognizer), a model that interprets pronunciation variability by figuring out how the talker planned his or her speech movements (tracking of tract variables from acoustics, and of gestures from tract variables), and a model that uses the stress and rhythm of natural language (prosody) to disambiguate confusable sentences. Applications of his research include:

Speech recognition for talkers with cerebral palsy. The automatic system, suitably constrained, outperforms a human listener.

Provably correct unsupervised ASR, or ASR that can be trained using speech that has no associated text transcripts.


Equal Accuracy Ratio regularization: Methods that reduce the error rate gaps caused by gender, race, dialect, age, education, disability and/or socioeconomic class.


Automatic analysis of the social interactions between infant, father, mother, and older sibling during the first eighteen months of life.


Hasegawa-Johnson is currently Senior Area Editor of the journal IEEE Transactions on Audio, Speech and Language and a member of the ISCA Diversity Committee. He has published 308 peer-reviewed journal articles, patents, and conference papers in the general area of automatic speech analysis, including machine learning models of articulatory and acoustic phonetics, prosody, dysarthria, non-speech acoustic events, audio source separation, and under-resourced languages.
Education

Postdoctoral fellow, University of California at Los Angeles, 1996-1999

Ph.D., Massachusetts of Technology, 1996

M.S., Massachusetts Institute of Technology, 1989

Honors

2023: Fellow of the International Speech Communication Association for contributions to knowledge-constrained signal generation

2020: Fellow of the IEEE, for contributions to speech processing of under-resourced languages


2011: Fellow of the Acoustical Society of America, for contributions to vocal tract and speech modeling


2009: Senior Member of the Association for Computing Machinery


2004: Member, Articulograph International Steering Committee; CLSP Workshop leader, "Landmark-Based Speech Recognition”, Invited paper


2004: NAACL workshop on Linguistic and Higher-Level Knowledge Sources in Speech Recognition and Understanding


2003: List of faculty rated as excellent by their students


2002: NSF CAREER award


1998: NIH National Research Service Award


Personal website: 
CV: 

Rachel Adler is an associate professor in the School of Information Sciences at the University of Illinois Urbana-Champaign where she co-directs the Information Experience and Accessibility Lab. Adler's research interests are in human-computer interaction, accessibility, and computing education. She is particularly interested in designing applications for and with people with disabilities. Some of her recent projects include co-designing a mobile health application to empower cancer survivors with disabilities, co-designing a mobile health peer navigator intervention for people with disabilities, and creating simulation games to teach students about accessible design. 
Her research has been funded through the National Institutes of Health; National Science Foundation; National Institute on Disability, Independent Living, and Rehabilitation Research; and the U.S. Department of Education. 
Adler was previously an associate professor in the Department of Computer Science at Northeastern Illinois University. She was also a visiting associate professor in the Department of Computer Science at Northwestern University. She received her Ph.D. in computer science from the Graduate Center of the City University of New York. 

 is a Beckman Institute researcher and an assistant professor in the School of Information Sciences at the University of Illinois Urbana-Champaign.
Within the iSchool, Seo directs the Accessible Computing Lab. His research topics include accessible computing, universal design, inclusive data science, and equitable healthcare technologies. As an information and learning scientist, his research focuses particularly on how to make computational literacy more accessible to people with dis/abilities by using multimodal data representation. His research projects have involved not just web accessibility, but also human-centered design and development studies, including inclusive makerspaces, tangible block-based programming, accessible data science (e.g., data actualization, sonification, and verbalization), and accessible/reproducible scientific writing tools for people with and without dis/abilities.
At the Beckman Institute, Seo's research addresses accessibility barriers at the intersection of information and learning. Specifically, he designs, develops, and evaluates accessible technologies that can offer better usability and learnability to blind and low-vision individuals. His two primary focus areas are accessible computing and accessible healthcare, given the increasing importance of computing and healthcare in our daily lives. He is particularly interested in multimodal data representation methods, such as physical data visualization, spatial audio sonification, and generative AI-assisted visual descriptions, to make data and information more accessible to people with visual impairments.
Research areas:


Accessible computing/data science


Ability-based human-computer interaction


Inclusive Learning Sciences/STEM+C education across dis/abilities


Accessible health informatics


 
Research interests:


Learning Analytics/Statistical Computing


Data Science-Based Reproducible Research


Large-Scale Virtual/Quantitative Ethnography


 
Education


Ph.D. Candidate (ABD), Learning, Design, and Technology, The Pennsylvania State University, 2021


M.Ed., Learning, Design, and Technology, The Pennsylvania State University, 2016


Double B.A., Education and English Literature, Sungkyunkwan University, 2014