Thomas and Margaret Huang Award Recipients

The Thomas and Margaret Huang Award for Graduate Research supports graduate students in Human-Computer Intelligent Interaction (HCII) at the Beckman Institute. The Huang Fund, which supports the award, was established by Image Formation and Processing Group alumni James J. Kuch (M.S. ECE 1994) and Chang Wen Chen (Ph.D. 1992). Professor Thomas Huang has advised over 100 students during his career, which has spanned five decades and three major research universities (MIT, Purdue, and UIUC). He is a founder of the Image Formation and Processing group and a long-term co-chair of the HCII main research theme.

2018 Awardees

Wei Han
Wei Han, a Ph.D. student in electrical and computer engineering, plans to investigate the problem of designing compact neural network models, provide a unified understanding of the existing empirically proved model selection strategies, and demonstrate new principles for designing parameter-efficient models. He will work with Thomas Huang, a research professor of electrical and computer engineering and founder of the Image Formation and Processing Group.

Ding Liu
Ding Liu, a Ph.D. candidate in electrical and computer engineering, will focus his research on connecting low-level image processing and high-level vision through deep learning. He will also work with Thomas Huang.

2017 Awardees

Renato Azevedo
Renato Azevedo is pursuing a Ph.D. in educational psychology. This award will help him continue his research in interdisciplinary cognitive science with Dan Morrow, a professor of educational psychology and member of the Cognition, Lifespan Engagement, Aging, and Resilience Group.

Ning Xu
Ning Xu is a Ph.D. student in electrical and computer engineering. He will work with his adviser, Thomas S. Huang, a research professor of electrical and computer engineering and a member of the Organizational Intelligence and Computational Social Science Group, on his research project, "Using Deep Learning for Video Object Segmentation."

2016 Awardees

Shiyu Chang
Shiyu Chang is a fifth-year Ph.D. student working under the supervision of Thomas Huang in the Image Formation and Processing (IFP) Group. His research focus is on "similarity" in networks.

Zhangyang Wang
Zhangyang Wang is a fourth-year Ph.D. student working with Huang. His principal area of interest is addressing machine learning and visual computing problems using advanced feature learning techniques.

2015 Awardees

Jessie Chin
Jessie explores information search and self-regulation across the lifespan. She is pursuing her Ph.D. in educational psychology and has worked with Dan Morrow, Elizabeth Stine-Morrow, and Wai-Tat Fu, all from the Human Perception and Performance Group. Jessie was also a Beckman Graduate Fellow in 2011–2012.

Jia-Bin Huang
Jia-Bin will earn his Ph.D. in electrical and computer engineering and is working with Narendra Ahuja from the Artificial Intelligence Group. His research is in the area of computer vision, specifically in the novel use of physically grounded constraints for solving inverse problems in image and video processing.

2014 Awardees

Brennan Payne
Brennan received a Ph.D. in cognitive science of teaching and learning in Department of Educational Psychology in May 2014. He has been working in the Adult Learning Lab at the Beckman Institute with Elizabeth Stine-Morrow. His research has focused on two main questions in the cognitive science of aging: first, how do age-related changes in cognitive ability impact sentence and discourse comprehension? Second, what are the mechanisms underlying cognitive enrichment in older adulthood? This second question includes topics such as the impact of computerized cognitive training and intellectual and activity engagement on memory, reasoning, learning, and attention in later life.

Vuong Le
Vuong’s single goal is to do top-notch research in visual media analysis. He has been working with Thomas Huang and the Information Formation and Processing Group at Beckman. Through his research experiences, he realized that a major difficulty in image understanding is the high variation of object appearance caused by different imaging conditions such as viewpoint, illumination, and object deformation, so he has decided to continue research in 3D modeling. Vuong is pursuing a Ph.D. in electrical and computer engineering.