Steve Oney is an Assistant Professor at the University of Michigan School of Information. His research focuses on enabling and encouraging more people to write and customize computer programs by creating new programming tools and exploring usability issues in programming environments. Steve completed his Ph.D in Carnegie Mellon's Human-Computer Interaction Institute where he was advised by Professor Brad Myers and Dr. Joel Brandt. He also attended MIT (CS & math S.B. in 2007, CS M.Eng in 2008).
Rebecca is a 3rd year PhD student in the EECS department at the University of Michigan, advised by Professor Steve Oney. She is generally interested in designing end-user programming systems. She currently is exploring ways to make creating and editing web macros more intuitive and visual, and less script-heavy. She has also designed programming-by-demonstration systems for creating responsive and interactive user interfaces. Previously she worked as a software engineer at MathWorks. Rebecca received her SB and MEng in Computer Science from MIT, where she was advised by Professor Rob Miller.
Mauli is a pre-candidate PhD student at the University of Michigan School of Information, where she is advised by Sile O'Modhrain and Steve Oney. Her research interests lie at the intersection of Human-Computer Interaction, Accessibility, and Programming. She is interested in lowering the barriers to programming and education for people with visual impairments by understanding their experiences through qualitative research methods. Before starting her PhD, Mauli was in the MS program (2018) at the University of Michigan School of Information. During her MS, she also worked closely with Matthew Kay, Michael Nebeling, and Sun Young Park. For her undergraduate studies, she attended the Indian Institute of Technology Guwahati (Design and Electronics, 2014), and was advised by Pradeep Yammiyavar.
April is a Ph.D. student at the School of Information at the University of Michigan, advised by Professor Steve Oney and Professor Christopher Brooks. With the growing complexity and interdisciplinary of the data science field, data science workers must embrace effective collaboration to improve the quality and efficiency of the work. Her work aims to understand different collaboration needs and challenges around data science, and design better programming tools to support collaborative data science. April received her B.Eng. in Computer Science from Zhejiang University and M.Sc. degree in Computer Science from Simon Fraser University, where her Masters thesis investigated non-programmers learning computational literacy.
Lei is a second year Ph.D. student at the University of Michigan School of Information, advised by Professor Steve Oney. Lei's research interests lie primarily in the fields of Human-Computer Interaction, Virtual/Augmented Reality, Authoring Tools, and 3D User Interfaces. Recently, he doing research in immersive authoring in Virtual Reality to enable users to easily create 3D interactive contents. He is constantly thinking about this fascinating question: how do we shape the languages (programming languages, body languages, natural languages, etc.) that people will use to customize and communicate with the holograms in the future? Previously, he was an undergraduate in the School of Software at Shanghai Jiao Tong University. He was a research member at the Digital ART Lab, supervised by Prof. Xubo Yang and Prof. Shuangjiu Xiao. He has also conducted research at Cascade Lab at the University of Illinois, Urbana-Champaign, supervised by Prof. Wai-Tat Fu.
Yan is currently a postdoctoral researcher at the University of Toronto, working with Tovi Grossman. Yan earned his PhD at the University of Michigan, advised by Dr. Steve Oney. His research aims to leverage human computation and machine intelligence to effectively solve complex tasks that require domain expertise, such as software development, video curation. He studies problems that users face with existing tools and methods, and builds computational systems to assist users via efficient collaboration and hybrid crowd-machine workflow.
Other Collaborators (Undergraduate and Master's)
- Hussain Alafaireet (MSI Researcher)
- Niu Chang (Undergraduate Summer Intern.)
- Erin Deutschman (Explore CS Research Mentee.)
- Natalie Gross (UMSI, Undergraduate Researcher)
- Yunjie Guo (Michigan CSE Undergraduate Researcher)
- Jaylin Herskovitz (Former Undergraduate Researcher. Now Ph.D. student at Michigan (CSE))
- Ruidong Liu (Undergraduate researcher. Now Ph.D. student at Cornell University)
- Gabriel Matute (Former Undergraduate Researcher. Now Ph.D. student at UC Berkeley)
- Jamie Neumann (UMSI, Undergraduate Researcher)
- Rebecca Parada (UMSI, Undergraduate Researcher)
- Tami Van Omen (Undergraduate researcher.)
- Yisen Wang (Explore CS Research Mentee.)
- Ningqi Wang
- Zihan Wu (Undergraduate Summer Intern. Currently: UMSI PhD Student)
- Jie Wei Wu (MSI Researcher. Now: Google Software Engineer)
- Jessica Wu (Former Undergraduate Researcher. Now Software Engineer at Amazon)
- Yin Xie (Former MS researcher. Now interaction designer at Internet Brands)
- Johnathan Yan (Undergraduate Researcher.)
- YiWei Yang (Former CSE Undergraduate Researcher. Now Ph.D. student at the University of Washington)
- Muhan Zhao (Michigan CSE Undergraduate Researcher)
- Yuan Zhou (Undergraduate Summer Intern. Georgia Tech M.S.)
- Licheng Zhu (MSI Researcher. Now: Senior User Experience Researcher at Thompson Reuters)
We are always excited to work with motivated and talented students.
Prospective Ph.D. Students
If you are interestested in joining our research group, you should apply to the UMSI PhD program. We strongly recommend reaching out to at least one member of the research group before you apply.
Prospective Masters and Undergraduate Students
If you are interested in collaborating with our research group, please reach out to firstname.lastname@example.org. You should ideally include your resume and a brief description of your interests.
We are particularly interested in collaborators who have experience with (or are interested in learning):