My research interests lie in the fields of accessibility, human computer interaction and design. Specifically, I am exploring how to combine novel sensing technologies and innovative design to help people.
Cornell University 2014-Present
Ph.D. in Information Science
Zhejiang University 2010-2014
B.Eng in Electrical Engineering
B.Eng in Industrial Design
University of California, Davis 2013
GREAT Summer Research Program
Lei Shi, Ross McLachlan, Yuhang Zhao, Shiri Azenkot. Magic Touch: Interacting with 3D Printed Graphics. In Proceedings of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’16), 329-330.
Lei Shi, Idan Zelzer, Catherine Feng, Shiri Azenkot. Tickers and Talker: An Accessible Labeling Toolkit for 3D Printed Models. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI ’16), 4896-4907. [pdf] [demo]
Lei Shi. Talkabel: A Labeling Method for 3D Printed Models. In Proceedings of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’15), 361-362. *1st Place, Student Research Competition* [pdf] [acm]
IBM Research 2016.5-2016.8
Research Intern, Cognitive Environments and Cognitive Objects Group
Cornell University 2014.9-2015.9
Research Assistant, Teaching Assistant
Wenzhou Electric Power Design Co., Ltd 2013.9-2013.11
Electrical Engineer Intern
Converting Everyday Objects into Smart Controllers: We developed a novel technique that allows users to use passive everyday objects to control a smart environment. The technique was deployed at the Cognitive Environments Laboratory.
Always Accessible Input: We build novel interfaces that enable users to access and input information on the go. We use different sensors (e.g., EMG, IMU) and interaction techniques to connect users with up-to-date information.
Interactive Fabrication Tools: We use 3D printing to build education materials for blind students. We design and build tools that can make printed models more interactive and can explain themselves without specialized equipment.
University of California Davis, Research Intern
Innovative Traditional Chinese Medicine App: We develope an iOS App that allows users detect their health conditions by simply scanning their tongues and faces.
INFO 5305: Usability and User Experience Research, Cornell Tech 2016.8-2016.12
INFO 6410: HCI and Design, Cornell Tech 2015.1-2015.5, 2016.1-2016.5
Interactive Game Design Workshop, Zhejiang University 2013.3 / 2013.10
Lecturer, Basic Processing and Arduino Skills
First Place, Student Research Competition, ASSETS 2015
Aol Fellow, Connected Experiences Lab, Cornell Tech 2015
Conference Travel Grant, Graduate School, Cornell University 2015, 2016
Distinguish Graduation Thesis Awards 2014
Outstanding Student Leader Award (2%), Zhejiang University 2012
First-Class Scholarship for Outstanding Students (<3%), Zhejiang University 2011
Languages: Processing, Arduino, HTML, CSS, Python
Electronics: Arduino, Digital Signal Processor (DSP)
Design: Rhinoceros, Keyshot, Illustrator, Photoshop
Qualitative Methods: Interviewing, Participatory Design
Quantitative Methods: Statistical Analysis, Hypothesis Testing
Design Methods: Profile and Scenario, Storyboard, Heuristic Evaluations
Native Proficiency: Mandarin, Wenzhounese
Full Professional Proficiency: English
Elementary Proficiency: Japanese