Introduction
Now more than ever, technology is capable of addressing the issues that we face both as individuals and as a society. These problems include, but are not limited to, the lack of assistive technologies for individuals with disabilities, limited access to health screening technologies, etc. The Access Computing Summer Program (ACSP) brings together the next generation of global talent in computer science and related fields to develop highly impactful solutions that address these grand challenges. Students in the ACSP will be able to practice a variety of human-centered design methods to develop novel sensing techniques, user-friendly interfaces, and cutting-edge computer technologies.
About the Program
The Access Computing Summer Program is be held in summer. We aim to recruit up to eighteen full-time participants with a background in computer science, electrical engineering, industrial engineering, psychology, or some other equivalent discipline. Participants will join a well-defined applied research project in a team formed by two participants and one mentor. The sponsoring faculty will supplement the mentorship with periodic advising.
The Access Computing Summer Program will also include lectures on topics within ubiquitous computing and human-computer interaction from academic and industry speakers. The program will also include lectures/workshops on embedded hardware, signal processing, machine learning, and paper reading/writing skills.
Personnel
This program is sponsored by the Global Innovation Exchange (GIX), a program founded by the University of Washington, Tsinghua University, and Microsoft to train the next leaders of innovation. This program is co-hosted by the China Computer Federation (CCF), a leading organization on computing technology and applications in China.
Program participants will be led by numerous experts in ubiquitous computing and human-computer interaction:
General Chairs
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Yuanchun Shi, Professor, Tsinghua University
Visit the Pervasive Human-Computer Interaction Lab at Tsinghua University in Beijing website to learn more.
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Shwetak Patel, Professor, University of Washington
View his bio or visit the Ubicomp lab at the University of Washington in Seattle
website to learn more. -
Pei-Luen Rau, Professor, Tsinghua University
View his bio or visit the Human Factor Research Lab at Tsinghua University in Beijing website to learn more.
Program Chairs
- Yuntao Wang, Assistant Professor (Research Track), Tsinghua University
- Alex Mariakakis, Assistant Professor, University of Toronto
- Yukang Yan, Postdoctoral Researcher, Tsinghua University; Assistant Professor @ HKUST from 2023 Fall
Mentors
- Yuntao Wang, Assistant Professor (Research Track), Tsinghua University
- Alex Mariakakis, Assistant Professor, University of Toronto
- Yukang Yan, Postdoctoral Researcher, Tsinghua University; Assistant Professor @ HKUST from 2023 Fall
- Xin Yi, Assistant Professor, Tsinghua University
- Tengxiang Zhang, Associate Research Scientist, Chinese Academy of Sciences
- Xin Liu, Ph.D. candidate, University of Washington
- Xuhai Xu, Ph.D. candidate, University of Washington
- Jason Hoffman, Ph.D. student, University of Washington
- Girish Narayanswamy, Ph.D. student, University of Washington
- Kenneth Christofferson, Ph.D. student, University of Toronto
- Chun Yu, Associate Professor, Tsinghua University.
- Anandghan Waghmare, Ph.D. student, University of Washington
Access Computing Summer Program in the Past Years
ACSP 2021
ACSP 2021 had over 90 applications from 9 countries and 38 universities. We recruited 15 participants who were engaged in 8 innovative projects. The ACSP 2021 had 5 paper submissions to top-tier conferences/journals in the areas of HCI, ubicomp, and healthcare. 3 papers were accepted by the CHI 2022 or IMWUT. There are 3 more ongoing projects targeting top-tier conferences/journals including UIST 2022 and IMWUT.
ACSP 2020
ACSP 2020 had over 100 applications from 8 countries and 41 universities. We recruited 25 participants who were engaged in 10+ innovative projects. The ACSP had 8 paper submissions to top-tier conferences/journals in the areas of HCI and ubicomp. 5 papers were accepted by the CHI 2021, CHI 2022, IMWUT, or DIS 2021.
Post-graduate Offers
More than 25 participants received Ph.D. offers from Tsinghua University, Georgia Institute of Technology, Carnegie Mellon University, University of California San Diego, and the University of Toronto or master’s degree offers from Tsinghua University, Carnegie Mellon University, University of Washington, University of Calgary, Sorbonne University, University of Edinburgh, etc.
Project Showcase
Access Computing is broadly focused on human-centered applications of computer science, particularly human-computer interaction (HCI) and ubiquitous computing (ubicomp). These domains require a wide variety of skills, including some combination of applied sensing, signal processing, machine learning, computer vision, embedded systems, and human-centered design. Examples of past projects by ACSP mentors and students are listed below.
Facilitating Text Entry on Smartphones with QWERTY Keyboard for Users with Parkinson’s Disease (Accepted by ACM CHI 2021, completed during ACSP 2020)
HulaMove: Using Commodity IMU for Waist Interaction (Accepted by ACM CHI 2021, completed during ACSP 2020) Video.
Understanding the Design Space of Mouth Microgestures (Accepted by DIS 2021, completed during ACSP 2020)
FaceOri: Tracking Head Position and Orientation Using Ultrasonic Ranging on Earphones (Accepted by CHI 2022, completed during ACSP 2020)
TypeOut: Leveraging Just-in-Time Self-Affirmation for Smartphone Overuse Reduction (Accepted by CHI 2022, completed during ACSP 2021)
SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices (Accepted by IMWUT 2021, completed during ACSP 2020)
MobilePhys: Personalized Mobile Camera-Based Contactless Physiological Sensing (Accepted by IMWUT 2022, completed during ACSP 2021)
NkhukuProbe: Using a Sensor-Based Technology Probe to Support Poultry Farming Activities in Malawi (Best Paper at COMPASS 2022, completed during ACSP 2021)
Modeling the Noticeability of User-Avatar Movement Inconsistency for Sense of Body Ownership Intervention (Major revision by IMWUT 2022, completed during ACSP 2021)
Benefits
The ACSP offers a number of benefits and opportunities for participants, including:
- Highly impactful projects for health, accessibility, human-computer interaction, etc.
- Networking and connections for future collaborations.
- Lectures to develop graduate research skills like related work search, paper writing, and paper reviewing.
- Potential publications at top-tier conferences or journals (e.g., CHI, IMWUT, UIST).
- Potential career benefits such as reference letters, internships, and referrals to the GIX Dual Degree Program.
Qualifications
Applicants must be highly proficient in English to participate in this program. They must also currently be pursuing a degree at an accredited post-secondary academic institution in any of the following fields: computer science, electrical engineering, and/or industrial engineering. Prior research experience is desired but not required.
Visa and travel
Due to the COVID-19 pandemic, ACSP 2022 will be held remotely. We are unable to sponsor travel visas to the United States or China.
Topics and Projects
Please select the top 3 preferred projects in the application form from the following projects.
Easily-Accessible Health Sensing and Intervention
- A multimodal sensing method for continuous sleep health monitoring using edge-computing earphones.
- Required Skills: deep learning, signal processing, user study design
- Desired Skills: embedded system programming
- A novel multimodal sensing system to measure various signals from facial videos (e.g., physiological signal, head pose, face action, emotion, etc.).
- Required Skills: machine learning, signal processing
- Desired Skills: deep learning for computer vision
- A novel data augmentation method for robust camera-based physiological sensing (rPPG) in real-world settings.
- Required Skills: machine learning, signal processing
- Desired Skills: deep learning in computer vision
- Domain Adaptation in Longitudinal Behavior Modeling, or, Algorithm Fairness and Biases in Longitudinal Behavior Modeling
- Required Skills: deep learning (TensorFlow/PyTorch)
- Desired Skills: processing longitudinal passive sensing or mobile sensing data
- Just-in-Time Adaptive Intervention Techniques for Smartphone Overuse.
- Required Skills: Android development, reinforcement learning, behavior intervention design
- Desired Skills: longitudinal field experiments with actual users
- Central Venous Pressure (CVP) estimation using remote photo-respiratory signal detection.
- Required Skills: signal processing, app development
- Desired Skills: computer vision, data visualization, HCI and usability design
- Just-in-time Slouch Intervention: A DNN Approach To Posture Feedback
- Required Skills: Machine learning, basic embedded experience (arduino esc.), Python
- Desired Skills: Deep learning for video, signal processing
- Single Point Blood Pressure Measurement Using Commodity Earphones
- Required Skills: signal processing, Python
- Desired Skills: embedded system, acoustic sensing
Novel Interaction Technologies for Metaverse
- A multi-step adaptive user interface for Mixed Reality across physical environments.
- Required Skills: VR/AR application development, statistical analysis, and modeling
- Desired Skills: machine learning skills
- A novel technology to improve the experience of virtual meetings.
- Required Skills: VR development, user study design
- Desired Skills: machine learning
- Ultrasound earphone sensing for silent speech gestures.
- Required Skills: machine learning, signal processing,
- Desired Skills: deep learning, audio processing
- A novel localization technique to locate both the user and surrounding AIoT devices.
- Required Skills: embedded system programming, signal processing
- Desired Skills: AR/VR application development, machine learning
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Continuous finger-tip input for AR/VR
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Required Skills: Rapid prototyping (software), Signal processing
- Desired Skills: Machine learning, User experience
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Home-scale activity tracking using millimeter-wave phased array radar.
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Required Skills: AR app development, Signal processing
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Desired Skills: Machine learning, Radar signal processing, User experience
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Innovating HCI Paradigm in Human-Machine-Object Fusion Scenarios
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Required Skills: Information processing, mobile/PC application development
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Desired Skills: Interaction design
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Contact Us
If you have any questions, please send inquiries to either yuntaowang@tsinghua.edu.cn or yanyukanglwy@gmail.com with the tag [ACSP] in the subject line.