Xin Liu

I am a 3rd Ph.D. student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington – Seattle. I am advised by Shwetak Patel at UW and Daniel McDuff at Microsoft Research.

Before joining UW, I obtained my bachelor’s degree in computer science from the University of Massachusetts Amherst in 2018, where my advisor was Sunghoon Ivan Lee.  While at UMass Amherst, I received a 21st Century Leaders Award, Rising Researcher Award, and Outstanding Undergraduate Achievement Award. 

My research interests lie in the intersection of on-device machine learning, sensing and healthcare — bringing machine learning to edge and mobile devices to advance the state-of-the-art healthcare 🙂 

Contact: xliu0 at cs dot washington dot edu

!! Check out our Microsoft Research Webinar about non-contact health sensing!

[10]Xin Liu, Yuang Li, Josh Fromm, Yuntao Wang, Ziheng Jiang, Alex Mariakakis, Shwetak Patel , “SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices”, ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/Ubicomp 2021)

[9] Xuhai Xu, Jiahao Li, Tianyi Yuan, Liang He, Xin Liu, Yukang Yan, Yuntao Wang, Yuanchun Shi, Jennifer Mankoff, Anind K Dey, “HulaMove: Using Commodity IMU for Waist Interaction”, ACM CHI Conference on Human Factors in Computing Systems (CHI 2021)

[8] Kathrin Zürcher et al., “Novel approach to estimate tuberculosis transmission in primary care clinics in sub-Saharan Africa: protocol of a prospective study”, BMJ Open, 2020.

[7] Daniel McDuff, Javier Hernandez, Erroll Wood, Xin Liu, Tadas Baltrusaitis, “Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars”, Preprint, PDF

[6] Xin Liu, Ziheng Jiang, Josh Fromm, Xuhai Xu, Shwetak Patel, Daniel McDuff, “MetaPhys: Unsupervised Few-Shot Adaptation for Non-Contact Physiological Measurement”, Preprint, PDF

[5] Xin Liu, Josh Fromm, Shwetak Patel, Daniel McDuff, “Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement”, To Appear in  Conference on Neural Information Processing Systems (NeurIPS 2020), PDF , CODE   (Oral, Top 1%,  105 out of 9454 Submissions)

[Microsoft Research Webinar], [Microsoft Research Blog], [NEWS]

[4] Young Lee, Xin Liu, Jeremy Gummeson, Sunghoon Ivan Lee, “A Wearable RFID System to Monitor Hand Use for Individuals with Upper Limb Paresis,” IEEE International Conference on Biomedical and Health Informatics (IEEE BHI’19). PDF

[3] Sunghoon Ivan Lee, Xin Liu, Smita Rajan, Nathan Ramasarma, Eun Kyoung Choe, Paolo Bonato, “A Novel Upper-Limb Function Measure Derived from Finger-Worn Sensor Data Collected in a Free-Living Setting”, PLoS One Journal.  PDF

[2] Xin Liu, Smita Rajan, Nathan Ramasarma, Paolo Bonato, Sunghoon Ivan Lee, ”Finger-Worn Sensors for Accurate Functional Assessment of the Upper Limbs in Real-World Settings,” in IEEE Engineering in Medicine and Biology Conference (EMBC 2018). PDF. 

[1] Xin Liu, Smita Rajan, Nathan Ramasarma, Paolo Bonato, Sunghoon Ivan Lee, “The Use of A Finger-Worn Accelerometer for Monitoring of Hand Use in Ambulatory Settings,” IEEE Journal of Biomedical and Health Informatics (J-BHI) – VOL. 23, NO. 2, 2019. PDF. (Cover Article Nominee)

Summer 2021 – Research Intern @ Microsoft Research

Topic TBD

Nov 2020 – June 2021 – Part-time MLSys Research Intern @ OctoML (TVM)

Accelerating Pre/Post processing for On-Device ML

Summer 2019 – Research Intern @ Allen Institute for Artificial Intelligence (AI2)

Developing Efficient Deep Neural Networks to Detect Blood Vessels in Portable Ultrasound Devices

During my undergraduate studies, I spent a huge amount of effort to push the international community to engage various leadership experiences at the university.  I was the first international peer mentor in the residential life office and the first international student consultant in the department of information and technology. I worked in six different departments during my undergrd years :p

I am also a big fan of NBA 🙂