I'm currently a DPhil (Ph.D.) student at the Department of Computer Science, University of Oxford and work with Prof. Tam Vu at Mobile and Networked Systems (MNS) Lab. I completed my B.E. degree in Computer Engineering from Vietnam National University - University of Technology (HCMUT) in 2015 and was awarded Silver Medal for the best student of the Honor Program in Computer Engineering. I received my M.S. degree in Computer Science from Korea Advanced Institute of Science and Technology (KAIST) in 2018 with my research on Multiple-hop Cognitive Radio Networks. My current research interests include Mobile Healthcare Systems, Embedded Operating Systems, and Cyber-Physical Systems.
Detection of Microsleep Events with a Behind-the-ear Wearable System. IEEE TMC - IEEE Transactions on Mobile Computing (IF: 5.577, preprint). Nhat Pham, Tuan Dinh, Taeho Kim, Zohreh Raghebi, Nam Bui, Hoang Truong, Tuan Nguyen, Farnoush Banaei-Kashani, Ann Halbower, Thang Dinh, Phuc Nguyen, and Tam Vu.
DroneScale: Drone Load Estimation Via Remote Passive RF Sensing. SenSys 2020 - The 18th ACM Intl' Conf. on Embedded Networked Sensor Systems.
Phuc Nguyen, Vimal Kakaraparthi, Nam Bui, Nikshep Umamahesh, Nhat Pham, Hoang Truong, Yeswanth Guddeti, Dinesh Bharadia, Eric Frew, Richard Han, Daniel Massey, Tam Vu.
(44 out of 213 submissions, acceptance ratio: 20.7%)
WAKE: A Behind-the-ear Wearable System for Microsleep Detection.[Slides][Video] MobiSys 2020 - The 18th ACM Intl' Conf. on Mobile Systems, Applications, and Services. Nhat Pham, Tuan Dinh, Zohreh Raghebi, Taeho Kim, Nam Bui, Phuc Nguyen, Hoang Truong, Farnoush Banaei-Kashani, Ann Halbower, Thang Dinh, and Tam Vu.
(34 out of 175 submissions, acceptance ratio: 19.4%)
Painometry: Wearable and Objective Quantification System for Acute Postoperative Pain.[Video] MobiSys 2020 - The 18th ACM Intl' Conf. on Mobile Systems, Applications, and Services.
H. Truong, N. Bui, Z. Raghebi, M. Ceko, N. Pham, P. Nguyen, A. Nguyen, T. Kim, K. Siegfried, E. Stene, T. Tvrdy, L. Weinman, T. Payne, D. Burke, T. Dinh, S. D'Mello, F. Banaei-Kashani, T. Wager, P. Goldstein, and T. Vu.
(34 out of 175 submissions, acceptance ratio: 19.4%)
Oliot-OpenCity: Open Standard Interoperable Smart City Platform. ISC2 2018 - IEEE International Smart Cities Conference, Kansas City, Missouri, USA, Sep. 2018.
Yalew k. Tolcha, Hoang Minh Nguyen, Jawook Byun, Kiwoong Kwon, Jiyong Han, Wondeuk Yoon, Nakyung Lee, Hyunseob Kim, Nhat Pham, and Daeyoung Kim.
WAKE - A Behind-the-ear Wearable System for Microsleep Detection
WAKE is a novel wearable device that can detects microsleep by monitoring biosignals from the brain, eye movements, facial muscle contractions, and sweat gland activities from behind the user’s ears. To ensure reliablity of WAKE in the real-world, we introduce a Three-fold Cascaded Amplifying (3CA) technique to tame the motion artifacts and environmental noises for capturing high fidelity signals.
Painometry - Wearable and objective quantification system for acute postoperative pain
Painometry is wearable system for objective quantification of users’ pain perception based on multiple physiological signals and facial expressions. The light-weight form factor and a minimal number of sensors enable the mobility of Painometry and its capability as a wearable and daily device.
Earable Computing - An Ear-Worn Biosignal Sensing Platform
Earable is a novel ear-worn biosensing platform for cognitive state quantification and human-computer interaction. Earable can capture biosignal including brain waves activities, eyes movements, and facial muscle contractions from the back of the ears. Its form-factor is also convenient to use in everyday life. The demo shows two use cases for our Earable platform. First, our system plays relaxing music and dims the light when the user is trying to relax or sleep by detecting alpha and beta waves generated by the brain. Second, our system controls a drone with eye movements and facial muscle activity.
eBP - Blood Pressure Measurement from inside the ear
In this work, we propose a device called eBP to measure blood pressure from inside the user’s ear aiming to minimize the measurement’s impact on users’ normal activities while maximizing its comfort level. eBP has 3 key components: (1) a light-based pulse sensor attached on an in"atable pipe that goes inside the ear, (2) a digital air pump with a fine controller, and (3) a blood pressure estimation algorithm. In contrast to existing devices, eBP introduces a novel technique that eliminates the need to block the blood flow inside the ear, which alleviates the user’s discomfort.
Experience
Research Experience
Aug. 2018 - Aug. 2020: Research Assistant, Mobile and Networked Systems Lab, University of Colorado Boulder, USA.
Mar. 2018 - Jul. 2018: Researcher, Real-time and embedded systems lab (RESL), KAIST, South Korea.
Teaching Experience
Hilary & Trinity 2021: Digital Systems, University of Oxford, UK.
Hilary 2021: Concurrent Programming, University of Oxford, UK.
Michaelmas 2020: Linear Algebra, University of Oxford, UK.
Fall 2015: Data and computer communication, Ho Chi Minh City University of Technology, Vietnam.
Spring 2015: Embedded systems, Ho Chi Minh City University of Technology, Vietnam.
Work Experience
Mar. 2015 - Jul. 2015: Embedded Software Engineer, FPT Software, Ho Chi Minh city, Vietnam.
Jul. 2014 - Sept. 2015: Embedded Software Intern, Applied Micro Circuits Corporation, Ho Chi Minh city, Vietnam.
