My research interests are:

• Human activity recognition using wearable devices
• Information Security
• Natural Language Processing

• Ph.D, Information Science, Posts and Telecoms Institute of Technology, 2017.
• Ms.C, Ubiquitous Computing, Kyung Hee University, 2008.
• B.Sc, Electronics and Telecommunications Engineering , Posts and Telecoms Institute of Technology, 2003.
• High school student, Trần Phú High School for the Gifted, Hai Phong, 1998

• Awarded Korean Research Foundation (KRF) Scholarship (Sep 2006 - August 2007)
• Received “Student Science Research Fellowship Award” from Posts and Telecommunications Institute of Technology in 2000
• Won the first prize in the Nationwide Olympic Contest on Informatics for students in 1999.
• Won the third prize in Nationwide Informatics Contest for High School students in 1998.

• From 2013: Lecturer at PTIT
• 2009-2012: Project Manager at CTIN
• Fom 2008-2009: Researcher and developer at NNode, Korea
• From 2003-2005: Researcher at CDIT

Journal Articles

• Pham, C., Diep, N. N., & Phuong, T. M. (2013). A Wearable Sensor based Approach to Real-Time Fall Detection and Fine-Grained Activity Recognition. J. Mobile Multimedia, 9(1&2), 15-26.

Conference Papers

2019

• Nguyen Ngoc Diep, Nguyen Van Tien, Nguyen Hoang Anh, Tu Minh Phuong, “An Unsupervised Method for Web User Interest Analysis”, The 6th NAFOSTED Conference on Information and Computer Science (NICS), Hanoi, Vietnam, 2019.

2018

• Phuong, T. M., & Diep, N. N. (2018, November). Speeding Up Convolutional Object Detection for Traffic Surveillance Videos. In 2018 10th International Conference on Knowledge and Systems Engineering (KSE) (pp. 13-18). IEEE.

2017

• Pham, C., Diep, N. N., & Phuong, T. M. (2017, October). e-Shoes: Smart shoes for unobtrusive human activity recognition. In 2017 9th International Conference on Knowledge and Systems Engineering (KSE) (pp. 269-274). IEEE.

2016

• Diep, N. N., Pham, C., & Phuong, T. M. (2016, August). Motion primitive forests for human activity recognition using wearable sensors. In Pacific Rim International Conference on Artificial Intelligence (pp. 340-353). Springer, Cham.
• Diep, N. N., Pham, C., & Phuong, T. M. (2016, August). An orientation histogram based approach for fall detection using wearable sensors. In Pacific Rim International Conference on Artificial Intelligence (pp. 354-366). Springer, Cham.

Before 2015

• Diep, N. N., Pham, C., & Phuong, T. M. (2015). SigVer3D: accelerometer based verification of 3-D signatures on mobile devices. In Knowledge and Systems Engineering (pp. 353-365). Springer, Cham.
• Diep, N. N., Pham, C., & Phuong, T. M. (2014, December). A classifier based approach to real-time fall detection using low-cost wearable sensors. In Proceedings of the Fifth Symposium on Information and Communication Technology (pp. 14-20). ACM.
• Diep, N. N., Hung, L. X., Zhung, Y., Lee, S., Lee, Y. K., & Lee, H. (2007, February). Enforcing access control using risk assessment. In Fourth European Conference on Universal Multiservice Networks (ECUMN'07) (pp. 419-424). IEEE.
• Diep, N. N., Lee, S., Lee, Y. K., & Lee, H. (2007). Contextual Risk-Based Access Control. Security and Management, 2007, 406-412.
• Diep, N. N., Lee, S., Lee, Y. K., & Lee, H. (2007, August). A privacy preserving access control scheme using anonymous identification for ubiquitous environments. In 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007) (pp. 482-487). IEEE.