Scholar
Duo Lu
Google Scholar ID: Q8loe9kAAAAJ
Rider University
Citations & Impact
Citations
568
H-index
13
i10-index
16
Publications
20
Co-authors
19
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published multiple papers and patents, including:
- - "Systems and Methods for a Multifactor User Identification and Authentication Framework for In-Air-Handwriting with Hand Geometry and Deep Hashing" (US Patent Appl. 16/781,596, 2020)
- - "Three-Dimensional In-The-Air Finger Motion based User Login Framework for Gesture Interface" (US Patent #10877568, 2020)
- - "FMHash: Deep Hashing of In-Air-Handwriting for User Identification" (International Conference on Communications, ICC 2019)
- - "FMCode: A 3D In-the-Air Finger Motion Based User Login Framework for Gesture Interface" (arXiv:1808.00130, 2018)
- - "Multifactor User Authentication with In-Air-Handwriting and Hand Geometry" (The 11th IAPR International Conference on Biometrics, ICB 2018)
- - "A Data Driven In-Air-Handwriting Biometric Authentication System" (International Joint Conference on Biometrics, IJCB 2017)
Research Experience
- Currently working at Rider University, the main research focus is understanding in-air-handwriting and using it as an input method, particularly in Virtual Reality (VR) and Augmented Reality (AR) applications. The current research emphasis is on pattern recognition using deep neural networks on in-air-handwriting movement data collected by the Leap Motion controller and a custom data glove. This project is sponsored by advisor Dr. Dijiang Huang.
Background
- Research interests include building smart IoT systems, smart robots, and smart wearable devices, proficient in software development using C/C++, Java, and Python on Linux.
Miscellany
- Besides research projects, also builds mobile robot vehicles and writes software to drive them with a certain level of autonomy.
