Mia Y. Wang
Assistant Professor
Education
PhD Technology, Purdue University
MS Computer and Information Technology, Purdue University
BA Music Performance, Tongji University, China
Research Interest
My research aims to utilize machine learning and audio technologies to develop an intelligent, accurate, and efficient detection and classification system for Unmanned Aerial Vehicles (UAVs). A crucial component of my research is the collection and creation of a UAV audio dataset, which serves as a unique audio fingerprint for UAVs from different manufacturers and models. This dataset will be used to train machine learning or deep learning models specifically designed for UAV detection and classification. Unlike other methods such as computer vision, radar, or radio frequency, the audio solution I have chosen offers cost efficiency, accuracy, and resilience to weather and lighting conditions. Audio detection can be performed reliably during various weather conditions and at different times of the day. Previous and ongoing experiments have shown outstanding detection and classification accuracy compared to other proposed methods in related research. Looking ahead, my career goal is to combine my passion for classical music with computer science to drive innovation and application advancements in both fields. By integrating these disciplines, I aim to explore new opportunities for growth and contribute to the advancement of both classical music and computer science.
Courses Taught
CSCI 220 - Programming I
CSCI 230 - Data Structures and Algorithms
Selected Publications
Jung, Heesun, Bokyung Kwon, Youngbin Kim, Yejin Lee, Jihyeon Park, Griffin Pegg, Yaqin Mia Wang, and Anthony H. Smith. A Deep Learning-Based Coyote Detection System Using Audio Data. In 2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), pp. 170-175. IEEE, 2023.
Yaqin Wang, Jin Wei-Kocsis, John A Springer, and Eric T Matson. Deep Learning in Audio Classification. In: Lopata, A., Gudonien ̇e, D., Butkien ̇e, R. (eds) Information and Software Technologies. ICIST 2022. Communications in Computer and Information Science, vol 1665. Springer, Cham.
Yaqin Wang, Zhiwei Chu, Ilmun Ku, E. Cho Smith, and Eric T. Matson. A Large-Scale UAV Audio Dataset and Audio-Based UAV Classification Using CNN. In 2022 Sixth IEEE International Conference on Robotic Computing (IRC), pp. 186-189. IEEE, 2022.
Yaqin Wang, Jin Wei-Kocsis, John A. Springer, and Eric T. Matson. Deep learning in audio classification. In International Conference on Information and Software Technologies, pp. 64-77. Cham: Springer International Publishing, 2022.
Juann Kim, Dongwhan Lee, Youngseo Kim, Heeyeon Shin, Yeeun Heo, Yaqin Wang, and Eric T. Matson. Deep Learning Based Malicious Drone Detection Using Acoustic and Image Data. In 2022 Sixth IEEE International Conference on Robotic Computing (IRC), pp. 91-92. IEEE, 2022.
Ilmun Ku, Seungyeon Roh, Gyeongyeong Kim, Charles Taylor, Yaqin Wang, and Eric T. Matson. UAV Payload Detection Using Deep Learning and Data Augmentation. In 2022 Sixth IEEE International Conference on Robotic Computing (IRC), pp. 18-25. IEEE, 2022.