Chang-Hee Won

Profile Picture of Chang-Hee Won

Chang-Hee Won

  • College of Engineering

    • Electrical and Computer Engineering

      • Professor

Biography

Chang-hee (Andy) Won is a professor in the Department of Electrical and Computer Engineering and the director of Control, Sensor, Network, and Perception (CSNAP) Laboratory at Temple University. Previous to coming to academia, he worked at Electronics and Telecommunications Research Institute as a senior research engineer. Currently, he is actively guiding various research projects funded by the National Science Foundation, Pennsylvania Department of Health, and the Department of Defense. He published over 120 peer-reviewed articles and received multi-million dollars of research funding as a principal investigator from industry, state, and federal funding sources. He is a frequent reviewer for the National Science Foundation review panels and sits on National Institute of Health Biomedical Imaging Study Section. His research interests include tactile sensing, optimal control theory, spectral imaging, sensors, and dynamic sensing systems.

Labs: CSNAP

Research Interests

  • Tactile Sensors
  • Optimal Control Theory
  • Spectral Imaging
  • Dynamic Sensing

Courses Taught

Number

Name

Level

ECE 3412

Classical Control Systems

Undergraduate

ECE 5412

Control System Analysis

Graduate

ECE 8110

Special Topics in Electrical and Computer Engineering

Graduate

Selected Publications

Recent

  • Kim, C., Hwang, S., Park, E., Won, C., & Lee, J. (2021). Computer-aided diagnosis algorithm for classification of malignant melanoma using deep neural networks. Sensors, 21(16). doi: 10.3390/s21165551.

  • Won, C., Lee, J., & Saleheen, F. (2021). Tactile Sensing Systems for Tumor Characterization: A Review. IEEE Sensors Journal, 21(11), 12578-12588. doi: 10.1109/JSEN.2021.3078369.

  • Choi, S., Oleksyuk, V., Caroline, D., Pascarella, S., Kendzierski, R., & Won, C. (2020). Breast Tumor Malignancy Classification using Smartphone Compression-induced Sensing System and Deformation Index Ratio. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2020-July, 6082-6085. doi: 10.1109/EMBC44109.2020.9176636.

  • Saleheen, F. & Won, C. (2019). Statistical Stackelberg game control: Open-loop minimal cost variance case. Automatica, 101, 338-344. doi: 10.1016/j.automatica.2018.12.015.

  • Saleheen, F., Goldstein, J., Rajan, R., Caroline, D., Pascarella, S., & Won, C. (2018). Smartphone-based Compression-Induced Scope with Temperature Sensor for Inflammatory Breast Cancer Screening. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2018-July, 4969-4972. doi: 10.1109/EMBC.2018.8513437.

  • Zhang, S., Gu, Y., Won, C., & Zhang, Y. (2018). Dimension-reduced radio astronomical imaging based on sparse reconstruction. Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, 2018-July, 470-474. doi: 10.1109/SAM.2018.8448615.

  • Oleksyuk, V., Rajan, R., Saleheen, F., Caroline, D., Pascarella, S., & Won, C. (2018). Risk score based pre-screening of breast tumor using compression induced sensing system. IEEE Sensors Journal, 18(10), 4038-4045. doi: 10.1109/JSEN.2018.2817883.

  • Saleheen, F., Wang, Z., Picone, J., Butz, B., & Won, C. (2018). Efficacy of a virtual teaching assistant in an open laboratory environment for electric circuits. Advances in Engineering Education, 6(3), 1-27.

  • Saleheen, F., Oleksyuk, V., & Won, C. (2018). Itchy skin region detection using hyperspectral imaging. Proceedings of SPIE - The International Society for Optical Engineering, 10656. doi: 10.1117/12.2305147.

  • Won, C., Goldstein, J., Oleksyuk, V., Caroline, D., & Pascarella, S. (2017). Tumor size and elasticity estimation using Smartphone-based Compression-Induced scope. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 4106-4109. doi: 10.1109/EMBC.2017.8037759.

  • Oleksyuk, V., Saleheen, F., Caroline, D., Pascarella, S., & Won, C. (2017). Classification of breast masses using Tactile Imaging System and machine learning algorithms. 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings. doi: 10.1109/SPMB.2016.7846857.