[S&P'25] J.-W. Chang, K. Sun, X. Zhang, F. Koushanfar, "EveGuard: Speech Privacy Protection against Side-Channel Eavesdropping Attacks," IEEE Symposium on Security and Privacy (S&P), May 2025
[NDSS'25] J.-W. Chang, K. Sun, N. Heydaribeni, S. Hidano, X. Zhang, F. Koushanfar, "Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systems," Network and Distributed System Security (NDSS) Symposium, Feb. 2025.
[NDSS'23] J.-W. Chang, M. Javaheripi, S. Hidano, F. Koushanfar, "RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression," Network and Distributed System Security (NDSS) Symposium, Feb. 2023. Slides Demo Video
[DAC'23] J.-W. Chang, M. Javaheripi, F. Koushanfar, "VideoFlip: Adversarial Bit-Flips for Reducing Video Service Quality," Proceedings of the 60th ACM/IEEE Design Automation Conference (DAC), July 2023.
[ICLR Workshop'23] J.-W. Chang, N. Sheybani, S. Hussain, M. Javaheripi, S. Hidano, F. Koushanfar, "NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression," ICLR 2023 Workshop on Machine Learning for Internet of Things(IoT): Datasets, Perception, and Understanding, May 2023.
[IEEE Sensors'22] S.-H. Ahn*, J.-W. Chang*, H.-S. Yoon, and S.-J. Kang, "TouchNAS: Efficient Touch Detection Model Design Methodology for Resource-Constrained Devices," IEEE Sensors Journal, 2022.
[ACM JETC'22] M. Javaheripi, J.-W. Chang, F. Koushanfar, "AccHASHTAG: Accelerated Hashing for Detecting Fault-Injection Attacks on Embedded Neural Networks," ACM Journal on Emerging Technologies in Computing Systems (JETC), 2022.
[TCSVT’20] J.-W. Chang, K.-W. Kang, and S.-J. Kang, "An Energy-Efficient FPGA-based Deconvolutional Neural Networks Architecture for Single Image Super-Resolution," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
[ICIP'20] S.-H. Ahn, J.-W. Chang, and S.-J. Kang, "An Efficient Accelerator Design Methodology for Deformable Convolutional Networks," IEEE international conference on image processing (ICIP), Oct. 2020.
[ASP-DAC’20] J.-W. Chang*, S.-H. Ahn*, K.-W. Kang and S.-J. Kang, "Towards Design Methodology of Efficient Fast Algorithms for Accelerating Generative Adversarial Networks on FPGAs," IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2020. (Best Paper Candidate)
[DATE’19] J.-W. Chang, K.-W. Kang, and S.-J Kang, "SDCNN: An efficient sparse deconvolutional neural network accelerator on FPGA," IEEE/ACM Design Automation and Test in Europe Conference (DATE), March. 2019.
[ASP-DAC’18] J.-W. Chang and S.-J. Kang, "Optimizing FPGA-based convolutional neural networks accelerator for image super-resolution," IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2018.
[JSTS'18] J.-W. Chang and S.-J. Kang, "Real-time vehicle detection and tracking algorithm for forward vehicle collision warning," JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE, 2018.