Biography

David Han is the inaugural holder of the Bruce Eisenstein Endowed Chair. He is an ASME Fellow and an IEEE senior member. He has previously held positions as a research and faculty member at the Johns Hopkins University Applied Physics Laboratory, Army Research Laboratory, and the University of Maryland at College Park, and has additionally served as Distinguished IWS Chair Professor at the US Naval Academy. He spent over 11 years as a program officer at the Office of Naval Research and served as its Deputy Director of Research, overseeing the Discovery and Invention portfolio of over $900 million from 2012 to 2014. He also served as Associate Director for Basic Research in Machine Intelligence and Robotics in the Office of the Assistant Secretary of Defense Research & Engineering from 2014 to 2016, helping to oversee an over $2 billion annual research portfolio. Han has authored or coauthored over 100 peer-reviewed papers, including four book chapters.

Degrees / Education

• PhD, Mechanical Engineering, Johns Hopkins University
• MSE, Mechanical Engineering, Johns Hopkins University
• BS, Mechanical Engineering, Carnegie-Mellon University

Research Interests

Select Publications

• D. Kim, S. Park, D. K. HAN, H. Ko, "Multi-band CNN Architecture Using Adaptive Frequency Filter For Acoustic Event Classification," Applied Acoustics, 2020.
• S. Park, M. Elhilali, D. K. HAN, H. Ko, "Amphibian Sounds Generating Network based on Adversarial Learning," IEEE Signal Processing Letters, Vol. 27, Issue 1, pp. 640-644, December, 2020.
• J. Park, D. K. HAN, and H. Ko, "Fusion of Heterogeneous Adversarial Networks for Single Image Dehazing," IEEE Transactions on Image Processing, Vol.29, No.1, pp.4721-4732, Dec. 2020.
• C. Kao, S. Park, A. Badi, D. K.HAN, H. Ko, "Orthogonal Gradient Penalty for Fast Training of Wasserstein GAN based Multi-task Autoencoder toward Robust Speech Recognition," IEICE TRANSACTIONS on Information and Systems, Vol. E103-135, January 2020.
• A. Badi, S. Park, D. K. HAN, H. Ko, "Correlation Distance Skip Connection Denoising Autoencoder (CDSK_DAE) for Speech Feature Enhancement ," Journal of Applied Acoustics, Vol. 163, pp. 107213, June 2020.
• Y. Lee, J. Min, D. K. HAN, H. Ko, “Spectro-Temporal Attention-Based Voice Activity Detection,” IEEE Signal Processing Letters, Vol. 27, Issue 1, Jan. 2020.
• D. Kim, D. K. HAN, H. Ko, “Dual Stage Learning Based Dynamic Time-Frequency Mask Generation for Audio Event Classification,” Interspeech 2020, Shanghai, China, 25-29 Oct 2020 (accepted)
• J. G. Kwak, D. K. HAN, H. Ko, “CAFE-GAN: Arbitrary Editing with Complementary Attention Feature,” European Conference on Computer Vision (ECCV) 2020, Glasgow, UK, 23 – 28 Oct 2020
• L. Zhang, T. Wen, J. Min, J. Wang, D. K. HAN, J. Shi, “Learning Object Placement by Inpainting for Compositional Data Augmentation,” European Conference on Computer Vision (ECCV) 2020, Glasgow, UK, 23 – 28 Oct 2020
• S. Eum, D. K. HAN, “SomethingFinder: Localizing Undefined Regions Using Referring Expressions,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Seattle, USA, 14 – 19 June, 2020
• G. Kim, J. Park, K. Lee, J. Lee, J. Min, B. Lee, D. K. HAN, H. Ko, “Unsupervised Real-World Super Resolution With Cycle Generative Adversarial Network and Domain Discriminator,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Seattle, USA, 14 – 19 June, 2020
• J. Lee, J. Park, K. Lee, J. Min, G. Kim, B. Lee, D. K. HAN, H. Ko, “FBRNN: Feedback Recurrent Neural Network for Extreme Image Super-Resolution,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Seattle, USA, 14 – 19 June, 2020