Hong Man

• PhD (1999) Georgia Institute of Technology (Electrical Engineering)

• Institute Curriculum Committee Member
• Academic Operations and Affairs Committee Member
• ECE Faculty Council Chair
• ECE Student Well-being Comittee Member
• ECE Undergraduate Committee Member
• Teahing Professor Search Committee Chair
• Faculty Senate Member
• SES ABET preparation working group Member
• SES ABET preparation working group Member
• ECE Student Wellbeing Committee Member
• BOT Nominating and Corporate Governance Committee Member
• ECE Graduate Program Committee Member
• ECE Undergraduate Program Committee Chair
• Faculty Senate Member
• SES Undergraduate Curriculum Committee Member
• Lecturer recruitment committee Chair
• BOT Nominating and Corporate Governance Committee Member
• ECE Graduate Program Committee Member
• ECE Undergraduate Program Committee Chair
• Faculty Senate Member
• SES ABET preparation working group Member
• SES Undergraduate Curriculum Committee Member
• SES Undergraduate Curriculum Revision Working group Member
• CpE Undergraduate Program Committee Chair
• ECE Graduate Program Committee Member
• SES ABET preparation working group Member
• SES Undergraduate Curriculum Committee Member
• SES Undergraduate Curriculum Revision Working group Member
• ECE Faculty Search Committee Chair

• Journal of Multimedia Tools and Applications (Springer) Member of the Editorial Board
• NSF NSF Panelist
• NSF NSF Panelist
• NSF NSF Panelist
• IEEE North Jersey Advanced Communications Symposium • Member of organizing committee

• ACM Member
• ASEE Member
• IEEE Senior member

Conference Proceeding

1. Morcos, A.; Man, H.; Maguire, B.; West, A. (2023). Classification without gradients: multi-agent reinforcement learning approach to optimization. Proc. SPIE 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V. SPIE.
   https://doi.org/10.1117/12.2664025..
2. Morcos, A.; Man, H.; West, A.; Maguire, B. (2022). Learning without Gradients: Multi-Agent Reinforcement Learning approach to optimization. Proc. SPIE 12276, Artificial Intelligence and Machine Learning in Defense Applications IV. SPIE.
   https://doi.org/10.1117/12.2636231.
3. Dai, S.; Man, H. (2022). Deep Latent Similarity Model for Online Data Categorization. Proc. the 18th Int. Conference on Data Science . Springer.
4. Man, H.; Dai, S.; Lawtence, V.; LaPeruta, T.; Hohil, M. (2021). Unsupervised Multi-view Object Proposal Ranking. Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III. SPIE Defense + Commercial Sensing (vol. 11746). Virtual: SPIE.
   http://dx.doi.org/10.1117/12.2587810.
5. Dai, S.; Su, P.; Man, H. (2020). Deep Similarity Metric Clustering. The 16th Int. Conference on Data Science (DATA’20). Las Vegas, NV: Springer.
6. Dai, S.; Man, H. (2019). Unsupervised Object Discovery and Inference with Deep Latent Similarity Model. Las Vegas, NV: The 23rd Int'l Conf on Image Processing, Computer Vision, & Pattern Recognition (IPCV’19), .
7. Dai, S.; Man, H. (2018). Integrating Visual and Textual Affective Descriptors for Sentiment Analysis of Social Media Posts. 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) (pp. 13--18).
8. Dai, S.; Su, P.; Man, H. (2018). Object discovery and localization via structural contrast. 2018 25th IEEE International Conference on Image Processing (ICIP) (pp. 2760--2764).
9. Dai, S.; Su, P.; Man, H. (2018). Unsupervised Object Discovery And Localization Via Structural Discrimination. Athens, Greece: IEEE International Conference on Image Processing (ICIP 2018), .
10. Dai, S.; Man, H. (2017). A convolutional Riemannian texture model with differential entropic active contours for unsupervised pest detection. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1028--1032).
11. Dai, S.; Man, H. (2017). A statistic manifold kernel with graph embedding discriminant analysis for action and expression recognition. 2017 IEEE International Conference on Image Processing (ICIP) (pp. 1792--1796).
12. Tang, B.; Xu, J.; He, H.; Man, H. (2017). ADL: Active dictionary learning for sparse representation. 2017 International Joint Conference on Neural Networks (IJCNN) (pp. 2723--2729).
13. Dai, S.; Man, H.; Zhan, S. (2016). A Bregman divergence based Level Set Evolution for efficient medical image segmentation. 2016 23rd International Conference on Pattern Recognition (ICPR) (pp. 1113--1118).
14. Dai, S.; Xu, X.; Jiang, B.; Man, H. (2016). Multi-scale sentiment classification using canonical correlation analysis on riemannian manifolds. 2016 IEEE International Symposium on Multimedia (ISM) (pp. 144--147).
15. Xu, X.; Man, H. (2015). Interpreting sports tactic based on latent context-free grammar. 2015 IEEE International Conference on Image Processing (ICIP) (pp. 4072--4076).
16. Dai, S.; Man, H.; Zhan, S. (2015). Minimum mutual information based level set clustering algorithm for fast mri tissue segmentation. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 3057--3060).
17. Dai, S.; Man, H. (2015). Statistical Adaptive Metric Learning for Action Feature Set Recognition in the Wild. International Symposium on Visual Computing (pp. 657--667).

Journal Article

1. Zeng, Y.; Wang, Y.; Liao, D.; Li, G.; Huang, W.; Xu, J.; Cao, D.; Man, H. (2022). Keyword-Based Diverse Image Retrieval with Variational Multiple Instance Graph. IEEE Transactions on Neural Networks and Learning Systems (doi: 10.1109/TNNLS.2022.3168431 ed.).
2. Dai, S.; Man, H. (2017). Mixture statistic metric learning for robust human action and expression recognition. IEEE Transactions on Circuits and Systems for Video Technology (10 ed., vol. 28, pp. 2484--2499). IEEE.
3. Cui, C.; Man, H.; Wang, Y.; Liu, S. (2016). Optimal cooperative spectrum aware opportunistic routing in cognitive radio ad hoc networks. Wireless Personal Communications (1 ed., vol. 91, pp. 101--118). Springer US.
4. Xu, J.; Tang, B.; He, H.; Man, H. (2016). Semisupervised feature selection based on relevance and redundancy criteria. IEEE transactions on neural networks and learning systems (9 ed., vol. 28, pp. 1974--1984). IEEE.
5. Dai, S.; Man, H. (2016). Statistical adaptive metric learning in visual action feature set recognition. Image and Vision Computing (vol. 55, pp. 138--148). Elsevier.