Hong Man (hman)

Hong Man

Professor

Charles V. Schaefer, Jr. School of Engineering and Science

Department of Electrical and Computer Engineering

Burchard 201
(201) 216-8246

Education

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

Research

Computer perception: texture and edge features, feature selection, semantic segmentation
Visual understanding: object detection, localization, recognition and tracking, action recognition, face and gesture recognition, emotion and sentiment analysis
Joint textual and visual analysis: image to phrases, textual features, sentiment analysis in social media
Medical imaging: robust segmentation, fMRI brain activation detection, EEG and EKG time series analysis, tomographic imaging

Institutional Service

  • Academic Operations and Affairs Committee Member
  • ECE Faculty Council Chair
  • ECE Student Well-being Comittee Member
  • ECE Undergraduate Committee Member
  • Institute Curriculum Committee Chair
  • 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

Professional Service

  • Journal of Multimedia Tools and Applications (Springer) Section Editor
  • International Conference on Pattern Recognition (ICPR) 2024 Meta-Reviewer
  • 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

Professional Societies

  • ACM Member
  • ASEE Member
  • IEEE Senior member

Selected Publications

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.; Xu, J.; Xu, X.; Liu, B.; Man, H. (2023). Contrastive Topic-Enhanced Network for Video Captioning. Expert Systems With Applications. Elsevier.
  2. Tang, X.; Liao, D.; Zhu, L.; Shen, M.; Huang, S.; Li, G.; Man, H.; Xu, J. (2023). Confidence-aware Sentiment Quantification via Sentiment Perturbation Modeling. IEEE Transactions on Affective Computing. IEEE.
  3. 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.).
  4. 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.
  5. 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.
  6. 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.
  7. 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.