Hsing-Kuo Kenneth Pao

Professor
Department of Computer Science and Information Engineering
National Taiwan University of Science & Technology.

No. 43 Keelung Rd, Section 4, Taipei 106, Taiwan
        Email: pao -at- mail.ntust.edu.tw 
        Phone: +886-2-27301065 
        Fax: +886-2-27301081 

B.S. in Mathematics, National Taiwan University
M.S. & Ph.D. in Computer Science, New York University.

Teaching

Research Area

Publications

Journal Paper

Hanjuan Huang, Hsing-Kuo Pao.
"Interpretable deep model pruning",
Neurocomputing, 130485, 2025. (to appear)

Mohammad Iqbal, Tsamara Rana Nugraha, and Hsing-Kuo Pao.
"Active Grade Estimator on Short Answer Assessment",
2025. (to appear)

Hanjuan Huang, Hsing-Kuo Pao.
"A unified noise and watermark removal from information bottleneck-based modeling",
Neural Networks, 181: 106853, 2025.

Zolnamar Dorjsembe, Hsing-Kuo Pao, Sodtavilan Odonchimed, Furen Xiao.
"Conditional Diffusion Models for Semantic 3D Brain MRI Synthesis",
IEEE J. Biomed. Health Informatics 28(7), 4084-4093, 2024.

Vahid Golderzahi, Hsing-Kuo Kenneth Pao
"Revenue forecasting in smart retail based on customer clustering analysis",
Internet of Things, 27: 101286, 2024.

Mohammad Iqbal, Adila Sekarrati Dwi Prayitno, Hsing-Kuo Pao, Imam Mukhlash
"Mining fuzzy local periodic activity pattern for Smart home applications",
Knowl. Based Syst, 293: 111629, 2024.

Mohammad Iqbal, Hsing-Kuo Pao.
"Mining non-redundant distinguishing subsequence for trip destination forecasting",
Knowledge-Based Systems, Vol. 211: 106519, Jan., 2021. [SCI]

Hsing-Kuo Pao, Fong-Ruei Lee, Yuh-Jye Lee.
"Dealing with Interleaved Event Inputs for Intrusion Detection",
Journal of Information Science and Engineering, Vol. 35: pp. 223-242, Jan. 2019. MOST 106-2221-E-011-159. [SCI]

Hsing-Kuo Pao, Alexander Chen, and Jiunn-Chia Huang.
"Road Traffic Forecasting with Unknown Multiple Periodicities and Complex Patterns",
IEEE Transactions on Intelligent Transportation Systems, (accepted) [SCI]

Chih-Hung Lin, Hsing-Kuo Pao and Jian-Wei Liao.
"Efficient Dynamic Malware Analysis Using Virtual Time Control Mechanics",
Computers and Security, (to appear) [SCI]

Rudy Cahyadi Hario Pribadi and Hsing-Kuo Pao.
"Sparse Tree Structured Representation for Re-identification",
Pattern Recognition, Vol. 60: pp. 394-404, 2016 [SCI]

Hsing-Kuo Pao, Yuh-Jye Lee, and Chun-Ying Huang.
"Statistical Learning Methods for Information Security: Fundamentals and Case Studies",
Applied Stochastic Models in Business and Industry, Vol. 31(2): pp. 97-113, 2015 [SCI]

Kai-Lung Hua, Ge-Ming Chiu, Hsing-Kuo Pao, and Yi-Chi Cheng.
"An Efficient Scheduling Algorithm for Scalable Video Streaming over P2P networks",
Computer Networks, Vol. 57(14): pp. 2856-2868, 2013. [SCI]

Hsing-Kuo Pao, Junaidillah Fadlil, Hong-Yi Lin, and Kuan-Ta Chen.
"Trajectory Analysis for User Verification and Recognition",
Knowledge-Based Systems, Vol. 34: pp. 81-90, 2012. [SCI]

Chien-Chung Chang, Hsing-Kuo Pao, and Yuh-Jye Lee.
"An RSVM Based Two-teachers-one-student Semi-supervised Learning Algorithm",
Neural Networks, Vol. 25: pp. 57-69, Jan., 2012. [SCI]

Hsing-Kuo Pao, Ching-Hao Mao, Hahn-Ming Lee, Chi-Dong Chen, and Christos Faloutsos.
"An Intrinsic Graphical Signature Based on Alert Correlation Analysis for Intrusion Detection",
Journal of Information Science and Engineering, Vol. 28, no. 2: pp. 243-262, March, 2012. [SCI]

Hsing-Kuo Pao, Kuan-Ta Chen, and Hong-Cheng Chang
"Game Bot Detection via Avatar Trajectories Analysis",
IEEE Transactions on Computational Intelligence and AI in Games, Vol. 2, no. 3, Sep. 2010.

Nava Rubin, Hsing-Kuo Pao, and Davi Geiger
"How do Convexity and Size Affect Figure/Ground Resolution? Theory and Experiments",
Investigative Ophthalmology and Visual Science, Vol. 41, no. 4: 2330B576 Suppl. S Mar 15 2000. [SCI]

Conference Paper

Dorjsembe, Zolnamar, Hsing-Kuo Pao, and Furen Xiao.
"Polyp-ddpm: Diffusion-based semantic polyp synthesis for enhanced segmentation",
2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2024.

Chen, Chia-Cheng, and Hsing-Kuo Pao.
"Reconsider Time Series Analysis for Insider Threat Detection",
2024 IEEE International Conference on Big Data (BigData), IEEE, 2024.

Yueh-Lin Chung and Hsing-Kuo Pao.
"Density-Based Prototypical Contrastive Learning on Visual Representations",
IEEE BigData, Dec. 2023.

Huang Hanjuan, Peng Hsuan-Ting, and Hsing-Kuo Pao.
"Fake News Detection via Sentiment Neutralization",
IEEE BigData, 9th Special Session on Intelligent Data Mining, Dec. 2023.

Tze-Qian Eng, Hsing-Kuo Pao, and Chi-Chen Liao.
"Self-supervised Federated Learning for Anomaly Detection",
IEEE BigData, 9th Special Session on Intelligent Data Mining, Dec. 2023.

Mohammad Iqbal, Rosita Laili Udhiah, Tsamarah Rana Nugraha, Hsing-Kuo Pao.
"ASAGeR: Automated Short Answer Grading Regressor via Sentence Simplification",
ICKG 2023: 60-68, 2023.

Mohammad Iqbal, Fitria Urbach, Hsing-Kuo Pao, Anggraini Dwi Sensusiati, Nurul Hidayat, Imam Mukhlash.
"Pseudo slicer on three dimensional brain tumor segmentation",
IEEE Big Data 2022: pp. 5278-5287,

Wawan Yunanto, Hsing-Kuo Pao.
"User Behaviour Risk Evaluation in Zero Trust Architecture Environment",
WF-IoT, 2022: pp. 1-6,

Pei-Cheng Tu, Hsing-Kuo Pao.
"A Dropout Style Model Augmentation for Cross Domain Few-Shot Learning",
IEEE BigData, Virtual, Dec. 2021.

Zhiye Fu, Hsing-Kuo Pao, Jiabin He.
"Active Learning with Numerical Feature Annotation",
IEEE BigData, Virtual, Dec. 2021.

Chin-Feng Yu, Hsing-Kuo Pao.
"Virtual Adversarial Active Learning",
IEEE BigData, Virtual, Dec. 2020.

Jiabin He, Hsing-Kuo Pao.
"Multi-modal, Multi-labeled Sports Highlight Extraction",
TAAI, Feb. 2020, Taipei.

Wawan Yunanto and Hsing-Kuo Pao.
"Deep Neural Network-based Data Forgery Detection in Transportation System",
NCS, 2019. (best paper)

Ming-Chen Wang, Vahid Golderzahi, Hsing-Kuo Pao.
"Extracting Explainable Deep Representation for Machine Tutoring",
IEEE BigData, Los Angeles, Dec. 2019. NSTC 108-2633-E-002-001.

Adrian Chriswanto, Hsing-Kuo Pao, Yuh-Jye Lee.
"A Unified Approach on Active Learning Dual Supervision",
International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 2019. NSTC 108-2633-E-002-001.

Vahid Golderzahi, Hsing-Kuo Pao.
"Understanding Customers and Their Grouping via WiFi Sensing for Business Revenue Forecasting",
International Conference on Machine Learning and Data Mining, New York, July 2018. MOST 106-2221-E-011-159.

Er-Chen Huang, Hsing-Kuo Pao, and Yuh-Jye Lee.
"Big Active Learning",
2017 IEEE International Conference on Big Data (IEEE BigData 2017), Boston, USA, Dec. 11-14, 2017.

Tao-Yi Lee, Yuh-Jye Lee, Hsing-Kuo Pao, You-Hua Lin and Yi-Ren Yeh.
"Elastic Motif Segmentation and Alignment of Time Series for Encoding and Classification",
The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS 2017), Time Series Workshop, Long Beach, USA, Dec. 4-9, 2017.

Yuh-Jye Lee, Hsing-Kuo Pao, Shueh-Han Shih, Jing-Yao Lin, and Xin-Rong Chen.
"Compressed Learning for Time Series Classification",
2016 IEEE International Conference on Big Data (IEEE BigData 2016), Washington D. C., USA, Dec. 5-8, 2016.

Alexander Chen, Hsing-Kuo Pao, and Yuh-Jye Lee.
"Online Traffic Speed Forecasting Considering Multiple Periodicities and Complex Patterns",
22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), Machine Learning for Large Scale Transportation Systems (LSTS 2016), San Francisco, USA, Aug. 13-17, 2016.

Chih-Hung Lin, Chin-Wei Tien, Chih-Wei Chen, Chia-Wei Tien, Hsing-Kuo Pao.
"Efficient spear-phishing threat detection using hypervisor monitor",
ICCST 2015: 299-303,

Ghaluh Indah P. S, Junaidillah Fadlil, Rudy Cahyadi Hario Pribadi, Hsing-Kuo Pao.
"Text Comprehensiveness Ranking",
WI-IAT (1) 2015: 21-25,

Ghaluh Indah P. S., Junaidillah Fadlil, Rudy Cahyadi H. P., and Hsing-Kuo Pao.
"Text Difficulty Ranking",
IEEE/WIC/ACM Web Intelligence Conference 2015 (WI-IAT 2015), Singapore, Dec. 6-9, 2015.

Xing-Yu Chen, Hsing-Kuo Pao, Yuh-Jye Lee.
"Efficient traffic speed forecasting based on massive heterogeneous historical data",
IEEE BigData 2014: 10-17,

Xing-Yu Chen, Hsing-Kuo Pao, and Yuh-Jye Lee.
"Efficient Traffic Speed Forecasting Based on Massive Heterogeneous Historical Data",
IEEE International Conference on Big Data (IEEE BigData 2014), Workshop on Large Data Analytics in Transportation Engineering, Washington DC, USA, Oct. 2014.

Erliyah Nurul Jannah and Hsing-Kuo Pao.
"Sensor Reading Prediction using Anisotropic Kernel Gaussian Process Regression",
IEEE International Conference on Internet of Things (iThings 2014), Taipei, Taiwan, Sep. 2014.

Min-Sheng Lin, Chien-Yi Chiu, Yuh-Jye Lee, and Hsing-Kuo Pao.
"Malicious URL Filtering - A Big Data Application",
IEEE International Conference on Big Data (IEEE BigData 2013), Santa Clara, CA, USA, Oct. 2013.

Junaidillah Fadlil, Hsing-Kuo Pao, and Yuh-Jye Lee.
"Anomaly Detection on ITS Data via View Association",
KDD Workshop on Outlier Detection and Description, Chicago, USA, Aug. 2013.

Kai-Lung Hua, Ge-Ming Chiu, Tai-Ling Chin, Hsing-Kuo Pao, Yi-Chi Cheng, and Guan-Ming Su.
"A Novel Scalable Video Streaming Systems on P2P Networks",
International Conference on Computing, Networking and Communications, Multimedia Computing and Communications Symposium, San Diego, USA, Jan. 2013.

Chih-Hung Lin, Chin-Wei Tien, Hsing-Kuo Pao.
"Efficient and Effective NIDS for Cloud Virtualization Environment",
The 4th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2012), Taipei, Taiwan, Dec. 2012.

Hsing-Kuo Pao, Yan-Lin Chou, and Yuh-Jye Lee.
"Malicious URL Detection Based on Kolmogorov Complexity Estimation",
The 2012 IEEE/WIC/ACM International Conference on Web Intelligence, Macau, Dec. 2012.

Danai Koutra, Tai-You Ke, U Kang, Duen Horng Polo Chau, Hsing-Kuo Pao, and Christos Faloutsos.
"Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms",
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Athens, Greece, Sep. 2011.

Chien-Chung Chang, Yuh-Jye Lee, and Hsing-Kuo Pao
"A Passive-Aggressive Algorithm for Semi-supervised Learning",
The 2010 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2010), Taipei, Nov. 2010

Hsing-Kuo Pao, Ching-Hao Mao, Hahn-Ming Lee, Chi-Dong Chen, and Christos Faloutsos
"An Intrinsic Graphical Signature Based on Alert Correlation Analysis for Intrusion Detection"
The 2010 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2010), Taipei, Nov. 2010

J. C.-H. Tseng, H.-K. Pao, and C. Faloutsos.
"The Typhoon Track Classification Using Tri-plots and Markov Chain",
2nd International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Valencia, Spain, Oct. 2010.

C.-H. Mao, H.-K. Pao, C. Faloutsos, and H.-M. Lee.
"SBAD: Sequence Based Attack Detection via Sequence Comparison",
ECML/PKDD Workshop on Privacy and Security issues in Data Mining and Machine Learning, Barcelona, Spain, Sep. 2010.

H.-K. Pao, H-Y. Lin, K.-T. Chen, and J. Fadlil.
"Trajectory Based Behavior Analysis for User Verification",
11th International Conference on Intelligent Data Engineering and Automated Learning, Paisley, Scotland, UK, Sep. 2010.[LNCS]

Y.-T. Wu, S.-J. Lin, E.-S. Liu, H.-K. Pao, C.-H. Mao and H.-M. Lee.
"Cross-Site Scripting Attack Detection Based on Hidden Markov Model",
National Computer Symposium (NCS), 2009.

H.-S. Lin, H.-K. Pao, C.-H. Mao, H.-M. Lee, T. Chen and Y.-J. Lee.
"Adaptive Alarm Filtering by Causal Correlation Consideration in Intrusion Detection",
First KES International Symposium on Intelligent Decision Technologies (IDT), 2009.

K.-T. Chen, H.-K. Pao and H.-C. Chang.
"Game Bot Identification Based on Manifold Learning" (pdf),
7th Workshop on Network and Systems Support for Games (NetGames), Worcester, Massachusetts, USA, Oct. 21 - 22, 2008. [ACM]

K.-T. Chen, A. Liao, H.-K. Pao and H.-H. Chu.
"Game Bot Detection Based on Avatar Trajectory" (pdf),
7th International Conference on Entertainment Computing, Pittsburgh, USA, Sep. 25 - 27, 2008. [LNCS]

H.-K. Pao, S.-C. Chang and Y.-J. Lee.
"Model Trees for Classification of Hybrid Data Types" (pdf),
6th International Conference on Intelligent Data Engineering and Automated Learning, Queensland, Australia, July 2005.

H.-K. Pao and J. Case.
"Computing Entropy for Ortholog Detection" (pdf),
International Conference on Computational Intelligence, Istanbul, Turkey, December 2004.

Y. Lin, J. Case, H.-K. Pao and J. Burnside.
"Predicted Secondary Structure Slightly Enhances Ortholog Detection",
The 8th International Conference on Research in Computational Molecular Biology, San Diego, USA March 2004.

C. Yap, H. Biermann, A. Hertzman, C. Li, J. Meyer, H.-K. Pao and S. Paxia.
"A Different Manhattan Project: Automatic Statistical Model Generation" (gzipped postscript),
Proc. of the 14th Symposium on Electronic Imaging, IS&T/SPIE, San Jose, California, USA, January 2002.

H.-K. Pao and D. Geiger.
"A Continuous Shape Descriptor by Orientation Diffusion" (gzipped postscript),
The 3rd International Workshop on EMMCVPR, France, September 2001.

H.-K. Pao, D. Geiger and N. Rubin.
"Measuring Convexity for Figure/Ground Separation" (gzipped postscript),
IEEE International Conference on Computer Vision, Kerkyra, Greece, September 1999.

D. Geiger, Krishnan Kumaran, H.-K. Pao and N. Rubin.
"The Shape of Illusory Figures",
IEEE Signal Processing Society, International Conference on Image Processing, Kobe, Japan, October 1999.

D. Geiger, H.-K. Pao and N. Rubin.
"Salient and Multiple Illusory Surfaces" (gzipped postscript),
IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Santa Barbara, California, USA, June 1998.

Others

Zolnamar Dorjsembe, Hsing-Kuo Pao, Sodtavilan Odonchimed, Furen Xiao.
"Conditional Diffusion Models for Semantic 3D Medical Image Synthesis",
CoRR abs/2305.18453 2023,

Book Chapter

Y.-J. Lee, Y-R. Yeh and H.-K. Pao.
"Introduction to Support Vector Machines and their Applications in Bankruptcy Prognosis",
in J.-C. Duan, J. E. Gentle, and W. Hardle (editors),
Handbook of Computational Finance, Data Visualization, Springer-Verlag, 2010.

Y.-C. Chang, Y.-J. Lee, H.-K. Pao, M.-H. Lee and S.-Y. Huang.
"Data Visualization via Kernel Machines",
in C.-H. Chen, W. Hardle and A. Unwin (editors),
Handbook of Computational Statistics (Volume III), Data Visualization, Springer-Verlag, New York, 2006.

Dissertation

H.-K. Pao
Doctoral Dissertation,
"A Continuous Model for Salient Shape Selection and Representation", New York University, April 2001.
  Abstract   Compressed PostScript     PDF
                     (3.5Mb)->(27.9Mb)     (4.5Mb)

Other Interesting Works

Laboratory Information