Shao-Lun Huang 黄绍伦


副教授

E-mail : shaolun.huang@sz.tsinghua.edu.cn

Tel & Fax : (86)-755-36881019

Data Science and Information Technology Research Center
Tsinghua-Berkeley Shenzhen Institute
Email: twn2gold@gmail.com, Tel: 15914059195 (cell)
Web: https://sites.google.com/view/slhuang/home

Working Experience
Associate professor, Tsinghua-Berkeley Shenzhen Institute, Sep. 2016 - present.
Postdoctoral researcher, National Taiwan University, Oct. 2013 - Aug. 2016.

Education
Ph.D. (2013) in electrical engineering, Massachusetts Institute of Technology, Cambridge, MA.
Ph. D. thesis: The Euclidean Network Information Theory.
M.S. (2009) in electrical engineering, Massachusetts Institute of Technology, Cambridge, MA.
Master’s thesis: The Design of Binary Shaping Filter of Binary Code.
B.A. (2007) in electrical engineering, National Taiwan University, Taiwan.

Teaching Experience
Introduction to Probability Theory, Spring 2016
Seminar in Data Science and Information Technology, Fall 2016.
Teaching part of of the course \Principle of Communications", National Taiwan University (Fall 2013, Fall 2014)
Organized and planned a few lectures for optimal receiver/filter designing.
Teaching Assistant in \Introduction to EECS II: Digital Communication Systems",
Massachusetts Institute of Technology (Fall 2012)
Organized and planned the interviews of the laboratories for 25 students.
Serving as the lecturer for part of a recitation section.


Internship
Summer internship as a full-time engineer at Sharp Laboratories of America, 2012.
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Participating the project: LTE Device-to-device (D2D) Discovery.

Awards and Honors
National Taiwan University Presidential Award, 2008.
International Mathematical Olympiad, Gold Medal (Tokyo, Japan), 2003.
International Mathematical Olympiad, Silver Medal (Glasgow, United Kingdom), 2002.

Fellowships
Irwin Mark Jacobs and Joan Klein Jacobs Presidential Fellowship, 2008.

Research Interests
Big data analytics and machine learning.
Information theory, error correcting codes, source coding.
Communication theory, communication system and network design.
Social network theory and the applications to Internet systems.

Publications

Monograph

1. S.-L. Huang, A. Makur, G. W. Wornell, L. Zheng (2020). On Universal Features for High-Dimensional Learning and Inference. Foundations and Trends® in Communications and Information Theory: Now Publishers.

Journal Papers

1. S.-L. Huang, X. Xu, L. Zheng, “An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data,” IEEE Journal on Selected Areas in Information Theory, vol. 1, no. 1, pp. 157–166, May 2020.

2. X. Xu, S.-L. Huang, “On the Optimal Tradeoff between Computational Efficiency and Generalizability of Oja’s Algorithm,” IEEE Access, 2020, 8: 102616-102628.

3. S.-L. Huang, X. Xu, “On The Sample Complexity of HGR Maximal Correlation Functions,” Submitted to IEEE transactions on Information Theory, 2019.

44. X. Xu and S.-L. Huang, “Maximal Correlation Regression,” IEEE Access, 2020, 8: 26591-26601.

5. J. Lian, Y. Li, W. Gu, S.-L. Huang, L. Zhang, “Mining Regional Mobility Patterns for Urban Dynamic Analytics,” Mobile Networks and Applications (2019): 1-15.

6. S. Zhang, Y. Dong, H. Fu, S.-L. Huang, L. Zhang, “A Spectral Reconstruction Algorithm if Miniature Soectrometer Based on Sparse Optimization and Dictionary Learning,” Sensors (Basel). 2018 Feb. 22.

7. K.-C. Chen, S.-L. Huang, L. Zheng, H. V. Poor, “Communication Theoretic Data Analytics,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 4, pp. 663-675, April 2015.

8. S.-L. Huang, C. Suh, L. Zheng, “Euclidean Information Theory of Networks,” IEEE transactions on Information Theory, vol. 61, pp. 6795-6814, Dec. 2015.

9. E. Abbe, S.-L. Huang, E. Telatar, “Proof of the outage probability conjecture for MISO channels,” IEEE transactions on Information Theory, vol. 59, pp. 2596-2602, May 2013.

Conference Papers

1. Y. Liang, F. Ma, Y. Li, S.-L. Huang “Person Recognition with HGR Maximal Correlation on Multimodal Data” IEEE International Conference on Pattern Recognition (ICPR), Jan., 2021.

2. M. Li, Y. Li, S.-L. Huang, L. Zhang, “Semantically Supervised Maximal Correlation For Cross-Modal Retrival” IEEE International Conference on Image Processing (ICIP), Oct., 2020.

3. X. Xu, W. Wang, S.-L. Huang, “On the Sample Complexity of Estimating Small Singular Modes” IEEE International Symposium on Information Theory, June, 2020.

4. S.-L. Huang, X. Xu, L. Zheng, G. W. Wornell, “A Local Characterization for Wyner Common Information,” IEEE International Symposium on Information Theory, June, 2020.

5. Z. Wang, H. Zhu, Z. Dong, X. He, S.-L. Huang, ”Less is better: Unweighted Data Subsampling via Influence Function,” Proceedings of the 34rd AAAI Conference on Artificial Intelligence (AAAI-20), Feb., 2020.

6. F. Zhao, F. Ma, Y. Li, S.-L. Huang, L. Zhang, ”Info-detection: An information theoretic approach to detect outlier.” 2019-26th International Conference on Neural Information Processing (ICONIP).

7. X. Xu, S.-L. Huang, “On the Asymptotic Sample Complexity of HGR Maximal Correlation Functions in Semi-supervised Learning,” Allerton Annual Conference on Communication, Control and Computing, Sep. 2019.

8. J. Lian, Y. Li, S.-L. Huang, L. Zhang, “Mining Mobility Patterns with Trip[1] Based Traffic Analysis Zones: A Deep Feature Embedding Approach.” accepted by 2019 IEEE 22nd International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2019.

9. S.-L. Huang, X. Xu, “On The Sample Complexity of HGR Maximal Correlation Functions,” IEEE Information Theory Workshop, Aug., 2019.

10. M. Li, H. Wang, S.-L. Huang, L. Zhang, “ Anomaly Detection in Surface Mount Technology Process using Multi-modal Data,” Proceedings of the 17th ACM Conference on Embedded Networked Sensor Systems, Nov., 2019.

11. Y. Bao, Y. Li, S.-L. Huang, L. Zhang, L. Zheng, A. Zamir, L. Guibas, “An Information-Theoretic Approach To Transferability In Task Transfer Learning” IEEE International Conference on Image Processing (ICIP), Sep., 2019.

12. S.-L. Huang, X. Xu, “On the Robustness of Noisy ACE Algorithm and Multi-Layer Residual Learning,” IEEE International Symposium on Information Theory, Jul., 2019.

13. S.-L. Huang, X. Xu, L. Zheng, G. W. Wornell, “An Information Theoretic Interpretation to Deep Neural Networks,” IEEE International Symposium on Information Theory, Jul., 2019.

14. F. Ma, W. Zhang, Y. Li, S.-L. Huang, L. Zhang, “ An End-to-end Learning Approach For Multimodal Emotion Recognition: Extracting Common and Private Information,” 2019 IEEE International Conference on Multimedia and Expo (ICME), Jul., 2019.

15. L. Li, X. Xu, Y. Li, S.-L. Huang, L. Zhang, “ Maximal Correlation Embedding Network for Multi-label Learning with Missing Labels,” 2019 IEEE International Conference on Multimedia and Expo (ICME), Jul., 2019.

16. L. Wang, J. Wu, S.-L. Huang, L. Zheng, X. Xu, L. Zhang, J. Huang, “An Efficient Approach to Informative Feature Extraction from Multimodal Data,” Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), Jan., 2019.

17. H. Wang, M. Li, F. Ma, S.-L. Huang, L. Zhang, “ Unsupervised anomaly detection via generative adversarial networks,” Proceedings of the 18th International Conference on Information Processing in Sensor Networks, Apr., 2019.

18. J. Lian, Y. Li, W. Gu, S.-L. Huang, L. Zhang, “Joint Mobility Pattern Mining with Urban Region Partitions,” Proceedings of the 15th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Nov., 2018. (Best paper award)

19. F. Ma, W. Gu, W. Zhang, S. Ni, S.-L. Huang, L. Zhang, “ Speech Emotion Recognition via Attention-based DNN from Multi-Task Learning,” Proceedings ofthe 16th ACM Conference on Embedded Networked Sensor Systems, Nov., 2018.

20. Q. Du, W. Gu, L. Zhang, S.-L. Huang, “ Attention-based LSTM-CNNs For Timeseries Classification,” Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems, Nov., 2018.

21. X. Xu, S.-L. Huang, L. Zheng, and L. Zhang. “The Geometric Structure of Generalized Softmax Learning,” 2018 IEEE Information Theory Workshop, Nov., 2018.

22. S.-L. Huang, L. Zheng, G. Wornell, “Gaussian Universal Features, Canonical Correlations, and Common Information,” IEEE Information Theory Workshop, Nov., 2018.

23. S.-L. Huang, L. Zhang, L. Zheng, “An information-theoretic approach to unsupervised feature selection for high-dimensional data,” IEEE Information Theory Workshop, Nov., 2017.

24. S.-L. Huang, A. Makur, L. Zheng, G. W. Wornell, “An Information-Theoretic Approach to Universal Feature Selection in High-Dimensional Inference,” IEEE International Symposium on Information Theory, June, 2017.

25. I-H. Wang, S.-L. Huang, K.-Y. Lee, “Extracting Sparse Data via Histogram Queries,” Allerton Annual Conference on Communication, Control and Computing, October 2016.

26. I-H. Wang, S.-L. Huang, K.-Y. Lee, “Data Extraction via Histogram and Arithmetic Mean Queries: Fundamental Limits and Algorithms,” IEEE International Symposium on Information Theory, June, 2016.

27. A. Makur, F. Kozynski, S.-L. Huang, L. Zheng, “Parallel ACE Algorithm: An Efficient Algorithm to Extract Non-Linear Features from High Dimensional Data,” Allerton Annual Conference on Communication, Control and Computing, October 2015.

28. S.-L. Huang, L. Zheng, “A Spectrum Decomposition to the Feature Spaces and the Application to Big Data Analytics,” IEEE International Symposium on In[1] formation Theory, June, 2015.

29. A. Makhdoumi, S.-L. Huang, Y. Polyanskiy, M. Medard, “On Locally Decodable Source Coding,” IEEE International Conference on Communications, June, 2015.

30. S.-L. Huang, K.-C. Chen, “Information Cascades in Social Networks via Dynamic System Analyses,” IEEE International Conference on Communications, June, 2015.

31. S.-L. Huang, A. Makur, F. Kozynski, and L. Zheng, “Efficient Statistics: Extracting Information from IID Observations,” Allerton Annual Conference on Communication, Control and Computing, Oct., 2014.

32. K.-H., Peng, K.-C. Chen, S.-L. Huang, “Green Traffic Compression in Wireless Sensor Networks,” IEEE 79th Vehicular Technology Conference, May, 2014.

33. S.-L. Huang, C. Suh, L. Zheng, “Euclidean Information Theory of Networks,” IEEE International Symposium on Information Theory, July, 2013.

34. S.-L. Huang, L. Zheng, “Linear Information Coupling Problems,” IEEE International Symposium on Information Theory, July, 2012.

35. E. Abbe, S.-L. Huang, E. Telatar, “Proof of the outage probability conjecture for MISO channels,” IEEE Information Theory Workshop, Sep., 2012.

36. S.-L. Huang, Y. Blankenship, and L. Zheng, “The design of binary shaping filter of binary code,” IEEE Wireless Communications, Networking and Information Security, pp. 228-232, June, 2010.