Mingxuan Sun

Associate Professor
Division of Computer Science and Engineering
Louisiana State University
Baton Rouge, LA 70803

Office: 3272S Patrick F. Taylor Hall
Phone: (225) 578-2882
Email: msun 'AT' csc 'DOT' lsu 'DOT' edu

About me

I am an Associate Professor in the Division of Computer Science and Engineering in the School of Electrical Engineering and Computer Science at Louisiana State University. I received my Ph.D. degree in Computer Science from the Georgia Institute of Technology in 2012. I received my Master's degree in Computer Science from the University of Kentucky in 2006 and my Bachelor's degree in Computer Science and Engineering from Zhejiang University, China in 2004. I was a Senior Scientist with the playlist recommendation group, Pandora Media, Inc. from 2012 to 2015.

To prospective students: I am looking for motivated graduate students and visiting scholars. If you are interested, please e-mail me at msun 'AT' csc 'DOT' lsu 'DOT' edu with your CV and transcripts.

News

  • March 2022: Dr. Sun received a joint NSF-Amazon grant, "FAI: Advancing Optimization for Threshold-Agnostic Fair AI Systems", in collaboration with Dr. Tianbao Yang (PI) and Dr. Qihang Lin.
  • Dec. 2021: Zihan Zhou has successfully defended her Ph.D. dissertation titled "Interpretable and anti-bias machine learning models for human event sequence data". Congratulations, Dr. Zhou!
  • April 2021: Our patent "Increasing the likelihood of receiving feedback for content items" has been issued.
  • April 2021: Dr. Sun received LSU Alumni Association Rising Faculty Research Award, 2021.
  • May 2020: Dr. Sun received NSF CAREER Award, "Privacy-aware predictive modeling of dynamic human events".
  • May 2020: Our paper on list-wise fairness criterion for point processes has been accepted by KDD 2020.
  • May 2020: Jin Shang has successfully defended his Ph.D. dissertation titled "Predictive modeling of asynchronous event sequence data". Congratulations, Dr. Shang!
  • Dec. 2019: Dr. Sun received an NSF grant, "SFS: Applied cybersecurity training", in collaboration with Dr. Golden G. Richard and others.
  • Aug. 2019: Dr. Sun received an NSF grant, "AI-DCL: EAGER: Fairness-aware informatics system for enhancing disaster resilience", in collaboration with Dr. Nina Lam.

Research

My research interests include machine learning, information retrieval, and data mining. I am also interested in machine learning and AI applications in social informatics, healthcare analytics, security, and wireless communications.

Publications

Conference Papers

X. Chen, X. Zhou, H. Zhang, M. Sun, and T. Zhao, Cost-effective federated learning: a unified approach to device and training scheduling, in Proc. IEEE Int. Conf. Commun. (ICC), June 2024, to appear.

Z. Li, and M. Sun, Sparse Transformer Hawkes Process for Long Event Sequences, in Proc. Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), Sep. 2023.

Z. Li, Z. Zhou, M. Sun, and H. Xu Debiased Imitation Learning for Modulated Temporal Point Processes, in Proc. SIAM International Conference on Data Mining (SDM), pp. 460-468, April. 2023.

Z. Zhou, and M. Sun, Multivariate Hawkes Processes for Incomplete Biased Data, in Proc. IEEE International Conference on Big Data, Dec. 2021.

M. Liu, X. Zhou, and M. Sun, A game-theoretic approach to achieving bilateral privacy-utility tradeoff in spectrum sharing, in Proc. IEEE Global Commun. Conf. (GLOBECOM), Dec. 2020.

J. Shang, M. Sun, and N. Lam, List-wise fairness criterion for point processes, in Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Aug. 2020.

M. Sun, Q. Wang, and Z. Liu, Human action image generation with differential privacy, in Proc. IEEE International Conference on Multimedia and Expo (ICME), July 2020.

Z. Zhou, M. Sun, and J. Chen, A model-agnostic approach for explaining the predictions on clustered data, in Proc. IEEE International Conference on Data Mining (ICDM), Nov. 2019.

Q. Chen, M. Sun, and J. Zhang, Neural-attention multi-instance learning for predicting user demographics from highly noisy tweets, in Proc. International Conference on Machine Learning and Data Mining (MLDM), July 2019.

J. Shang and M. Sun, Geometric Hawkes processes with graph convolutional recurrent neural networks, in Proc. AAAI Conference on Artificial Intelligence (AAAI), Jan. 2019.

F. Zhang, X. Zhou, and M. Sun, Multi-level channel valuations and coalitional subgames in spatial spectrum reuse, in Proc. IEEE Consumer Communications and Networking Conference (CCNC), Jan. 2019.

N. Wu, X. Zhou, and M. Sun, Incentive mechanisms and influence of negotiation power in multi-relay cooperative wireless networks, in Proc. IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, UAE, Dec. 2018.

J. Shang and M. Sun, Local low-rank Hawkes processes for temporal user-item interactions, in Proc. IEEE International Conference on Data Mining (ICDM), Singapore, Nov. 2018.

J. Shang, M. Sun, and K. Collins-Thompson, Demographic inference via knowledge transfer in cross-domain recommender systems, in Proc. IEEE International Conference on Data Mining (ICDM), Singapore, Nov. 2018.

S. Guo, X. Zhou, S. Xiao, and M. Sun, Low-complexity mode selection and resource allocation for energy-efficient D2D communications, in Proc. IEEE Vehicular Technology Conference (VTC), Chicago, IL, Aug. 2018.

N. Wu, X. Zhou, and M. Sun, Multi-channel jamming attacks against cooperative defense: a two-level Stackelberg game approach, in Proc. IEEE International Conference on Communications (ICC), Kansas City, MO, May 2018.

F. Zhang, X. Zhou, and M. Sun, Constrained VCG auction for spatial spectrum reuse with flexible channel evaluations, in Proc. IEEE Global Communications Conference (GLOBECOM), Singapore, Dec. 2017.

N. Wu, X. Zhou, and M. Sun, Secure transmission in heterogeneous networks: a two-level Stackelberg game approach, in Proc. IEEE Global Communications Conference (GLOBECOM), Singapore, Dec. 2017.

M. Sun, C. Li, and H. Zha, Inferring private demographics of new users in recommender systems, in Proc. ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM), Miami, FL, Nov. 2017.

M. Sun, G. Xu, J. Zhang, and D.W. Kim, Tracking you through DNS traffic: linking user sessions by clustering with Dirichlet mixture model, in Proc. ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM), Miami, FL, Nov. 2017.

T. Wang, M. Sun, and K. Hu, Dilated deep residual network for image denoising, in Proc. International Conference on Tools with Artificial Intelligence (ICTAI), Boston, MA, Nov. 2017.

M. Sun and S. Yang, Personalization of learning paths in online communities of creators, in Proc. International Conference on Educational Data Mining (EDM), Raleigh, NC, June 2016.

K. Kapoor, M. Sun, J. Srivastava, and T. Ye, A hazard based approach to user return time prediction, in Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), New York, NY, Aug. 2014.

M. Sun, F. Li, J. Lee, K. Zhou, G. Lebanon, and H. Zha, Learning multiple-question decision trees for cold-start recommendation, in Proc. ACM International Conference on Web Search and Data Mining (WSDM), Rome, Italy, Feb. 2013.

J. Lee, M. Sun, S. Kim, and G. Lebanon, Automatic feature induction for stagewise collaborative filtering, in Proc. Annual Conference on Neural Information Processing Systems (NeurIPS), Lake Tahoe, NV, Dec. 2012.

M. Sun, G. Lebanon, and P. Kidwell, Estimating probabilities in recommendation systems, in Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), Ft. Lauderdale, FL, Apr. 2011.

M. Sun, G. Lebanon, and K. Collins-Thompson, Visualizing differences in web search algorithms using the expected weighted Hoeffding distance, in Proc. International World Wide Web Conference (WWW), Raleigh, NC, Apr. 2010.

M. Sun, G. Schindler, G. Turk, and F. Dellaert, Color matching and illumination estimation for urban scenes, in Proc. IEEE International Conference on Computer Vision (ICCV) Workshops, Tokyo, Japan, Oct. 2009.

M. Liao, M. Sun, R. Yang, and Z. Zhang, Robust and accurate visual echo cancellation in a full-duplex projector-camera system, in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop, New York, NY, June 2006.

M. Sun, R. Yang, L. Yun, G. Landon, B. Seales, and M. S. Brown, Geometric and photometric restoration of distorted documents, in Proc. IEEE International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005.

Journal Papers

L. Song, S. Chen, Z. Meng, M. Sun, and X. Shang, FMSA-SC: A Fine-grained Multimodal Sentiment Analysis Dataset based on Stock Comment Videos, IEEE Transactions on Multimedia, 2024, to appear.

L. Song, J. Li, J. Liu, Y. Yang, X. Shang, and M. Sun, Answering knowledge-based visual questions via the exploration of Question Purpose, Pattern Recognition, 133, p.109015, 2023.

V.V. Mihunov, K. Wang, Z. Wang, N.S. Lam, and M. Sun, Social media and volunteer rescue requests prediction with random forest and algorithm bias detection: a case of Hurricane Harvey, Environmental Research Communications, 2023.

Z. Wang, N.S. Lam, M. Sun, X. Huang, J. Shang, L. Zou, Y. Wu, and V.V. Mihunov, A Machine Learning Approach for Detecting Rescue Requests from Social Media, ISPRS International Journal of Geo-Information, vol. 11, no. 11, 2022.

L. Song, X. Shang, C. Yang, and M. Sun, Attribute-Guided Multiple Instance Hashing Network for Cross-Modal Zero-Shot Hashing, IEEE Transactions on Multimedia, 2022.

M. Liu, X. Zhou, and M. Sun, Bilateral privacy-utility tradeoff in spectrum sharing systems: a game-theoretic approach, IEEE Trans. Wireless Commun., vol. 20, no. 8, pp. 5144-5158, Aug. 2021.

L. Song, J. Liu, M. Sun, and X Shang, Weakly Supervised Group Mask Network for Object Detection, International Journal of Computer Vision, vol. 129, no. 3, 681-702, 2021.

A. Case, R. Maggio, M. Firoz-Ul-Amin, M. Jalalzai, A. Ali-Gombe, M. Sun, and G. G. Richard III, Hooktracer: automatic detection and analysis of keystroke loggers using memory forensics, Computers & Security, 101872, 2020.

J. Shang and M. Sun, Local low-rank Hawkes processes for modeling temporal user-item interactions, Knowledge and Information Systems, vol. 62, 1089-1112, 2020.

F. Zhang, X. Zhou, and M. Sun, On-demand receiver-centric channel allocation via constrained VCG auction for spatial spectrum reuse, IEEE Systems Journal, 13(3), 2519-2530, 2019.

A. Case, M. Jalalzai, M. Firoz-Ul-Amin, R. Maggio, A. Ali-Gombe, M. Sun, and G. G. Richard III, HookTracer: a system for automated and accessible API hooks analysis, Digital Investigation, 29, S104-S112, 2019.

N. Wu, X. Zhou, and M. Sun, Incentive mechanisms and impacts of negotiation power and information availability in multi-relay cooperative wireless networks, IEEE Transactions on Wireless Communications, 18(7), 3752-3765, 2019.

S. Guo, X. Zhou, S. Xiao, and M. Sun, Fairness-aware energy-efficient resource allocation in D2D communication networks, IEEE Systems Journal, vol. 13, no. 2, 1273-1284, June 2019.

F. Zhang, X. Zhou, and M. Sun, Constrained VCG auction with multi-level channel valuations for spatial spectrum reuse in non-symmetric networks, IEEE Transactions on Wireless Communications, 67(2), 1182-1196, 2019.

L. Song, J. Liu, B. Qian, M. Sun, K. Yang, M. Sun, and S. Abbas, A deep multi-modal CNN for multi-instance multi-label image classification, IEEE Transactions on Image Processing, vol. 27, no. 12, 6025-6038, 2018.

Z. Zhang, C. Sun, R. Bridgelall, and M. Sun, Application of a machine learning method to evaluate road roughness from connected vehicles, Journal of Transportation Engineering, Part B: Pavements, vol. 144, issue. 4, p. 04018043, Dec. 2018.

N. Wu, X. Zhou, and M. Sun, Secure transmission with guaranteed user satisfaction in heterogeneous networks: a two-level Stackelberg game approach, IEEE Transactions on Communications, vol. 66, no. 6, pp. 2738-2750, June 2018.

M. Sun, F. Li, and J. Zhang, A multi-modality deep network for cold-start recommendation, Big Data and Cognitive Computing, pp. 1-15, Mar. 2018.

J. Lee, M. Sun, and G. Lebanon, PREA: personalized recommendation algorithms toolkit, Journal of Machine Learning Research (JMLR), vol. 13, no. 1, pp. 2699-2703, Sept. 2012.

M. Sun, G. Lebanon, and P. Kidwell, Estimating probabilities in recommendation systems, Journal of the Royal Statistical Society, Series C, vol. 61, no. 3, pp. 471-492, May 2012.

J. Lee, M. Sun, and G. Lebanon, A comparative study of collaborative filtering algorithms, ArXiv:1205.3193, May 2012.

M. Sun, Z. Liu, J. Qiu, Z. Zhang, and M. Sinclair, Active lighting for video conferencing, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 19, no. 12, pp. 1819-1829, Dec. 2009.

M. S. Brown, M. Sun, R. Yang, L. Yun, G. Landon, and B. Seales, Restoring 2D content from distorted documents, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 29, no. 11, pp. 1904-1916, Nov. 2007.

H. Wang, M. Sun, and R. Yang, Space-time light field rendering, IEEE Transactions on Visualization and Computer Graphics (TVCG), vol. 13, no. 4, pp. 697-710, July 2007.

Patent

M. Sun and G. P. Rios, Increasing the likelihood of receiving feedback for content items, U.S. Patent 10,990,989, Apr. 27, 2021.

Z. Liu, M. Sun, J. Qiu, Z. Zhang, and M. Sinclair, Lighting array control, U.S. Patent 7869705, Jan. 11, 2011.

Software

J. Lee, M. Sun, and G. Lebanon, PREA: personalized recommendation algorithm toolkit.

Other Projects

Research applications in visualization and computer vision.

Current Students

  • Taibiao Zhao, PhD Student
  • Zhuoqun Li, PhD Student
  • Boyang Zhang, PhD Student

Alumni

Graduated PhD Students

Graduated MS Students

  • Changbin Li, MS Student
  • Fei Li, MS Student
  • Zhongzhu Peng, MS Student
  • Abhishek Huddar, MS Student
  • Qing Wang, MS Student

Teaching

Supporting Agencies