Publications

1.    Ph.D. Dissertation: “Global Search Methods for Solving Nonlinear Optimization Problems,” Dept. of Computer Science, University of Illinois, 1997.

2.    M.S. Thesis: “Novel Genetic Operators for Combinatorial Optimization Problems,” Institute of Computing Technology, Chinese Academy of Sciences, 1991.

Publications (Over 200 refereed journal and conference publications)

Refereed Journal Papers

1.     Zhao, F., Shang, Y. & Trull, T.J. FENAP: Foundation Models for EMA-Derived Narrative Analysis and Prediction. J Healthc Inform Res (2024). https://doi.org/10.1007/s41666-024-00170-9.

2.     R. Viegut, E. Webb, A. Raedeke, Z. Tang, Y. Zhang, Y. Shang, “Nonbreeding Waterfowl Behavioral Response to Crewed and Uncrewed Aerial Surveys on Conservation Areas in Missouri,” Journal of Southeastern Association of Fish and Wildlife Agencies, Volume 11, pp. 127-136, March 2024.

3.     R. Viegut, E. Webb, A. Raedeke, Z. Tang, Y. Zhang, Z. Zhai, Z. Liu, S. Wang, J. Zheng, Y. Shang, “Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys,” Drones 8, no. 2: 54, MDPI, 2024. https://doi.org/10.3390/drones8020054.

4.     Zhang, Y.; Feng, Y.; Wang, S.; Tang, Z.; Zhai, Z.; Viegut, R.; Webb, L.; Raedeke, A.; Shang, Y. “Deep Learning Models for Waterfowl Detection and Classification in Aerial Images.” Information 15, no. 3: 157, MDPI, March 2024. https://doi.org/10.3390/info15030157.

5.     C. Yu, Y. Shang, T. Hough, A. Bokshan, M. Fleming, Al. Haney, and T. Trull, “Predicting quantity of cannabis smoked in daily life: An exploratory study using machine learning,” Drug and Alcohol Dependence, 252:110964, Nov. 2023.

6.     J. Wang, W. Wang and Y. Shang, "Protein Loop Modeling Using AlphaFold2," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 20, no. 5, pp. 3306-3313, 1 Sept.-Oct. 2023, doi: 10.1109/TCBB.2023.3264899. 

7.     Praveen K Edara, Carlos Sun, Henry Brown, Peter T Savolainen, Venky Shankar, Bimal Balakrishnan, Yi Shang, Sounak Chakraborty, Yaw Adu-Gyamfi, Can Li, Khaled Aati, S Lima, Yilun Huang, Abdul Rashid Mussah, J Hopfenblatt, “MIMIC—Multidisciplinary Initiative on Methods to Integrate and Create Realistic Artificial Data,” FHWA-HRT-23-015, Federal Highway Administration, January 2023.

8.     G. Chen and Y. Shang, “Transformer for Tree Counting in Aerial Images,” Remote Sensing, vol. 14, no. 3, p. 476, Jan. 2022, doi: 10.3390/rs14030476.

9.     W. Wang, J. Wang, Z. Li, D. Xu, and Y. Shang, “MUfoldQA_G: High-accuracy protein model QA via retraining and transformation,” Computational and Structural Biotechnology Journal, Volume 19, 2021, Pages 6282-6290, ISSN 2001-0370, https://doi.org/10.1016/j.csbj.2021.11.021.

10.  B. Rezaeianjouybari and Y. Shang, “A Novel Deep Multi-Source Domain Adaptation Framework for Bearing Fault Diagnosis Based on Feature-level and Task-specific Distribution Alignment,” Measurement, Vol. 178, June 2021. https://doi.org/10.1016/j.measurement.2021.109359.

11.  F.C. Feng and Y. Shang, “Breathing Crack Detection Using Dynamic Equations and Machine Learning,” Journal of Vibration Testing and System Dynamics, pp. 359-372, January 2021. 10.5890/JVTSD.2021.12.004.

12.  Y. Liu, P. Sun, N. Wergeles, and Y. Shang, “A Survey and Performance Evaluation of Deep Learning Methods for Small Object Detection,” Expert Systems With Applications, Vol 172, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2021.114602, Elsevier, 2021.

13.  B. Rezaeianjouybari and Y. Shang, “Deep learning for prognostics and health management: State of the art, challenges, and opportunities,” Measurement, Volume 163, 107929, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2020.107929, Elsevier, 2020.

14.  P. Sun, G. Chen and Y. Shang, "Adaptive Saliency Biased Loss for Object Detection in Aerial Images," in IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7154-7165, Oct. 2020, doi: 10.1109/TGRS.2020.2980023.

15.  C. Fang, Z. Li, D. Xu, and Y. Shang, “MUFold-SSW: a new web server for predicting protein secondary structures, torsion angles and turns,” Bioinformatics, 36(4), 15 February 2020.

16.  C. Fang, Y. Shang, and D. Xu, “A Deep Dense Inception Network for Protein Beta-Turn Prediction,” Proteins: Structure, Function, and Bioinformatics, Wiley, 11 July 2019.

17.  W. Wang, Z. Li, J. Wang, D. Xu, and Y. Shang, “PSICA: a fast and accurate web service for protein model quality analysis,” Nucleic Acids Research, Volume 47, Issue W1, 02 July 2019, Pages W443–W450.

18.  W. Wang, J. Wang, D. Xu, and Y. Shang, “Two New Heuristic Methods for Protein Model Quality Assessment,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019. DOI 10.1109/TCBB.2018.2880202.

19.  C. Fang, Y. Shang, and D. Xu, “Prediction of Protein Backbone Torsion Angles Using Deep Residual Inception Neural Networks,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16(3):1020-1028, May-June 2019. DOI 10.1109/TCBB.2018.2814586.

20.  S. Nguyen, Z. Li, D. Xu, and Y. Shang, “New Deep Learning Methods for Protein Loop Modeling,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16(2):596-606, March-April 2019. DOI: 10.1109/TCBB.2017.2784434.

21.  C. Fang, Y. Shang, and D. Xu, “MUFOLD-SS: New Deep Inception-Inside-Inception Networks for Protein Secondary Structure Prediction,” Proteins: Structure, Function, and Bioinformatics, 86(5):592-598, May 2018. DOI 10.1002/prot.25487.

22.  C. Fang, Y. Shang, and D. Xu, “Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks,” Scientific Reports, 2018.

23.  J. Yang, Y. Xu, Y. Shang, and G. Chen, “A Space-Bounded Anytime Algorithm for the Multiple Longest Common Subsequence Problem”, IEEE Transactions on Knowledge and Data Engineering, 26(11), Nov.  2014. PMID: 25400485; PMCID: PMC4231498.

24.  Q. Wang, C. Shang, D. Xu, and Y. Shang, “New MDS and Clustering Based Algorithms for Protein Model Quality Assessment and Selection,” Int’l Journal on Artificial Intelligence Tools, 22(5), 2013.

25.  D. Wang and Y. Shang, “Modeling Physiological Data with Deep Belief Networks”, Int’l Journal of Information and Education Technology, 3(5):505-511, Oct. 2013.

26.  T. Zhuang, P. Baskett, and Y. Shang, “Managing Ad Hoc Networks of Smartphones,” Int’l Journal of Information and Education Technology, 3(5):540-546, Oct. 2013.

27.  Y. Xu, J. Yang, Y. Zhao, and Y. Shang, “An Improved Voting Algorithms For Planted (l, d) Motif Search,” Information Sciences, 237, pp. 305-312, July 2013.

28.  J. Yang, Y. Xu, G. Sun, and Y. Shang. "A new progressive algorithm for multiple longest common subsequences problem and its efficient parallelization". IEEE Trans. on Parallel and Distributed Systems, 24(5), pp. 862-870, May 2013. 

29.  J. Zhang, Z. He, Q. Wang, B. Barz, I. Kosztin, Y. Shang, and D. Xu, “Prediction of protein tertiary structures using MUFOLD,” Methods in Molecular Biology. 815:3-13, 2012.

30.  Z. He, J. Zhang, Y. Xu, Y. Shang, and D. Xu, “Protein model selection based on sequence-dependent scoring function,” Journal Statistics and Its Interface, 5(1), pp. 109-116, 2012.

31.  Q. Wang, K. Vantasin, D. Xu, and Y. Shang, “MUFOLD-WQA: A New Selective Consensus Method for Quality Assessment in Protein Structure Prediction,” Proteins, 79(S10), pp. 185-195, 2011.

32.  J. Zhang, Q. Wang, K. Vantasin, J. Zhang, Z. He, I. Kosztin, Y. Shang, and D. Xu, “A multi-layer evaluation approach for protein structure prediction and model quality assessment,” Proteins, 79(S10), pp. 172-184, 2011.

33.  Q. Qi and Y. Shang, “Comparison of Probabilistic Chain Graphical Model-Based and Gaussian Process-Based Observation Selections for Wireless Sensor Scheduling,” International Journal of Distributed Sensor Networks, Article ID 928958, doi:10.1155/2011/928958, 2011.

34.  Q. Wang, Y. Shang, and D. Xu, “Improving Consensus Approach for Protein Structure Selection by Removing Redundancy,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(6), pp. 1708-1715, 2011.  

35.  X. Shi, J. Zhang, Z. He, Y. Shang, and D. Xu. “A sampling-based method for ranking protein structural models by integrating multiple scores and features.” Current Protein and Peptide Science, 12(6):540-548, September 2011.

36.  Q. Wang, D. Korkin, and Y. Shang, “A Fast Multiple Longest Common Subsequence (MLCS) Algorithm,” IEEE Transactions on Knowledge and Data Engineering, 23(3), pp. 321-334, March 2011.

37.  B. Yin, H. Shi, and Y. Shang, “An Efficient Algorithm for Constructing Connected Dominating Set in Mobile Ad Hoc Networks,” Journal of Parallel and Distributed Computing, 71(1), pp. 27-39, January 2011.

38.  J. Zhang, Q. Wang, B. Barz, Z. He, I. Kosztin, Y. Shang, D. Xu, “MUFOLD: A New Solution for Protein 3D Structure Prediction.” Proteins, 78(5), pp. 1137-1152, Wiley, 2010.

39.  H. Shi, X. Li, Y. Shang, and D. Ma, “Error Analysis of Quantized RSSI Based Sensor Network Localization,” International Journal of Wireless and Mobile Computing, 4(1), pp. 31-40, 2010.

40.  B. Yin, H. Shi, and Y. Shang, “A Two-Level Topology Control Strategy for Energy Efficiency in Wireless Sensor Networks,” International Journal of Wireless and Mobile Computing, 4(1), pp. 41-49, 2010.

41.  Y. Liu, H. Shi, and Y. Shang, “Design of Learning Objects to Support Constructivist Learning Environments.” IEEE Learning Technology Newsletter, 11(4), Oct. 2009.

42.  Yi Shang, H. Shi, Y. Zhang, C. Guettier, “Distributed systems of sensors and actuators.” Wireless Communications and Mobile Computing, 9(3), 2009.

43.  M. Tubaishat, P. Zhuang, Q. Qi, and Y. Shang, “Wireless Sensor Networks in Intelligent Transportation Systems.” Wireless Communications and Mobile Computing, 9(3), pp. 287-302, 2009.

44.  P. Zhuang, Y. Shang, and B. Hua, “Statistical methods to estimate vehicle count using traffic cameras,” Multidimensional Systems and Signal Processing, Springer, Vol 20(2), 2009.

45.  X. Li, B. Hua, Y. Shang, Y. Xiong, “A robust localization algorithm in wireless sensor networks.” Frontiers of Computer Science in China, 2(4), pp. 438-450, 2008.

46.  P. Zhuang, Y. Shang, and H. Shi, “A New Method of Using Sensor Networks for Pursuit-Evasion Problems,” Journal of Networks, 2(1):9-16, February 2007.

47.  S. Selvakennedy, S. Sinnappan, and Y. Shang, “A Biologically-inspired Clustering Protocol for Wireless Sensor Networks,” Computer Communications, Vol. 30, June 2007.

48.  Y. Shang and H. Shi, “Flexible Energy Efficient Density Control on Wireless Sensor Networks,” Int’l Journal of Distributed Sensor Networks, 3:5-21, 2007. 

49.  X. Li, H. Shi, and Y. Shang, “Sensor Network Localization Based on Sorted RSSI Quantization,” Int’l Journal of Ad Hoc and Ubiquitous Computing, 1(4), pp. 222 – 229, July 2006.

50.  Y. Shang, M. Fromherz, and L. Crawford, “A new constraint test-case generator and the importance of hybrid optimizers,” European Journal of Operational Research, Elsevier Science, vol. 173, pp. 419-443, 2006.

51.  H. Shi, Y. Shi, and Y. Shang, “A ProFound-based Meta Search Engine for Rapid Protein Identification,” Information, Japan, Vol. 9, No. 6, pp. 891-900, 2006.

52.  S. Selvakennedy, Sukunesan Sinnappan and Yi Shang, “T-ANT: A Nature-Inspired Data Gathering Protocol for Wireless Sensor Networks,” Journal of Communications, Vol. 1, No. 2, pp. 22-29, May 2006.

53.  A. Ahmed, Y. Shang, H. Shi, and B. Hua, “Variants of MDS-Based Methods for Ad Hoc Network Localization,” Journal of Interconnection Networks, World Scientific, Vol. 7, No. 1, pp. 5-19, 2006.

54.  Y. Shang, W. Ruml, and M.  Fromherz, “Positioning Using Local Maps,” Ad Hoc Networks Journal, Elsevier, Vol. 4, pp. 240-253, 2006.

55.  H. Shi, H. Liu, Y. Shang, and S. Chen, “Student Modeling in E-Learning Environments,” Int’l Journal on Education and Information Technologies, Springer Science, 2(1), pp. 1-20, Sept. 2005.

56.  H. Shi, C. S. Cummngs, Y. Shang, and S. Chen, “A Flexible Authentication and Authorization Scheme for A Learner Information Management Web Service,” International Journal of Information Technology and Decision Making, World Scientific, vol. 4, No. 2, June 2005.

57.  Y. Shang, W. Ruml, M.  Fromherz, and Y. Zhang, “Localization from Connectivity in Sensor Networks,” IEEE Trans. Parallel and Distributed Systems, vol. 15, no. 11, pp. 961-974, Nov. 2004.

58.  H. Shi, O. Rodriguez, S. Chen, and Y. Shang, “Open Learning Objects as an Intelligent Way of Organizing Educational Material,” International Journal on E-Learning, 3(2):47-59, April-June 2004.

59.  Y. Shang and M. Fromherz, “Experimental Complexity Analysis of Continuous Constraint Satisfaction Problems,” Information Sciences, Elsevier Science, No. 153, pp. 1-36, 2003.

60.  Y. Shang and L. Li, “Precision Evaluation of Search Engines,” World Wide Web, Kluwer Academic, Vol. 5, No. 2, pp. 159-173, 2002.

61.  Y. Shang, H. Shi, and S. Chen, “An Intelligent Distributed Environment for Active Learning,” ACM Journal on Educational Resources in Computing, Vol. 1, No. 2, pp. 1-17, summer, 2001.

62.  Y. Shang, L. Li, and B. Wah, “Optimization Design of Biorthogonal Filter Banks for Image Compression,” Information Sciences, Elsevier Science, No. 132, pp. 23-51, 2001.

63.  L. Li and Y. Shang, “A New Method for Automatic Performance Comparison of Search Engines,” World Wide Web, Kluwer Academic, Vol. 3, No. 4, pp. 241-247, Dec. 2000.

64.  Y. Shang, C. Sapp, and H. Shi, “An Intelligent Web Representative,” Information, Vol. 3, No. 2, International Information Institute, Japan, 2000.

65.  B. W. Wah, T. Wang, Y. Shang, and Z. Wu, “Improving the Performance of Weighted Lagrange-Multiplier Methods for Constrained Nonlinear Optimization,” Information Sciences, Elsevier, Vol. 124, No. 1-4, pp. 241-272, 2000.

66.  Y. Shang and H. Shi, “A Web-Based Multi-Agent System for Interpreting Medical Images,” World Wide Web, Kluwer Academic, Vol. 2, No. 4, pp. 209-218, 1999.

67.  B. W. Wah, Y. Shang, and Z. Wu, “Discrete Lagrangian Method for Optimizing the Design of Multiplierless QMF Filter Banks”, IEEE Transactions on Circuits and Systems II, Vol. 46, No. 9, pp. 1179-1191, Sept. 1999.

68.  Y. Shang and B. W. Wah, “A Discrete Lagrangian-based Global-Search Method for Solving Satisfiability Problems,” Journal of Global Optimization, Kluwer Academic, Vol. 12, No. 1, pp. 61-99, Jan. 1998.

69.  Y. Shang and B. W. Wah, “Global Optimization for Neural Network Training,” IEEE Computer, vol. 29, No. 3, pp. 45-54, March 1996.

70.  B. W. Wah and Y. Shang, “Comparison and Evaluation of a Class of IDA* Algorithms,” Int'l Journal of Tools with Artificial Intelligence, World Scientific, vol. 3, no. 4, Oct. 1995, pp. 493-523.

71.  Y. Shang and Z. Tang, “Heuristic Operators for Genetic Algorithms,” Journal of Computer Research and Development of China, vol. 29, pp. 14--19, Sept. 1992.

Refereed Conference Papers

  1. J. Tang and Y. Shang, “Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessment,” IEEE International Conf. on Cognitive Machine Intelligence, Oct. 2024.
  2. J. Tang, Q. Guo, Y. Zhao, and Y. Shang, “Decoding Linguistic Nuances in Mental Health Text Classification Using Expressive Narrative Stories,” IEEE International Conf. on Cognitive Machine Intelligence, Oct. 2024.
  3. F. Zhao, F. Yu, and Y. Shang, “A New Method Supporting Qualitative Data Analysis Through Prompt Generation for Inductive Coding,” IEEE 25th International Conference on Information Reuse and Integration for Data Science, San Jose, CA, August 2024.
  4. W. Wang, C. Li, L. Hu, B. Pang, B. Balducci, D. Marinova, M. Gordon, and Y. Shang, “Recognizing and Predicting Business Communication Outcomes Using Local LLMs,” IEEE 25th International Conference on Information Reuse and Integration for Data Science, San Jose, CA, August 2024.
  5. Y. Feng, Y. Zhang, and Y. Shang, “Toward Optimal Amount of Training Annotations for Waterfowl Detection and Classification,” IEEE International Conference on Intelligent Mobile Computing, Shanghai, China, July 2024.
  6. Y. Wang, J. Wang, and Y. Shang, “New Methods for Animal Detection in Camera Trap Image Sequences,” IEEE International Conference on Intelligent Mobile Computing, Shanghai, China, July 2024.

7.     A. Zhao, A. Fratila, Y. Zhang, Z. Zhai, Z. Liu, and Y. Shang, “Automatic Waterfowl and Habitat Detection using Drone Imagery and Deep Learning,” IEEE International Conference on Consumer Electronics, January 2024. DOI:10.1109/ICCE59016.2024.10444338.

  1. F. Zhao, F. Yu, T. Trull, and Y. Shang, “A New Method Using LLMs for Keypoints Generation in Qualitative Data Analysis,” IEEE Conference on Artificial Intelligence, June 2023.
  2. C. Li, B. Pang, W. Wang, L. Hu, and Y. Shang, “How Well Can Language Models Understand Politeness?” IEEE Conference on Artificial Intelligence, June 2023.
  3. C. Li, P. Edara, and Y. Shang, “Crash Frequency Modeling using Realistic Artificial Data,” IEEE Conference on Artificial Intelligence, June 2023.
  4. C. Li, Z. Qing, P. Edara, C. Sun, B. Balakrishnan, and Y. Shang, “Semi-Automatic Construction of Virtual Reality Environment for Highway Work Zone Training using Open-Source Tools,” IEEE Conference on Virtual Reality and 3D User Interfaces, March 2023.
  5. Z. Tang, Y. Liu and Y. Shang, "A New GNN-Based Object Detection Method for Multiple Small Objects in Aerial Images," IEEE/ACIS 23rd International Conference on Computer and Information Science (ICIS), June 2023.
  6. C. Yu, Y. Shang, and T. Trull, “Reproducible Workflows for Exploring and Modeling EMA Data,” IEEE International Conference on Collaboration and Internet Computing, Dec. 2022.
  7. Y. Zhang, Y. Wang, Z. Tang, Z. Zhai, R. Viegut, and Y. Shang, “Deep Learning Methods for Tree Detection and Classification,” IEEE International Conference on Cognitive Machine Intelligence, Dec. 2022.
  8. J. Wang, W. Wang, and Y. Shang, “New Heuristic Methods for Protein Model Quality Assessment via Two-Stage Machine Learning and Hierarchical Ensemble,” IEEE International Conference on Cognitive Machine Intelligence, Dec. 2022.
  9. Y. Zhang, Z. Tang, S. Wang, Z. Zhai, R. Viegut, E. Webb, A. Raedeke, and Y. Shang, “Development of New Aerial Image Datasets and Deep Learning Methods for Waterfowl Detection and Classification,” IEEE International Conference on Cognitive Machine Intelligence, Dec. 2022. (Best paper award)
  10. L. Hu, C. Li, W. Wang, B. Pang, and Y. Shang, “Performance Evaluation of Text Augmentation Methods with BERT on Small-sized, Imbalanced Datasets,” IEEE International Conference on Cognitive Machine Intelligence, Dec. 2022.
  11. Y. Wang, Y. Zhang, Y. Feng, and Y. Shang, “Deep Learning Methods for Animal Counting in Camera Trap Images,” IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI), Nov. 2022.

19.  C. Li, W. Wang, B. Balducci, L. Hu, M. Gordon, D. Marinova, and Y. Shang, “Deep Formality: Sentence Formality Prediction with Deep Learning,” 23rd IEEE International Conference on Information Reuse and Integration for Data Science, April 2022.

  1. Z. Tang, Y. Zhang, Y. Wang, R. Viegut, E. Webb, A. Raedeke, J. Sartwell, and Y. Shang, "sUAS and Machine Learning Integration in Waterfowl Population Surveys," 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), 2021, pp. 517-521, doi: 10.1109/ICTAI52525.2021.00084.
  2. B. Rezaeianjouybari and Y. Shang, “An Empirical Study of Machine Learning and Deep Learning Methods on Bearing Fault Diagnosis Benchmarks,” Proc. ASME 2021 International Mechanical Engineering Congress and Exposition. Volume 7A: Dynamics, Vibration, and Control. Virtual, Online. November 1–5, 2021. V07AT07A050. ASME. https://doi.org/10.1115/IMECE2021-69994.
  3. W. Guo, S. Zong, S. Chen, F. Zhao and Y. Shang, "Design and Implementation of a New Serverless Conversational Survey System," 2021 IEEE International Conference on Data Science and Computer Application (ICDSCA), 2021, pp. 358-363, doi: 10.1109/ICDSCA53499.2021.9650203.
  4. C. Winters, J. E. Varghese, G. Stafford, F. Zhao, S. Chen and Y. Shang, "Creation of EMA-KN – A Knowledge Network for Ecological Momentary Assessment," 2021 IEEE International Conference on Big Data (Big Data), 2021, pp. 5639-5647, doi: 10.1109/BigData52589.2021.9671616.
  5. C. Li, W. Wang, B. Balducci, D. Marinova and Y. Shang, "Predicting Conversation Outcomes Using Multimodal Transformer," 2021 International Joint Conference on Neural Networks (IJCNN), 2021, pp. 1-6, doi: 10.1109/IJCNN52387.2021.9533935.
  6. M. Krusniak, A. James, A. Flores and Y. Shang, "A Multiple UAV Path-Planning Approach to Small Object Counting with Aerial Images," 2021 IEEE International Conference on Consumer Electronics (ICCE), 2021, pp. 1-6, doi: 10.1109/ICCE50685.2021.9427712.
  7. X. Su, Z. Ye, L. Wu, and Y. Shang, “Optimal Stochastic Media Storage in Federated Cloud Environments,” Proc. IEEE International Conference on Computing, Networking and Communications (ICNC), February 2020.
  8. M. Krusniak, K. Leppanen, Z. Tang, F. Gao, Y. Wang, and Y. Shang, “A Detection Confidence-Regulated Path Planning (DCRPP) Algorithm for Improved Small Object Counting in Aerial Images,” Proc. IEEE International Conference on Consumer Electronics (ICCE), January 2020.
  9. J. Wang, W. Wang, and Y. Shang, “A New Approach Of Applying Deep Learning To Protein Model Quality Assessment,” Proc. IEEE International Conference on Bioinformatics and Biomedicine, Nov. 2019.
  10. J. Ruffolo, Z. Li, and Y. Shang, “MUFold-Contact and TPCref: New Methods for Protein Structure Contact Prediction and Refinement,” Proc. IEEE International Conference on Bioinformatics and Biomedicine, Nov. 2019.
  11. L. Guerdan, P. Sun, C. Rowland, L. Harrison, Z. Tang, N. Wergeles, and Y. Shang, “Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction,” Adolescent Brain Cognitive Development Neurocognitive Prediction, Lecture Notes in Computer Science, Springer International, Oct. 2019.
  12. Y. Handrianto, R. Huang, and Y. Shang, “TigerAware Assistant: A New Serverless Implementation of Conversational Agents for Customizable Surveys on Smart Devices,” IEEE Transdisciplinary AI Conference, September 2019.
  13. D. Simmons, M. Shah, J. Rogers, C. Rowland, and Y. Shang, “Deep Learning at Your Fingertips,” IEEE Annual Consumer Communications & Networking Conference, January 2019.
  14. W. Morrison, L. Guerdan, J. Kanugo, T. Trull, and Y. Shang, “TigerAware: An Innovative Mobile Survey and Sensor Data Collection and Analytics System,” IEEE International Conference on Data Science in Cyberspace, June 2018.
  15. Z. Peng, W. Wang, B. Balducci, D. Marinova, and Y. Shang, “Toward Predicting Communication Effectiveness,” Proc. IEEE International Conference on Data Science in Cyberspace, June 2018.
  16. Y. Liu, P. Sun, M. Highsmith, N. Wergeles, J. Sartwell, M. Mitchell, A. Raedeke, and Y. Shang, “Performance Comparison of Deep Learning Techniques for Recognizing Birds in Aerial Images,” Proc. IEEE International Conference on Data Science in Cyberspace, June 2018.
  17. A. Cheng, V. Raghavaraju, J. Kanugo, H. Yohanes, and Y. Shang, “Development and evaluation of a Healthy Coping voice interface application using the Google Home for elderly patients with Type 2 Diabetes,” Proc. 15th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2018.
  18. G. Chen, Y. Liu, N. Wergeles, Y. Shang, J. Sartwell, T. Thompson and A. Lewandowski, “Digital Image Vegetation Analysis with Machine Learning,” International Conference on Robotics and Artificial Intelligence, Dec. 2017.
  19. J. Wang, Z. Li, and Y. Shang, “Deep Neural Networks for Evaluating the Quality of a Single Protein Model,” Proc. IEEE International Conference on Tools with Artificial Intelligence, Nov. 2017.
  20. Z. Li, S. Nguyen, D. Xu, and Y. Shang, “Protein Loop Modeling Using Deep Generative Adversarial Networks,” Proc. IEEE International Conference on Tools with Artificial Intelligence, Nov. 2017.
  21. S. Nguyen, Z. Li, and Y. Shang, “Deep Networks and Continuous Distributed Representation of Protein Sequences for Protein Quality Assessment,” Proc. IEEE International Conference on Tools with Artificial Intelligence, Nov. 2017.
  22. C. Fang, Y. Shang, and D. Xu, “A New Deep Neighbor-Residual Neural Network for Protein Secondary Structure Prediction,” Proc. IEEE International Conference on Tools with Artificial Intelligence, Nov. 2017.
  23. G. Chen, P. Sun, and Y. Shang, “AFCS – Automatic Fisheries Classification System Using Deep Learning,” Proc. IEEE International Conference on Tools with Artificial Intelligence, Nov. 2017.
  24. J. Bernstein, B. Mendez, P. Sun, Y. Liu, and Y. Shang, “Using Deep Learning for Alcohol Consumption Recognition,” Proc. IEEE Consumer Communications and Networking Conference, January 2017.
  25. P. Sun, N.M. Wergeles, C. Zhang, L.M. Guerdan, T. Trull, and Y. Shang, “ADA-Automatic Detection of Alcohol Usage for Mobile Ambulatory Assessment." Proc. IEEE International Conference on Smart Computing (SMARTCOMP), May, 2016.
  26. Wergeles, N.M., Shang, C., Peng, Z., Wang, H., Sartwell, J., Treiman, T., Beringer, J., Belant, J.L., Millspaugh, J., McRoberts, J.T. and Shang, Y., “Mobile Data Collection and Analysis in Conservation.” Proc. IEEE International Conference on Smart Computing (SMARTCOMP), May, 2016.
  27. Lander, S.; Yi Shang, “EvoAE -- A New Evolutionary Method for Training Autoencoders for Deep Learning Networks,” Proc. IEEE 39th Annual Computer Software and Applications Conference (COMPSAC), vol.2, no., pp.790-795, July 2015.
  28. Z. Li, J. Adolphe, R. Miranda, and  Y. Shang, “Towards a System to Find Correlations between Geographical Twitter Sentiment and Stock Prices,” Proc. IEEE Consumer Communications and Networking Conference, January 2015.
  29. R. Shi, C. Zhang, H. Wang, P. Sun, T. Trull, and Y. Shang, “mAAS -- A Mobile Ambulatory Assessment System for Alcohol Craving Studies,” in Computer Software and Applications Conference (COMPSAC), 2015 IEEE 39th Annual , vol.3, no., pp.282-287, July 2015.
  30. S. Nguyen, Y. Shang, and D. Xu, “DL-Pro: A Novel Deep Learning Method for Protein Model Quality Assessment,” IEEE International Joint Conference on Neural Networks, July 2014.
  31. D. Wang and Y. Shang, “A New Active Labeling Method for Deep Learning,” IEEE International Joint Conference on Neural Networks, July 2014.
  32. Y. Chen, Y. Shang, and D. Xu, “Multi-Dimensional Scaling and MODELLER-Based Evolutionary Algorithms for Protein Model Refinement,” IEEE Congress on Evolutionary Computation, July 2014.
  33. Z. Ye, X. Su, L. Wu, and Y. Shang, “Optimal Stochastic Media Storage in Federated Cloud Environments,” Proc. IEEE Consumer Communications and Networking Conference, January 2014.
  34. Y. Wang, L. Rui, W. Shi,  D.K. Ho, and Y. Shang, “Localization of An Acoustic Source Using Smart Phones,” Proc. IEEE Consumer Communications and Networking Conference, pp. 761-764, January 2013.
  35. M. Van Devender and Y. Shang, “Wake IQ: Using a Smartphone to Reduce Sleep Inertia,” Proc. IEEE Consumer Communications and Networking Conference, pp. 649-652, January 2013.
  36. P. Baskett, B. Guttersohn, Y. Shang, and W. Zeng, “SDNAN: Software-Defined Networking in Ad hoc Networks of Smartphones,” Proc. IEEE Consumer Communications and Networking Conference, pp. 861-862, January 2013.
  37. P. Baskett, M. Patterson, Y. Shang, and T. Trull, “Towards A System for Body-Area Sensing and Detection of Alcohol Craving and Mood Dysregulation,” Proc. IEEE Consumer Communications and Networking Conference, pp. 875-876, January 2013.
  38. X. Su, B. Schlinker, Y. Shang, and Z. Ye, “Optimal Media Storage in Federated Cloud Environments,” Proc. ICC’12, WS-CloudNetsDataCenters, 2012.
  39. Qia Wang, Alex Lobzhanidze, Hyun I. Jang, Wenjun Zeng and Yi Shang, “Video based Real-world remote target tracking on smartphones,” Proc. IEEE International Conference on Multimedia and Expo, pp.693-698, Melbourne, Australia, July, 2012. 
  40. Q. Wang, A. Lobzhanidze, H. Jang, W. Zeng, Y. Shang, and J. Yang, “Image and video-based remote target localization and tracking on smartphones,” SPIE Geospatial InfoFusion conference, SPIE Defense, Security, and Sensing Symposium, April 2012,  Baltimore, MD.
  41. Y. Shang, W. Zeng, D.K. Ho, D. Wang, Q. Wang, Y. Wang, T. Zhuang, A. Lobzhanidze, and L. Rui, “Nest: NEtworked Smartphones for Target localization,” Proc. IEEE Consumer Communications and Networking Conference, pp. 732-736. January 2012.
  42. K. Ramlakhan and Y. Shang, “A Mobile Automated Skin Lesion Classification System,” Proc. 23th IEEE Int’l Conf. on Tools with Artificial Intelligence, Nov. 2011.
  43. Q. Wang, Y. Shang, and D. Xu, “A Hybrid Consensus and Clustering Method for Protein Structure Selection,” Proc. 23th IEEE Int’l Conf. on Tools with Artificial Intelligence, Nov. 2011.
  44. Q. Wang, A. Lobzhanidze, S. D. Roy, W. Zeng and Y. Shang, “PositionIt – An Image-based Remote Target Localization System on Smartphones,” Proc. ACM Multimedia, Nov. 2011.
  45. Q. Qi and Y. Shang, “Comparing Probabilistic Graphical Model Based and Gaussian Process Based Selections for Temporal Prediction.”  Proc. ANNIE 2010, St. Louis, MO, Nov. 2010.
  46. D. Wang, P. Zhuang, and Y. Shang, “A New Framework for Multi-Source Geo-Social Based Mobile Classifieds Searches.” Proc. ANNIE 2010, St. Louis, MO, Nov. 2010.
  47. Q. Qi, Y. Shang and H. Shi, “An Improved Algorithm for Optimal Subset Selection in Chain Graphical Models.” Proc. IEEE Congress on Evolutionary Computation, Barcelona, Spain, July 2010.
  48. P. Zhuang, D. Wang, and Y. Shang, “SMART: Simultaneous Indoor Localization and Map Construction Using Smartphones.” Proc. International Joint Conference on Neural Networks (IJCNN), Barcelona, Spain, July 2010.
  49. Q. Wang, Y. Shang, and D. Xu, “Protein Structure Selection Based on Consensus.” Proc. IEEE Congress on Evolutionary Computation, Barcelona, Spain, July 2010.
  50. Qingguo Wang, Mian Pan, Yi Shang, Dmitry Korkin, “A Fast Heuristic Search Algorithm for Finding the Longest Common Subsequence of Multiple Strings.” Proc. Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, Georgia, July 2010.
  51. J. Yang, Y. Xu, and Y. Shang, “An Efficient Parallel Algorithm for Longest Common Subsequence Problem on GPUs.” World Congress on Engineering, London, UK, June 2010.
  52. B. Barz, Q. Wang, J. Zhang, Z. He, D. Xu, Y. Shang, I. Kosztin, “Selection of Near-Native Protein Structures by Means of Molecular Dynamics Simulations.” Biophysical Society Meeting, 2010.
  53. P. Zhuang, D. Wang, and Y. Shang, “Distributed Faulty Sensor Detection.” Proc. IEEE Globecom, Dec. 2009.
  54. P. Zhuang and Y. Shang. “Vehicle Localization from Wireless Traffic Sensors.” Mobile Entity Localization and Tracking in GPS-less Environnments Workshop (MELT), Sept. 2009.
  55. P. Zhuang, D. Wang, and Y. Shang, “Distributed Distribution-based Optimization for Sensor Fault Detection.” IEEE 52nd MWSCAS, Aug, 2009.
  56. Q. Wang, D. Korkin, and Y. Shang, "Efficient Dominant Point Algorithms for the Multiple Longest Common Subsequence (MLCS) Problem", 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 1494-1500, July 2009.
  57. P. Zhuang and Y. Shang, “Cobra: Correlation-based content authentication in wireless sensor networks,” Proc. IEEE Globecom, New Orleans, Dec. 2008.
  58. X. Li, B. Hua, Y. Shang, Y. Guo, and L. Yue, “Bilateration: An attack-resistant localization of Wireless Sensor Network", Proc. IFIP International Conference on Embedded and Ubiquitous Computing, pp. 321-332, Dec. 2008.
  59. D. Korkin, Q. Wang, and Y. Shang, “An Efficient Parallel Algorithm for the Multiple Longest Common Subsequence Problem,” Proc. 37th Int’l Conf. on Parallel Processing, pp. 354 – 363, Portland, OR, Sept. 2008.
  60. I. Almosallam and Y. Shang, “A New Adaptive Framework for Collaborative Filtering Prediction,” Proc. IEEE Congress on Evolutionary Computation, pp. 2725 – 2733, Hong Kong, June 2008.
  61. Q. Wang, Y. Shang, and D. Xu, “A New Clustering-based Method for Protein Structure Selection,” in Proc. IEEE Int’l Joint Conf. on Neural Networks, pp. 2891 – 2898, Hong Kong, June 2008.
  62. A. Ahmed, H. Shi, and Y. Shang, “Adaptive Localization in Wireless Sensor Networks: An Experimental Study,” Proc. 21st International Conference on Parallel and Distributed Computing and Communication Systems (PDCCS-2008)}, New Orleans, May 2008.
  63. X. Li, H. Shi, and Y. Shang, ``Selective Anchor Placement Algorithm for Ad-hoc Wireless Sensor Networks,'' Proc. IEEE International Conference on Communications (ICC 2008), Beijing, China, May 2008.
  64. P. Zhuang, Q. Qi, Y. Shang, and H. Shi, “Model-Based Traffic Prediction Using Sensor Networks,” Proc. IEEE Consumer Communications and Networking Conference, Las Vegas, NV, January 2008.
  65. M. Tubaishat, Q. Qi, Y. Shang, and H. Shi, “Wireless Sensor-Based Traffic Light Control,” Proc. IEEE Consumer Communications and Networking Conference, Las Vegas, NV, January 2008.
  66. X. Li, A. Ahmed, H. Shi, and Y. Shang, ``A Systematic Evaluation of RangeQ-based Localization Algorithms in Wireless Sensor Networks,'' Proc. 6th WSEAS International Conference on Circuits, Systems, Electronics, Control, and Signal Processing (CSECS'07), pages 119-124, Cairo, Egypt, December 2007.
  67. Y. Shang, R. Bondugula, D. Xu, and Q. Wang. “A New Method for Protein Tertiary Structure Prediction,” Proc. IASTED Int’l Conf. on Computational Intelligence, Banff, Canada, July, 2007.
  68. B. Yin, H. Shi, Y. Shang, and D. Ma. “Adaptive Clustering and Transmission Range Adjustment in Wireless Sensor Networks,” Proc. IASTED Int’l Conf. on Communications, Internet, and Information Technology, Banff, Canada, July, 2007.
  69. P. Zhuang, Q. Wang, Y. Shang, H. Shi, and B. Hua. “Wireless Sensor Network Aided Search and Rescue in Trails,” Proc. Int’l Conference on Scalable Information Systems, Suzhou, China, June. 2007.
  70. B. Yin, H. Shi, and Y. Shang, “Analysis of Energy Consumption in Clustered Wireless Sensor Networks,” Proc. IEEE Int’l Symposium on Wireless Pervasive Computing, San Juan, Puerto Rico, Feb. 2007.
  71. P. Zhuang, Q. Wang, Y. Shang, and H. Shi, “Minimizing Location Uncertainty in Access Points Deployment,” Proc. IEEE Int’l Symposium on Wireless Pervasive Computing, San Juan, Puerto Rico, Feb. 2007.
  72. A. Ahmed, H. Shi, and Y. Shang, “Map-based Adaptive Positioning in Wireless Sensor Networks,” Proc. IEEE Int’l Symposium on Wireless Pervasive Computing, San Juan, Puerto Rico, Feb. 2007.
  73. B. Yin, H. Shi, and Y. Shang, “An Efficient Algorithm for Constructing Connected Dominating Set in Ad Hoc Networks,” Proc. IEEE Consumer Communications and Networking Conference, Las Vegas, NV, January 2007.
  74. M. Tubaishat, Y. Shang, and H. Shi, “Adaptive Traffic Light Control with Wireless Sensor Networks,” Proc. IEEE Consumer Communications and Networking Conference, Las Vegas, NV, January 2007.
  75. Q. Wang and Y. Shang, “Optimal Access Point Placement for Target Localization along Trails,” Proc. IEEE Consumer Communications and Networking Conference, Las Vegas, NV, January 2007.
  76. R. Bondugula, D. Xu, and Y. Shang. “A Fast Algorithm for Low-Resolution Protein Structure Prediction”, Proc. Int’l Conf. of the Engineering in Medicine and Biology Society, New York City, New York, USA, August-Sept, 2006.
  77. P. Zhuang, Y. Shang, and H. Shi, “Sensor Network Assisted Collaboration for Pursuit-Evasion Problem,” Proc. IEEE Int’l Conf. on Pervasive Services, Lyon, France, June 2006.
  78. A. Ahmed, Y. Shang, and H. Shi, “A New Hybrid Wireless Sensor Network Localization System,” Proc. IEEE Int’l Conf. on Pervasive Services, Lyon, France, June 2006.
  79. S. Selvakennedy, S. Sinnappan, and Y. Shang, “Data Dissemination Based on Ant Swarms for Wireless Sensor Networks,” Proc. IEEE Consumer Communications and Networking Conference, Las Vegas, NV, January 2006.
  80. A. Ahmed, H. Shi, and Y. Shang, “Adaptive Localization in Wireless Sensor Networks,” 2nd IEEE Int’l Workshop on Adaptive Wireless Networks of the IEEE Globecom 2005, St. Louis, MO, Dec, 2005.
  81. B. Yin, H. Shi, and Y. Shang, “An Efficient Single-Phase Distributed Algorithm for Constructing Connected Dominating Set in Ad Hoc Networks,” 2nd IEEE Int’l Workshop on Adaptive Wireless Networks of the IEEE Globecom 2005, St. Louis, MO, Dec, 2005.
  82. P. Zhuang, Y. Shang, and H. Shi, “A New Distributed Planning Method for Pursuit-Evasion Game Using Sensor Networks,” 2nd IEEE Int’l Workshop on Adaptive Wireless Networks of the IEEE Globecom 2005, St. Louis, MO, Dec, 2005.
  83. H. Shi, X. Li, Y. Shang, and D. Ma, “Cramer-Rao Bound Analysis of Quantized RSSI Based Localization in Wireless Sensor Networks,” Proc. IEEE/IFIP Int’l Workshop on Parallel and Distributed Embedded Systems (PDES-05), Fukuoka, Japan, July 2005.
  84. B. Yin, H. Shi, and Y. Shang, “A Two-level Strategy for Topology Control in Wireless Sensor Networks,” Proc. 1st IEEE Inte’l Workshop on Heterogeneous Wireless Sensor Networks (HWISE 2005), Fukuoka, Japan, July 2005.
  85. Y. Shang and H. Shi, “Coverage and Energy Tradeoff in Density Control on Sensor Networks,” Proc. 11th IEEE Int’l Conf. Parallel and Distributed Systems (ICPADS 2005), Fukuoka, Japan, July 2005.
  86. A. Ahmed, Y. Shang, and H. Shi, “Variants of Multidimensional Scaling for Node Localization,” Proc. 11th IEEE Int’l Conf. Parallel and Distributed Systems (ICPADS 2005), Fukuoka, Japan, July 2005.
  87. X. Li, H. Shi, and Y. Shang, ``A Sorted RSSI Quantization Based Algorithm for Sensor Network Localization,” Proc. 11th IEEE Int’l Conf. Parallel and Distributed Systems (ICPADS 2005), Fukuoka, Japan, July 2005.
  88. A. Ahmed, H. Shi, and Y. Shang, “SHARP: A New Approach to Relative Localization in Wireless Sensor Networks,” Proc. 2nd IEEE International Workshop on Wireless Ad Hoc Networking (WWAN 2005), Columbus, OH, June 2005.
  89. Y. Shang, J. Shen, and H. Shi, “A New Density Control Algorithm for Sensor Networks,” 1st IEEE Int’l Workshop on Embedded Networked Sensors, Nov. 2004.
  90. X. Li, H. Shi, and Y. Shang, “A Partial-Range-Aware Localization Algorithm for Ad Hoc Wireless Sensor Networks,” 29th Annual IEEE Int’l Conf. on Local Computer Networks, Nov. 2004.
  91. Y. Shang, H. Shi, and A. A. Ahmed, “Performance Study of Localization Methods in Ad Hoc Sensor Networks,” 1st IEEE Int’l Conf. on Mobile Ad-hoc and Sensor Systems, Oct. 2004.
  92. X. Li, H. Shi, and Y. Shang, “A Map-Growing Localization Algorithm for Ad Hoc Wireless Sensor Networks,” IEEE Int’l Conf. on Parallel and Distributed Systems (ICPADS), July 2004.
  93. H. Liu, H. Shi, Y. Shang, and S. Chen, “Student Modeling with Timed Assessment Information,” IEEE Int’l Conf. on Information Technology: Research and Education, London, England, June 2004.
  94. X. Su, Yi Shang, and Y. Mai, “Delay-Sensitive Delivery of Scalable Coded Images Over Peer-to-Peer Networks,” IEEE Int’l Conf. on Multimedia and Expo (ICME), Taipei, Taiwan, June 2004.
  95. X. Su and Y. Shang, “Error Concealment of Transform Coded Images with Continuous QoS,” IEEE Int’l Conf. on Information Technology: Coding & Computing (ITCC), Las Vegas, NV, April 2004.
  96. Y. Shang, J. Meng, and H. Shi, “Relative Localization in Wireless Sensor Networks,” IEEE Int’l Parallel and Distributed Processing Symposium (IPDPS), April 2004.
  97. Y. Shang and W. Ruml, “Improved MDS-Based Localization,” IEEE Infocom, Hong Kong, March 2004.
  98. Y. Shang, W. Ruml, M.  Fromherz, and Y. Zhang, “Localization from mere connectivity,” 4th ACM Int’l Symposium on Mobile Ad Hoc Networking and Computing (ACM MobiHoc), pp. 201-212, Annapolis, Maryland, June 2003.
  99. Y. Shang, M. Fromherz, Y. Zhang, and L. Crawford, “Constraint-based routing for ad-hoc networks,” IEEE Int’l Conf. on Information Technology: Research and Education (ITRE), pp. 306-310, Newark, NJ, August 2003 (invited paper).
  100. A. Ahmed, H. Shi, and Yi Shang, “A Survey on Routing Protocols for Wireless Sensor Networks,” IEEE Int’l Conf. on Information Technology: Research and Education (ITRE), pp. 301-305, Newark, NJ, August 2003 (invited paper).
  101. H. Liu, H. Shi, Y. Shang, and S. Chen, “SAM: A Student Assessment and Modeling System,” Int’l Conf. on Artificial Intelligence (IC-AI’03), Las Vegas, Nevada, June, 2003.
  102. L. Li, Y. Shang, W. Zhang, and H. Shi, “A General Method for Statistical Performance Evaluation,” Hawaii Int'l Conference on System Sciences (HICSS-36), Hawaii, Jan. 2003.
  103. L. Li, Y. Shang, W. Zhang, and H. Shi, “Fuzzy Logic for Search Engine Ranking,” 12th Int'l Conference on Artificial Neural Networks In Engineering (ANNIE 2002), St. Louis, MO, Nov. 2002.
  104. L. Li, Y. Shang, H. Shi, and W. Zhang, “Performance Evaluation of HITS-based Algorithms,” Proc. IASTED Int’l Conf. on Communications, Internet, and Information Technology (CIIT 2002), St. Thomas, Virgin Islands, Nov. 2002.
  105. Y. Shang, M. Fromherz, and Y. Zhang, “Developing Efficient Cooperative Solvers for Constrained Optimization,” Workshop on Cooperative Solvers in Constraint Programming, 8th Int’l Conf. on Principles and Practice of Constraint Programming (CP’02), Ithaca, Sep. 2002.
  106. Y. Zhang, M. Fromherz, L. Crawford, and Y. Shang, “A General Constraint-based Control Framework with Examples in Modular Self-reconfigurable Robots,” IEEE/RSJ Conf. on Intelligent Robots and Systems (IROS 2002), Lausanne, Switzerland, Sep. 2002
  107. Y. Shang, M.  Fromherz, and L. Crawford, “An Efficient Cooperative Solver for Nonlinear Continuous Constraint Problems,” Int’l Congress of Mathematical Software (ICMS’02), Beijing, China, August 2002.
  108. Y. Shang, M. Fromherz, and L. Crawford, “Solving Nonlinear Continuous Constraint Problems,” Int’l Congress of Mathematicians (ICM'02), Short Communication, Beijing, China, August 2002.
  109. O. Rodriguez, S. Chen, H. Shi, and Y. Shang, “Open Learning Objects: the case for inner metadata,” 11th Int'l World Wide Web Conference (WWW2002)), May 2002.
  110. L. Li, Y. Shang, and W. Zhang, “Improvement of HITS-based Algorithms on Web Documents,” 11th Int'l World Wide Web Conference (WWW2002), May 2002.
  111. M. Fromherz, L. Crawford, C. Guettier, and Y. Shang, “Distributed Adaptive Constrained Optimization for Smart Matter Systems,” 2002 AAAI Spring Symposium on Intelligent Embedded and Distributed Systems, March 2002.
  112. L. Crawford, M. Fromherz, C. Guettier, and Y. Shang, “A Framework for On-line Adaptive Control of Problem Solving,” Workshop on On-line Combinatorial Problem Solving and Constraint Programming, 7th Int’l Conf. on Principles and Practice of Constraint Programming (CP’01), Paphos, Cyprus, 2001.
  113. Y. Shang, Y. Wan, M. P.J. Fromherz, and L. Crawford, “Combining Global and Local Search in Solving Continuous Constraint Problems,” Workshop on Cooperative Solvers in Constraint Programming, 7th Int’l Conf. on Principles and Practice of Constraint Programming (CP’01), Paphos, Cyprus, 2001.
  114. Y. Shang, M. Fromherz, T. Hogg, and W. Jackson, “Complexity of Continuous, 3-SAT-like Constraint Satisfaction Problems,” IJCAI-01 Workshop on Stochastic Search Algorithms, pp. 49-54, Seattle, WA, 2001.
  115. M. P. J. Fromherz, T. Hogg, Y. Shang, and W. B. Jackson, “Modular Robot Control and Continuous Constraint Satisfaction,” IJCAI-01 Workshop on Modeling and Solving Problems with Constraints, pp. 47-56, Seattle, WA, 2001.
  116. H. Shi, Y. Shang, and F. Ren, “Using Natural Language to Access Databases on the Web,” IEEE Int’l Workshop on Natural Language processing and Knowledge Engineering (NLPKE 2001) in conjunction with the IEEE SMC' 2001, Tucson, Arizona, 2001.
  117. S. Chen, O. Rodriguez, C. Choo, Y. Shang, and H. Shi, “Personalizing Digital Libraries for Learners," 12th Int’l Conf. On Database and Expert Systems Applications (DEXA'2001), Munich, Germany, 2001.
  118. Y. Shang, H. Shi, and S. Chen, “An Intelligent Distributed Environment for Active Learning,” Proc. 10th Int'l World Wide Web Conference (WWW10), Hong Kong, May 2001.
  119. L. Li and Y. Shang, “Approximate ranking of Web Searching Engines,” Proc. 10th Int'l World Wide Web Conference (WWW10), Hong Kong, May 2001.
  120. H. Shi, Y. Shang, and S. Chen, “Smart Instructional Component Based Course Content Organization and Delivery,” Proc. 6th Annual Conf. on Innovation and Technology in Computer Science Education, ITiCSE 2001, Canterbury, UK, June, 2001.
  121. H. Shi, Y. Shang, and S. Chen, “TIGERMU: a Tightly Integrated General Environment for Resource Management and Utilization,” (Invited paper), Proc. 1st Int'l Conf. on Information (Information'2000), pp. 17-24, Fukuoka, Japan, October 2000.
  122. L. Li and Y. Shang, “A New Statistical Method for Evaluating Search Engines,” Proc. IEEE 12th Int'l Conf. on Tools with Artificial Intelligence, pp. 208-215, Vancouver, British Columbia, Canada, 2000.
  123. Y. Shang, L. Li, and K. C. Ho, “Optimization Design of Filter Banks For Wavelet Denoising,” Proc. 5th Int'l Conf. on Signal Processing (ICSP), IFIP 16th World Computer Congress, Beijing, China, August 2000.
  124. Y. Shang and H. Shi, “IDEAL: An Integrated Distributed Environment for Asynchronous Learning,” Proc. ACM Workshop on Distributed Communities on the Web, Lecture Notes in Computer Science, Vol. 1830, pp. 182-191, 2000.
  125. H. Shi, Y. Shang, M. Jurczyk, and A. Joshi, “Laboratory-Oriented Teaching in Web and Distributed Computing,” Proc. ASEE's 2000 Annual Conference, St. Louis, June, 2000.
  126. Y. Shang, H. Shi, and S. Chen, “Agent Technology in Computer Science and Engineering Curriculum,” Proc. 5th Annual Conf. on Innovation and Technology in Computer Science Education, ITiCSE 2000, Helsinki, Finland, pp. 120-123, July, 2000.
  127. H. Shi, Y. Shang, and S. Chen, “A Multi-Agent System for Computer Science Education,” Proc. 5th Annual Conf. on Innovation and Technology in Computer Science Education, ITiCSE 2000, Helsinki, Finland, pp. 1-4, July, 2000.
  128. M. Popescu and Y. Shang, “An Agent Framework for Automated Radiology Test,” Proc. Parallel and Distributed Methods for Image Processing, SPIE Int'l Symposium on Optical Science, Engineering and Instrumentation, July 2000.
  129. C. Sapp and Y. Shang, “Intelligent Web Representatives,” Proc. IEEE 11th Int'l Conference on Tools with Artificial Intelligence, pp. 85-88, Nov. 1999.
  130. M. Popescu and Y. Shang, “An Agent-Based Approach for Interpreting Medical Images,” Proc. IEEE 11th Int'l Conference on Tools with Artificial Intelligence, pp. 129-130, Nov. 1999.
  131. Y. Shang and L. Li, “Intelligent Agents for Designing Filter Banks in Image Compression,” Proc. Parallel and Distributed Methods for Image Processing, SPIE Int'l Symposium on Optical Science, Engineering and Instrumentation, pp. 98-107, July 1999.
  132. Y. Shang and L. Li, “Optimization Design of Filter Banks in Subband Image Coding,” Proc. IEEE Symposium on Application-Specific Systems and Software Engineering and Technology, pp. 112-119, March 1999.
  133. Y. Shang and B. W. Wah, “Improving the Performance of Discrete Lagrange-Multiplier Search for Solving Hard SAT Problems,” Proc. IEEE 10th Int'l Conference on Tools with Artificial Intelligence, pp. 176-183, Nov. 1998.
  134. Y. Shang and B. W. Wah, “A New Global-Search Method for Designing Filter Banks,” Proc. Parallel and Distributed Methods for Image Processing II, SPIE Int'l Symposium on Optical Science, Engineering and Instrumentation, pp. 94-105, July 1998.
  135. B. W. Wah, Y. Shang, and Z. Wu,  “Discrete Lagrangian Method for Optimizing the Design of Multiplierless QMF Filter Banks,” IEEE Int'l Conf. on Application-Specific Systems, Architectures and Processors, pp. 529-538, July, 1997.
  136. B. W. Wah, Y. Shang, T. Wang, and T. Yu, “QMF Filter Bank Design by a New Global Optimization Method”, Proc. IEEE Int'l Conf. on Acoustics, Speech and Signal Processing, vol. 3, pp. 2081-2084, April 1997.
  137. B. W. Wah, T. Wang, Y. Shang, and Z. Wu, “Improving the Performance of Weighted Lagrange-Multiplier Methods for Constrained Nonlinear Optimization,” Proc. 9th Int'l Conference on Tools with Artificial Intelligence, IEEE, pp. 224-231, Nov. 1997.
  138. B. W. Wah, Y. Shang, T. Wang, and T. Yu, “Global Optimization Design of QMF Filter Banks”, Proc. IEEE Midwest Symposium on Circuits and Systems, August 1996.
  139. Y. Shang and B. W. Wah, “A Global Optimization Method for Neural Network Training”, Proc. 1996 IEEE Int'l Conf. on Neural Networks (Plenary, Panel and Special Sessions), pp. 7-11, June 1996.
  140. B. W. Wah and Y. Shang, “Discrete Lagrangian-Based Search for Solving MAX-SAT Problems,” Proc. 15th Int'l Joint Conf. on Artificial Intelligence, pp. 378-383, Aug. 1997.
  141. B. W. Wah and Y. Shang, “A Comparative Study of IDA*-Style Searches,” Proc. 6th Int'l Conference on Tools with Artificial Intelligence, IEEE, Nov. 1994, pp. 290-296.
  142. Y. Shang and G-J Li, “New Crossover Operators In Genetic Algorithms,” Proc. 3rd Int'l Conference on Tools for Artificial Intelligence, IEEE, Nov. 1991, pp.150--153.

 

Patents

  1. Y. Zhang, M. Fromherz, L. Crawford, Y. Shang, “Protocol Specification for Message-Initiated Constraint-Based Routing”, US Patent 7,577,107, August 18, 2009.
  2. Y. Zhang, M. Fromherz, Y. Shang, S. Vassilvitskii, L. Crawford, “Learning-Based Strategies for Message-Initiated Constraint-Based Routing”, US Patent 7,577,108, August 18, 2009.
  3. Y. Zhang, M. Fromherz, S. Vassilvitskii, Y. Shang, “Time-aware Strategy for Message-Initiated Constraint-Based Routing”, US Patent 7,486,627, February 3, 2009.
  4. Y. Shang and Wheeler Ruml, “Node Localization in Communication networks”, US Patent 7,457,860, November 25, 2008.
  5. M. Fromherz, Y. Shang, L. Crawford, “Complexity-Directed Cooperative Problem Solving”, US Patent 7,089,220, Aug. 8, 2006.
  6. M. Fromherz, L. Crawford, Y. Shang, “Feedback Control of Problem Solving”, US Patent 7,089,221, Aug. 8, 2006.