Dissemination

1. Nobel A**, Fang H⁺, Jacob M*, Wang H. A Digital Twins Prototype for Monitoring and Predicting Dynamic Diet-related Health Conditions. ISMB/ECCB 2025 NIH Special Track on Cyberinfrastructure and Emerging Technologies in Biomedical Research. Liverpool, United Kingdom. (Accepted)
2. S. Lomasov**, H. Fang⁺, and H. Wang. (2025). Federated Choquet Regression with LASSO for Outcome Prediction in Multisite Longitudinal Clinical Trial Data. ACM Transactions on Computing for Healthcare (Accepted) 
3. Fried M**, Wang H, Fang H⁺. Feature Interaction Detection in Big Data Through a New Choquet Integral based Deep Neural Network. Proc IEEE Int Conf Big Data. 2024 Dec;2024:700-708. doi: 10.1109/bigdata62323.2024.10825719. Epub 2025 Jan 16. PMID: 40291853; PMCID: PMC12033041.
4. Liu D**, Wang H, Xiang X*, Fang H⁺. Chapter 1.11. Digital Twin in Healthcare and Medical Field: A Review. In: Chen CH, ed. Computational Intelligence and Image Processing for Medical Applications. DOI: 10.1142/9789819807154_0011.(Accepted)
5. Nobel A**, Fang H⁺, Wang H. Smart Ring Based Digital Twin for Healthcare Application. INFOCOM 2025, London, UK, May 2025 (Accepted). (Best Poster Award)   
6. Fried M**, Wang H, Fang H⁺. Adaptive Eigen-Analysis Using Game-Theoretic Strategies for Multi-Scale CNNs in Medical Imaging.   IEEE/ACM Conference on Connected Health: Applications, Systems, and Engineering Technologies (CHASE), New York, USA, Jun. 2025. (Accepted, regular).
7. Matos J*, Ngo H*, Wang H, Fang H⁺. xR-enabled Digital Twins Applications in Longitudinal Trials.  IEEE/ACM Conference on Connected Health: Applications, Systems, and Engineering Technologies (CHASE), New York, USA, Jun. 2025. (Accepted).
8. D Liu, M Ma, H Fang, Honggang Wang, PolypSEAG-Net: Enhanced Polyp Segmentation with Attention, 
   Gates and Squeeze-and-Excitation, ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE '25), June, 2025, New York, NY, USA (accepted)
9. Fried M**, Wang H, Fang H⁺. Adaptive Heatmaps for Medical Imaging in CNNs.   in Proc. 47th IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, Jul. 2025.   (Accepted).
10. Liu D**, Wang H, Fang H⁺. Fuzzy Deep Neural Network for Health Info Prediction. in Proc. 47th IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, Jul. 2025.   (Accepted).
11. Nobel A**, Fang H⁺, Wang H. Contextual Representation of Longitudinal Biomarker and Dietary Data with Missing Info. Session on "Advances in generative models” Joint Statistical Meetings (JSM); American Statistical Association. JSM 2025, ASA, Aug 2025 (Accepted)
12. Liu D**, Wang H, Fang H⁺. Adaptive Neural-Fuzzy Rule Generation with Attention for Anthropometric Prediction. Session on “Machine learning for biomedical applications and time-to-event data”, JSM 2025, ASA, Aug 2025 (Accepted).
13. M. B. Mollah**, H. Wang, M. A. Karim and H. Fang⁺, "Multi-Modality Sensing in mmWave Beamforming for Connected Vehicles Using Deep Learning," in IEEE Transactions on Cognitive Communications and Networking, doi: 10.1109/TCCN.2025.3558026. 

1. H Ngo^*,H Fang⁺ , H Wang. AI-enabled Fuzzy Clustering in Longitudinal Digital Trials. Session “Time Series Analysis and Forecasting”, Section on Statistical Learning and Data Science. 2024 Joint Statistical Meetings (JSM). American Statistical Association, 2024. 
2. S Bruendl*, H Fang⁺, H Wang.Electrodermal activity based on-device machine learning for multidimensional substance use data streams. Session “Advances in Machine Learning”, Section on Statistical Learning and Data Science. 2024 Joint Statistical Meetings (JSM). American Statistical Association, 2024. 
3. M Fried**, H Wang, H Fang⁺, A New Choquet Activation Function Based Deep Neural Network for Drug Interaction Detection. Session “Deep Learning Models and Techniques”. Section on Statistical Learning and Data Science. 2024 Joint Statistical Meetings (JSM). American Statistical Association, 2024.
4. S Semyon^**,H Wang, H Fang⁺. Federated Multidimensional Choquet Classification for Outcome Prediction in Longitudinal Trial Data. Session “Time Series Analysis and Forecasting”, Section on Statistical Learning and Data Science. 2024 Joint Statistical Meetings (JSM). American Statistical Association, 2024. 
5. H Ngo*, H Fang⁺, J.Rumbut*, S Bruendl*, H Wang, M Wang, L Steffen, J Shikany, J Allison, M Rosal, K Catarina, A Ash. Privacy-Focused Federated Fuzzy Clustering for Incomplete Longitudinal Behavioral Data, Section on Innovative Methods in Health Services Research, 2024 Annual Research Meeting, AcademyHealth, Baltimore, MD.
6. M. Fried**, H. Wang and H. Fang, "A Choquet-Integral Based Approach To Identify Weight Loss Component Subsets," 2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Wilmington, DE, USA, 2024, pp. 202-203, doi: 10.1109/CHASE60773.2024.00039.
7. M. B. Mollah**, H. Wang and H. Fang, "Position Aware 60 GHz mmWave Beamforming for V2V Communications Utilizing Deep Learning," ICC 2024 - IEEE International Conference on Communications, Denver, CO, USA, 2024, pp. 4711-4716, doi: 10.1109/ICC51166.2024.10622582.
8. L. Song, W. Valentine, Q. Yang, H. Wang, H. Fang and Y. Liu, "BB-Align: A Lightweight Pose Recovery Framework for Vehicle-to-Vehicle Cooperative Perception," 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS), Jersey City, NJ, USA, 2024, pp. 1016-1026, doi: 10.1109/ICDCS60910.2024.00098.

1. H Ngo^*, H Fang⁺, J.Rumbut^*, H Wang. Federated fuzzy clustering for decentralized incomplete longitudinal behavioral data. IEEE Internet of Things Journal. DOI: 10.1109/JIOT.2023.3343719. NIHMSID:1952709
2. H Ngo^*,H Fang⁺ , H Wang. Federated fuzzy clustering for decentralized longitudinal behavioral trial data. Session “Methods for Time Series and Longitudinal Data”, Section on Statistical Learning and Data Science. 2023 Joint Statistical Meetings (JSM). American Statistical Association, 2023. 
3. J. Rumbut^*, H. Fang⁺, E. Boyer and H. Wang, Precision polysubstance use episode detection in wearable biosensor data streams, 2023 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Orlando, FL. DOI: 10.1145/3580252.3586989
4. MB Mollah^**, H Wang, MA Karim, H Fang⁺, mmWave Enabled Connected Autonomous Vehicles: A Use Case with V2V Cooperative Perception. IEEE Network Magazine. DOI: 10.1109/MNET.2023.3321520
5. H. Ngo^*, H. Fang⁺ and H. Wang, "Cooperative Perception With V2V Communication for Autonomous Vehicles," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2023.3264020.

1. H Ngo*, H Fang⁺, H Wang. Intelligent fuzzifier-based cluster validation for incomplete longitudinal digital trial data. IEEE/ACM Conference on Connected Health Applications, Systems, and Engineering Technologies (IEEE/ACM CHASE 2022). ISBN: 978-1-4503-9476-5
2. SV Balkus*, Fang H⁺, Wang H. Federated Fuzzy Clustering for Longitudinal Health Data.  IEEE/ACM Conference on Connected Health Applications, Systems, and Engineering Technologies (IEEE/ACM CHASE 2022). ISBN:978-1-4503-9476-5
3. CS Mahabal**, H Fang+, H Wang, On-Ramp Merging for Connected Autonomous Vehicles using Deep Reinforcement Learning. The 15^th IEEE International Conference on Internet of Things (iThings-2022), DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics55523.2022.00048.
4. H Fang, H Wang. Chapter 1.2. Intelligent behavioral trajectory pattern recognition for longitudinal trials. Computational Intelligence and Image Processing for Medical Applications, C.H. Chen (Ed). DOI: 10.1142/9789811257452_0002
5. CS Mahabal**  H Wang, HFang⁺, Dual Mode Localization Assisted Beamforming for mmWave V2V Communication. IEEE Transactions on Vehicular Technology. DOI: 10.1109/TVT.2022.3175165
6. VS Gurugubelli^*, H Fang⁺, JM Shikany, SV Balkus^*, J Rumbut^*, HX Ngo^*, H Wang, JJ Allison, LM Steffen. A review of harmonization methods for studying dietary patterns. Elsevier. Vol 23. Available online 13 January 2022.DOI: 10.1016/j.smhl.2021.100263. NIHMS1779312.
7. J Rumbut^*, H Fang⁺, S Carreiro, D Smelson, E Boyer, An overview of wearable biosensor systems for real-time substance use detection. IEEE Internet of Things Journal. 9(23), 23405 - 23415, DOI: 10.1109/JIOT.2022.3207090.
8. SV Balkus^*, H Wang, BD Cornet^*, CS Mahabal^**, HX Ngo^*, H Fang⁺,A Survey of Machine Learning Methods for 5G Vehicle-to-Vehicle Communications. IEEE Communications Surveys & Tutorials. (IF: 25.249) DOI: 10.1109/COMST.2022.3149714

2021

1. S Bruendl*, H Fang⁺, H Wang, EW Boyer. EDA-based data stream pattern analysis and peak detection algorithm for substance users. 2021 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). DOI: 10.1109/CHASE52844.2021.00017
2. CS Mahabal**, H Fang⁺, H Wang, Q Yang. Adaptive Vehicle Platooning With Joint Network-Traffic Approach. GLOBECOM2021. DOI: 10.1109/GLOBECOM46510.2021.9685116
3. SV Balkus^*, H Fang⁺, J Rumbut^*, A Moormann, E Boyer, A multi-level biosensor-based epidemic simulation model for COVID-19. IEEE Internet of Things Journal. DOI: 10.1109/JIOT.2021.3127804
4. H Fang, Patent “System and methods for trajectory pattern recognition”, US20160358040A1, issued on June 1st, 2021. 
5. HX Ngo^*, H Fang⁺, H Wang. Beamforming and scalable image processing in vehicle-to-vehicle Networks. Journal of Signal Processing Systems. Springer. DOI: 10.1007/s11265-021-01696-6
6. SV Balkus^*,H Fang⁺, Multi-Level Biosensor-Based Epidemic Forecasting in Small Areas. Section on Statistical Learning and Data Science. 2021 Joint Statistical Meetings (JSM). American Statistical Association, 2021.
7. Yang Q, Fu S, Wang H, Fang H. Machine learning enabled cooperative perception for connected autonomous vehicles: Challenges and Opportunities. IEEE Network Magazine. DOI: 10.1109/MNET.011.2000560
8. BD Cornet^*, H Fang⁺, HX Ngo^*, EW Boyer, H, Wang. An Overview of wireless body area networks for mobile health applications. IEEE Network Magazine. DOI: 10.1109/MNET.103.2000761

2020

1. J Rumbut*, Fang H⁺, Wang H. Topic modeling for systematic review of visual analytics in incomplete longitudinal behavioral trial data. Smart Health. Elsevier. 2020 Nov;18:100142. doi: 10.1016/j.smhl.2020.100142. Epub 2020 Nov 13. PMCID: PMC7745978. NIHMSID: 1649927.
2. BD Cornet*, H Fang⁺, H, Wang. Overview of quantum technologies, standards, and applications in mobile devices. ACMGetMobile. 2021, 24(4), 5-9. doi:10.1145/3457356.3457358.
3. HX Ngo*, H Fang⁺, H Wang. Deep Learning-based adaptive beam forming for 5G mmWave Wireless body area network. GLOBECOM2020. doi: 10.1109/GLOBECOM42002.2020.9322515 (Best Paper Award)
4. CS Mahabal**, H Fang⁺, H Wang, Smart Spectrum Switching and Beamforming for Wireless Body Area Networks in Dynamic Environment. GLOBECOM2020. DOI: 10.23919/JCIN.2020.9130436
5. SV Balkus*, J Rumbut*, H Wang H Fang⁺. An Adaptive and dynamic biosensor epidemic model for COVID19.  21st IEEE International Conference on Information Reuse and Integration. IEEE IRI 2020. DOI: 10.1109/IRI49571.2020.00051
6. S Bruendl*, H Fang⁺, HX Ngo*, EW Boyer H Wang. A new emulation platform for real-time machine learning in substance use data stream.  21st IEEE International Conference on Information Reuse and Integration. IEEE IRI 2020. DOI: 10.1109/IRI49571.2020.00054
7. MD N Anjum, H Wang, HFang, "Prospects of 60 GHz mmWave WBAN: A PHY-MAC Joint Approach," IEEE Transactions on Vehicular Technology. 69(6), 6153-6164. 2020. DOI: 10.1109/TVT.2020.2978332.
8. J Rumbut*, H Fang⁺, Towards an Adaptive Algorithm for Online Substance Use Episode Detection, Section on Statistical Learning and Data Science. 2020 Joint Statistical Meetings (JSM). American Statistical Association, 2020.
9. VS Gurugubelli^*, H Fang⁺, Validation of Neuro-Fuzzy based classifiers for outcome from longitudinal RCT, Section on Statistical Learning and Data Science. 2020 Joint Statistical Meetings (JSM). American Statistical Association, 2020.
10. S Bruendl^*, H. Fang⁺, Making the Switch to 5G and 60GHz in mHealth applications using USRP hardware, IEEE Internet Computing. 24(2). 57-64. doi: 10.1109/MIC.2019.2962797
11. J Rumbut^*, H Fang⁺, S Carreiro, D Smelson, B Chapman, E Boyer, H Wang. Harmonizing wearable biosensor data streams to test polydrug detection. In 2020 International Conference on Computing, Networking and Communications (ICNC): Cloud Computing and Big Data.DOI: 10.1109/ICNC47757.2020.9049684
12. MD N Anjum, H Wang, H Fang. Coverage Analysis of Random UAV Networks Using Percolation Theory. In 2020 International Conference on Computing, Networking and Communications (ICNC): Network Algorithms and Performance Evaluation. DOI: 10.1109/ICNC47757.2020.9049663

1. H Fang. Data analytics for longitudinal biomedical data. Encyclopedia of Wireless Networks. DOI: 10.1007/978-3-319-78262-1_351
2. H Wang, M Daneshmand, H Fang. Artificial Intelligence (AI) Driven Wireless Body Area Networks: Challenges and Directions. IEEE ICII2019.DOI: 10.1109/ICII.2019.00079
3. S.Bruendl*, H Fang⁺. 60 GHz in WBAN and mm-Wave Technologies. Encyclopedia of Wireless Networks. DOI: 10.1007/978-3-319-78262-1_351
4. Rumbut, J*.Fang, H+. Carreiro S, Singh D., Wang, H, Boyer E. Detecting Kratom Intoxication in Wearable Biosensor Data.  IEEE/ACM CHASE 2019. DOI: 10.1109/CHASE48038.2019.00028
5. VS Gurugubelli*, Fang H⁺, Wang, H. (2019) Neuro-Fuzzy classifier for behavioral intervention data 2019 International Conference on Computing, Networking and Communications (ICNC): Cloud Computing and Big Data. IEEE ICNC2019 DOI: 10.1109/ICCNC.2019.8685574
6. Z. Li** H. Fang, H. Wang, M. Daneshmand, (2019)"A Data-Centric Cognitive Gateway with Distributed MIMO for Future Smart Homes,"IEEE Wireless Communication Magazine, 26(3), 40-46 10.1109/MWC.2019.1800358
7. Md Shaad Mahmud**, H. Fang⁺, H. Wang, "An Integrated Wearable Sensor for Unobtrusive, Continuous Measurement of Autonomic Nervous System," IEEE Internet of Things Journal,  6(1), 1104-1113, 2019. DOI: 10.1109/JIOT.2018.2868235.

1. Fang H, Invited talk, MIFuzzy for incomplete longitudinal data pattern recognition, Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, New Hampshire.
2. M. S. Mahmud*, H.Fang+, H Wang, S Carreiro, E Boyer. (2018) Wearables Technology for Drug Abuse Detection: A Survey of Recent Advancement, 13,  Smart Health (Elsevier). DOI: 10.1016/j.smhl.2018.09.002.
3. VS Gurugubelli*, Li Z**, H Wang, H Fang⁺.(2018) eFCM: An Enhanced Fuzzy C-Means Algorithm for Longitudinal Intervention Data, IEEE ICNC2018. DOI: 10.1109/ICCNC.2018.8390419. PMCID: PMC6428443 NIHMSID: NIHMS973824; PMID: 30906794
4. VS Gurugubelli*, Li, Z**, Wang, H, Fang H⁺, (2018) A Computational Efficient Fuzzy Clustering Algorithm for Big Incomplete Longitudinal Trial Data 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE/ACM CHASE 2018. DOI: 10.1145/3278576.3278588
5. T. Jiang, H. Fang,  H. Wang,(2018) "Blockchain-based Internet of Vehicles: Distributed Network Architecture and Performance Analysis," in IEEE Internet of Things Journal, 2018. 10.1109/JIOT.2018.2874398
6. M.S. Mahmud**, H. Wang, H. Fang, "SensoRing: An Integrated Wearable System for Continuous Measurement of Physiological Biomarkers”  IEEE ICC2018. DOI: 10.1109/ICC.2018.8423001

1. SS Kim, H Fang⁺, K Bernstein, Z Zhang, J DiFranza, D ZieDonis, J Allison, Acculturation, Depression, and Smoking Cessation: a trajectory pattern recognition approach. Tob Induc Dis, 2017, doi:  10.1186/s12971-017-0135-x, PMCID: PMC5525352
2. Zhou, L**, Wang H, H.Fang⁺, " Group-Based Cooperation on Symmetric Key Generation for Wireless Body Area Networks," in IEEE Internet of Things Journal, 2017, 4(6): 1955-1963 doi: 10.1109/JIOT.2017.2761700. 
3. Haijia Wang*, Zitong Su*, H. Fang⁺. Simulating Normal and Abnormal ECG Signals in Children Age 0-16. 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), Accepted. DOI: 10.1109/CHASE.2017.103
4. M. S. Mahmud, H. Wang, A. M. Esfar-E-Alam, H. Fang, "A Wireless Health Monitoring System Using Mobile Phone Accessories," IEEE Internet of Things Journal, 2017, accepted, doi: 10.1109/JIOT.2016.2645125
5. Fang, H. MIFuzzy Clustering for Incomplete Longitudinal Data in Smart Health. Smart Health (Elsevier Journal). 1–2, pp. 50-65. DOI: 10.1016/j.smhl.2017.04.002. NIHMSID: 906898
6. Fang, H., Z. Zhang*. An Enhanced Visualization Method to Aid Behavioral Trajectory Patten Recognition Infrastructure for Big Longitudinal Data. IEEE Transaction on Big Data. 2017, Accepted. DOI: 10.1109/TBDATA.2017.2653815. NIHMSID: 907513 
7. Wang H, Mahmud MS, Fang H, Wang C. Wireless Health. Springer. 2017. ISBN 978-3-319-47946-0.
8. J. Wang* , Fang H⁺, B. Li and H. Wang, "Evaluate clustering performance and computational efficiency for PSO based fuzzy clustering methods in processing big imbalanced data," 2017 IEEE International Conference on Communications (ICC), Paris, 2017, pp. 1-6.doi: 10.1109/ICC.2017.7996802
9. Wang CJ,* Fang H⁺ , Carreiro S, Wang H., Boyer E. A New Mining Method to Detect Real Time Substance Use Events from Wearable Biosensor Data Stream. Proceedings of International Conference on Computing, Networking and Communications: Social Computing and Semantic Data Mining, pp. 465-470. ICNC2017. NIHMSID: 907527

1. Fang, H, Zhang Z,*  Ash, A, Houston, T, Allison, J, Validating Engagement Trajectory Patterns in Mining Big Longitudinal Web Trial Data, 9th Annual Conference on the Science of Dissemination and Implementation. Washington, DC. 2016.
2. Wang CJ,* Fang H⁺ , Carreiro S, Wang H., Boyer E. Detecting Real-time Substane Use from Wearable Biosensor Data Stream. Section on Statistical Learning and Data Mining. Joint Statistical Meetings, American Statistical Association. Chicago, IL, 2016.
3. Zhang Z,* Fang H⁺ , Wang H. A New MI-based Visualization Aided Validation Index for Mining Big Longitudinal Web Trial Data. IEEE Access.4:2272-2280. DOI: 10.1109/ACCESS.2016.2569074. NIHMSID: 790905. PMID: 27482473. PMCID: PMC4963037.
4. Zhang Z,* Fang H⁺ . Multiple- vs Non- or Single-Imputation based Fuzzy Clustering for Incomplete Longitudinal Behaviroal Intervention Data. Proceedings of 2016 IEEE first conference on Connected Health: Applications, Systems and Engineering Technologies (NIH & NSF jointly sponsored).  DOI: 10.1109/CHASE.2016.19. 
5. Zhang Z,* Fang H,⁺ Wang H. Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth. Journal of Medical System. 40 (6):1-9. DOI: 10.1007/s10916-016-0499-0. PMID: 27126063. PMCID: PMC4881752.
6. Fang, H, Zhang Z,* Zhang J, Houston, T, Ash, A, Allison, J, Identifying & Visualizing Participants’ Engagement Trajectory Patterns in Large-Scale Web Behavioral Intervention, Society of Behavioral Medicine, Washington D.C.
7. Carreiro, S, Wittbold, M., Premananda, I, Fang, H, Boyer, E. Non-Invasive Biosensors to Detect Physiologic Changes During Opioid Use, Society of Behavioral Medicine, Washington D.C. 
8. Wang CJ,* Fang H,⁺ Wang, H. ESammon: A Computationally Enhanced Sammon Mapping based on Data Density.  Proceedings of International Conference on Computing, Networking and Communications, ICNC2016. 1-5. DOI: 10.1109/ICCNC.2016.7440696. PMID: 27668263. PMCID: PMC5033056
9. Fang H, Wang H, Wang C, Daneshmand, M. Using Probabilistic Approach to Joint Clustering and Statistical Inference: Big Investment Data. IEEE BigData 2015. 2916 - 2918, DOI: 10.1109/BigData.2015.7364121.
10. Wang CJ,* Fang H,⁺ Wang C, Daneshmand M, Wang H. A Novel Initialization Method for Particle Swarm Optimization-based FCM in Big Biomedical Data. IEEE BigData 2015. 2942 – 2944, DOI: 10.1109/BigData.2015.7364130.
11. Zhang Z,* Fang H,⁺ Wang H. Visualization aided Engagement pattern validation for big longitudinal web behavior intervention data.  17th international Conference on E-health Networking, Application& Services. (IEEE Healthcom’15). 475-478, DOI: 10.1109/HealthCom.2015.7454549.

1. Wang, C.J,* Fang, H., Wang, H. A Computationally Enhanced Fuzzy Clustering Method for Big Biomedical Data. Section on Statistical Learning and Data Mining, Joint Statistical Meeting, American Statistical Association. Seattle, WA. 
2. Fang, H, Wittbold, M., Zhang, J., Weng, S, Carreiro, S, Mullins, R, Boyer, E. Describing Real-time Substance-use Detection from Big Biosensor Data: A Case study of Cocaine Users, Health Behavior Methods and Measures paper session, Society of Behavioral Medicine, San Antonio, TX. (Abstract Citation Award)
3. Fang, H, Zhang, Z.*, Wang, C.J.*, Wang, H., Ma, Y. Using Visualization-aided Trajectory Pattern Validation in a Longitudinal Dietary Data. Health Behavior Methods and Measures paper session , Society of Behavioral Medicine, San Antonio, TX. 
4. Fang H., Kim, S., Zhang, Z.*, DiFranza, J., Ziedonis, D., Allison, J. A Visualization-aided Trajectory Pattern Recognition Approach to Smoking and Depression among Asian Americans. Society for Research on Nicotine and Tobacco, Philadelphia, PA.
5. Fang H., Allison, J. Zhang, Z.*, Ash, A. A new look at behavioral interventions: Trajectory pattern recognition approach. 7th Annual Conference on the Science of Dissemination and Implementation, Bethesda, MD
6. Zhang Z *, Wang H., Wang C., Fang H., "Cluster-based Epidemic Control Through Smartphone-based Body Area Network," IEEE Transactions on Parallel and Distributed Systems (TPDS), March 2015, 26(3), PMID: 25741173.
7. Zhang Z*, Wang H., Wang C., Fang H., Modeling Epidemics Spreading on Social Contact Networks. IEEE Transactions on Emerging Topics in Computing. doi:10.1109/TETC.2015.2398353. 2015, 3(3), 410-419.
8. Wang CJ*, Fang H⁺, Wang H. DAG-searched and Density-based Initial Centroid Location Method for fuzzy clustering of big biomedical data. BICT2014. Feb, 2015, DOI: 10.4108/icst.bict.2014.257932. 
9. Fang H, Zhang Z*, Wang CJ*, Wang H. A Survey on Big Data Research. 2015. IEEE Network Magazine, 29 (5): 6-9. DOI: 10.1109/MNET.2015.7293298. PMID:26504265.
10. Carreiro S, Fang H⁺, Zhang, J, Wittbold K, Weng S, Mullins R, Smelson D, Boyer EW. iMStrong: Deployment of a biosensor system to detect cocaine use. Journal of Medical System. 39(12):186. doi: 10.1007/s10916-015-0337-9. PMID: 26490144.

1. Fang H., Invited Session Chair, Big Data in Smart Health: Models, Algorithms and Network. Institute of Mathematical Statistics & Section on Statistical Computing. Joint Statistical Meetings, American Statistical Association. Boston, MA, 2014
2. Fang H., Zhang, Z.*, Huang, J*, Wang, CJ, Wang H. Validating patterns for longitudinal trial data. Section on Statistics in Epidemiology. Joint Statistical Meetings, American Statistical Association. Boston, MA, 2014
3. Fang H. Zhang, Z.*, Wang H. An enhanced projection pursuit method to aid pattern recognition for longitudinal data. Section on Statistical Learning and Data Mining. Joint Statistical Meeting, American Statistical Association. Boston, MA, 2014
4. Fang, H., Allison, J. Barton, B., Pagoto, S., Zhang, Z,  Olendzki, G., Ma Y. Pattern Recognition Approach for Behavioral Interventions: An Application to a Dietary Trial, Philadelphia, Society of Behavioral Medicine. Ann Behav Med. 2014, in press.
5. Fang H., Kim, S., DiFranza, J., Zhang, Z., Ziedonis, D., Allison, J. Pattern recognition approach to culturally-tailored behavioral interventions for smoking cessation: Dose and Timing. Society for Research on Nicotine and Tobacco, Seattle, WA, 2014.
6. Kim S, Kwon, S., Fang H, Shelley, D., Ziedonis D. A Culturally Adapted Smoking Cessation Intervention for Korean Americans: A Mediating Effect of Perceived Family Norm toward Quitting. Journal of Immigrant and Minority Health. J Immigr Minor Health. 2014 May 31. [Epub ahead of print]. PMID: 24878686.
7. Kim S, Fang H, Mckee S, Ziedonis D, Prospective Evaluation of Factors Predicting Nicotine withdrawal Symptoms among Korean Americans. Journal of Smoking Cession. Sept, 2014. DOI: http://dx.doi.org/10.1017/jsc.2014.20. Cambridge University Press.