Publications

  • Publications
  • 2024
    • Muzhe Guo, ..., and Fang Jin. Bayesian Iterative Prediction and Lexical-based Interpretation for Disturbed Chinese Sentence Pair Matching , The 2024 ACM International World Wide Web Conference, WWW 2024, accepted.

  • 2023
    • Muzhe Guo, Muhao Guo, Edward Dougherty, and Fang Jin. MSQ-BioBERT: Ambiguity Resolution to Enhance BioBERT Medical Question-Answering , The 2023 ACM International World Wide Web Conference, WWW 2023, pages: 4020-4028.

    • Muzhe Guo, Yong Ma, Efe Eworuke, Melissa Khashei, Jaejoon Song, Yueqin Zhao, and Fang Jin. Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing , Nature Scientific Reports, 13, 13721, 2023. PDF

  • 2022
    • Zhou Yang, Ninghao Liu, Xia Ben Hu, and Fang Jin. Tutorial on Deep Learning Interpretation: A Data Perspective. , CIKM 2022. Oct 2022. PDF

    • Hongfei Du, Si Wen, Yufei Guo, Fang Jin, and Brandon Gallas. Single Reader Between-Cases AUC Estimator with Nested Data , Statistical Methods in Medical Research. June 2022.

    • Juntao Su, Edward Dougherty, Shuang Jiang and Fang Jin. An Interactive Knowledge Graph Based Platform for COVID-19 Clinical Research, The 15th ACM International Conference on Web Search and Data Mining, WSDM 2022. PDF

    • Muzhe Guo, Long Nguyen, Hongfei Du, and Fang Jin. When Patients Recover from COVID-19: Data-driven Insights from Wearable Technologies. , Frontiers in Big Data-Medicine and Public Health. April 2022.

    • Qiyue Wang, Wu Xue, Xiaoke Zhang, Fang Jin, and James Hahn. S2FLNet: Hepatic Steatosis Detection Network with Body Shape, Computers in biology and Medicine. Volume 140, January 2022, 105088.

    • Zhou Yang, Spencer Bradshaw and Fang Jin. Discovering Opioid Use Patterns from Social Media for Relapse Prevention, IEEE Computer Society. 2022.

  • 2021
    • Shunyan Luo, Emre Barut, and Fang Jin. Statistically Consistent Saliency Estimation, International Conference on Computer Vision, ICCV 2021. Acceptance Rate: 25%. PDF, Code

    • Hongfei Du, Emre Barut, and Fang Jin. Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21). Feb 2021. Acceptance Rate: 21%. PDF

    • Shang Zhao, Xiaoke Zhang, Fang Jin, and James Hahn. An Auxiliary Tasks Based Framework for Automated Medical Skill Assessment with Limited Data, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021.

    • Qiyue Wang, Wu Xue, Xiaoke Zhang, Fang Jin, and James Hahn. Pixel-Wise Body Composition Prediction with a Multi-Task Conditional Generative Adversarial Network, Journal of Biomedical Informatics. 2021.

    • Hashim Abu-gellban, Yu Zhuang, Long Nguyen, Fang Jin, and Zhenkai Zhang. OnlineDC: Leveraging Temporal Driving Behavior to Facilitate Driver Classification, 2021 IEEE Conference on Big Data (BigData 2021) workshop, Applications of Big Data Technology in the Transport Industry. December 2021.

  • 2020
    • Zhou Yang, Long Nguyen, Zhu Jiazhen, Jia Li, and Fang Jin. Coordinating Disaster Emergency Response with Heuristic Reinforcement Learning, The 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. ASONAM 2020. PDF

    • Vinay Jayachandra, Rashmi Kesidi, Zhou Yang, Chen Zhang, Victor Sheng, and Fang Jin. BeSober: Assisting relapse prevention in Alcohol Addiction using a novel mobile app-based intervention., The 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. Demo, ASONAM 2020.

    • Zhenhe Pan, Dhruv Mehta, Anubhav Tiwari, Siddhartha Ireddy, Zhou Yang, and Fang Jin. An Interactive Platform to Track Global COVID-19 Epidemic. , The 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. Demo, ASONAM 2020.

    • Zhou Yang, Jiwei Xu, and Fang Jin. COVID19 Tracking: An Interactive Tracking, Visualizing and Analyzing Platform. , The 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. Demo, ASONAM 2020.

    • Sisheng Liang, Zhou Yang, Fang Jin, and Yong Chen. Data Centers Job Scheduling with Deep Reinforcement Learning, The 24th Pacific-Asia conference on Knowledge Discovery and Data Mining (PAKDD). Acceptance rate 21%. May, 2020. PDF

    • Zhou Yang, Sisheng Liang and Fang Jin. Not All Areas Are Equal: Detecting ThoracicDisease With ChestWNet. IEEE International Conference on Big Data workshop, 2020.

    • Hashim Abu-gellban, Long Nguyen and Fang Jin. GFDLECG: PAC Classification for ECG Signals Using Gradient Features and Deep Learning, Springer Nature – Book Series: Transactions on Computational Science & Computational Intelligence, 2020.

    • Hashim Abu-gellban, Long Nguyen, Mahdi Moghadasi, and Fang Jin. LiveDI: An Anti-theft Model Based on Driving Behavior, Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security. Page 67-72. June 2020.

  • 2019
    • Long Nguyen, Zhou Yang, Jia Li, and Fang Jin. Forecasting People's Needs in Hurricane Events from Social Network, IEEE Transactions on Big Data, 2019. PDF

    • Zhou Yang, Long Nguyen, and Fang Jin. Opioid Relapse Prediction with GAN, the 2019 IEEE/ACM International Conference on Social Networks Analysis and Mining, ASONAM 2019. August, 2019. Vancouver, Canada. Acceptance rate 14%. PDF

    • Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu and Naren Ramakrishnan. Online flu epidemiological deep modeling on disease contact network, Geoinformatica. 2019. PDF

    • Long H. Nguyen, Siyuan Jiang, Hashim Abu-gellban, Hanxiang Du, and Fang Jin. NiRec: Need Recommender for Hurricane Disaster Relief, 16th International Symposium on Spatial and Temporal Databases, SSTD 2019. August, 2019. Vienna, Austria. PDF, Code

    • Zhou Yang, Long H. Nguyen, and Fang Jin. Coordinating Disaster Emergency Response with Heuristic Reinforcement Learning, 1st Workshop on Adversarial Learning Methods for Machine Learning and Data Mining, at 25th ACM SIGKDD conference on knowledge discovery and data mining. KDD 2019 workshop.

    • Zhou Yang, Vinay Jayachandra, Rashmi Kesidi and Fang Jin. Addict Free - A Smart and Connected Relapse Intervention Mobile App, 16th International Symposium on Spatial and Temporal Databases, SSTD 2019. August, 2019. Vienna, Austria. PDF

    • Long Nguyen, Jiazhen Zhu, Zhe Lin, Hanxiang Du, Zhou Yang, Wenxuan Guo, and Fang Jin. Spatial-temporal Multi-Task Learning for Within-field Cotton Yield Prediction, The 23rd Pacific-Asia conference on Knowledge Discovery and Data Mining (PAKDD). Acceptance rate 24.7%. April 14-17 2019. PDF, Code

    • Zhou Yang and Fang Jin. Pneumonia Detection on Chest X-Rays with Deep Learning, 2019 Conference on Computer Vision and Pattern Recognition, CVPR Workshop on Towards Causual, Explanable and Universal Medical Visual Diagnosis. June 16-20, 2019. PDF

    • Hanxiang, Long Nguyen, Zhou Yang, Hashim Abu-gellban, Xingyu Zhou, Wanli Xing, Guofeng Cao, and Fang Jin. Twitter vs News: Concern Analysis of the 2018 California Wildfire Event, DADA 2019: The 1st IEEE International Workshop on Deep Analysis of Data-Driven Applications. IEEE. July 2019. PDF, Code

    • Mehdi Jamali, Ali Nejat, Souparno Ghosh, Fang Jin, and Guofeng Cao. Social Media Data and Post-disaster Recovery, International Journal of Information Management. Volume 44, Pages 25-37, February, 2019. PDF

  • 2018
    • Long H. Nguyen, Rattikorn Hewett, Akbar S. Namin, Nicholas Alvarez, Cristina Bradatan, and Fang Jin. Smart and Connected Water Resource Management via Social Media and Community Engagement, The 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018). Barcelona, Spain, 28-31 August, 2018. PDF, Code

    • Sisheng Liang, Long Nguyen, and Fang Jin. A Multi-variable Stacked Long-Short Term Memory Network for Wind Speed Forecasting, IEEE BigData 2018, Big Data Engineering and Analytics in Cyber-Physical Systems (BigEACPS) workshop. Dec 10-13, 2018. Seattle, WA, USA. PDF

    • Vinh T. Nguyen, Tommy Dang, and Fang Jin. Predict Saturated Thickness using TensorBoard Visualization, Visualization in Environmental Sciences 2018 (EnvirVis 2018). Brno, Czech Republic. June 4-8th, 2018. PDF

  • 2017
    • Zhou Yang, Long Nguyen, Joshua Stuve, Guofeng Cao, and Fang Jin. Harvey Flooding Rescue in Social Media, Proceedings of the IEEE International Conference on Big Data, Boston, Dec. 11-14, 2017. PDF

    • Long Nguyen, Andrew Salopek, Liang Zhao and Fang Jin. A Natural Language Normalization Approach to Enhance Social Media Text Reasoning, Proceedings of the IEEE International Conference on Big Data, Boston, Dec. 11-14, 2017. PDF, Code

    • Fang Jin, Wei Wang, Prithwish Chakraborty, Nathan Self, Feng Chen, Naren Ramakrishnan. Tracking Multiple Social Media for Stock Market Event Prediction, Industrial Conference on Data Mining ICDM 2017. PDF

    • Fang Jin, Feng Chen, Rupinder Khandpur, Chang-Tien Lu, Naren Ramakrishnan. Absenteeism Detection in Social Media, in Proceedings of the SIAM International Conference on Data Mining (SDM'17), Houston, TX, Apr 2017. Acceptance rate: 26%. PDF

  • Before 2017
    • Fang Jin. Algorithms for Modeling Mass Movements and their Adoption in Social Networks, Dissertation. Arlington, VA. June 2016.

    • Fang Jin, Rupinder Khandpur, Nathan Self, Edward Dougherty, Sheng Guo, Feng Chen, B. Aditya Prakash, Naren Ramakrishnan. Modeling Mass Protest Adoption in Social Network Communities using Geometric Brownian Motion, in Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14), Aug 2014. Acceptance rate: 14.6%. Recipient of KDD 2014 NSF student travel award. PDF, Slides, Poster, Spotlight

    • Fang Jin, Wei Wang, Liang Zhao, Edward Dougherty, Yang Cao, Chang-Tien Lu, Naren Ramakrishnan. Misinformation Propagation in the age of Twitter, IEEE Computer, Volume 47, Issue 12, pages 90-94, Dec 2014. PDF, Code

    • Fang Jin, Edward Dougherty, Parang Saraf, Peng Mi, Yang Cao, and Naren Ramakrishnan. Epidemiological modeling of news and rumors on twitter, in Proceedings of the 7th ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD 2013), Chicago, IL, 2013, pages 8:1-8:9. Recipient of Best Paper Award & Student Travel Award. PDF, PPT, Code

    • Fang Jin, Nathan Self, Parang Saraf, Patrick Butler, Wei Wang, Naren Ramakrishnan. Forex-Foreteller: Currency Trend Modeling using News Articles, in Proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining - Demo Track, pages 1470--1473, Aug 2013. PDF, Slides, Poster

    • Yan Wang, Guofu Wang, Wenchuan He, Feng Gao, Jiang Zhu, Mingnong Feng, Fang Jin. Tiered storage technology of meteorological spatial data, Chinese Meteorological Society & Meteorological Communications and Information Technology Committee Scientific Meeting, 2011.

    • Min Wei, Lanning Wang, Fang Jin. The implementation of coupling algorithm for MOM4 and BCC_CSM Model, in Information Science and Engineering (ICISE), 2010 2nd International Conference on, pp. 1600-1604. IEEE, 2010.

    • Fang Jin, Hongqun Zhang, Xiaoqing Ge. Design of Fault Diagnosis Expert System for Satellites Receiving System, in Microcomputer Information, 7 (2009): 107-108.

  • Book Chapters
    • 2014
      • Edward A. Fox, Monika Akbar, Sherif Hanie El Meligy Abdelhamid, Noha Ibrahim Elsherbiny, Mohamed Magdy Gharib Farag, Fang Jin, Jonathan P. Leidig, Sai Tulasi Neppali. Computing Handbook, Third Edition, Vol. 2 (Information Systems and Information Technology). Section 3, Ch. 18, ed. by Heikki Topi, Allen Tucker, Chapman & Hall/CRC Press, Taylor and Francis Group, ISBN 9781439898444, http://www.crcpress.com/product/isbn/9781439898543, May 2014.