Lijing Wang

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 18

Top Topics

Replicator Dynamics

Simulation Models

Top Venues

Publications

Aniruddha Adiga, Gursharn Kaur, Lijing Wang, Benjamin Hurt, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe
Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts. AAAI (2023)
Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav V. Marathe
CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting. AAAI (2022)
Aniruddha Adiga, Gursharn Kaur, Benjamin Hurt, Lijing Wang, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe
Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources. Big Data (2022)
Aniruddha Adiga, Lijing Wang, Benjamin Hurt, Akhil Sai Peddireddy, Przemyslaw Porebski, Srinivasan Venkatramanan, Bryan Leroy Lewis, Madhav Marathe
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting. KDD (2021)
Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav Marathe, Rajesh Sundaresan, Milind Tambe
Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway. AAMAS (2021)
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan L. Lewis, Madhav Marathe
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting. IEEE BigData (2020)
Lijing Wang, Jiangzhuo Chen, Madhav Marathe
TDEFSI: Theory-guided Deep Learning-based Epidemic Forecasting with Synthetic Information. ACM Trans. Spatial Algorithms Syst. 6 (3) (2020)
Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav Marathe, Rajesh Sundaresan, Milind Tambe
Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway. CoRR (2020)
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta, Jiangzhuo Chen, Madhav Marathe
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models. NeurIPS (2020)
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta, Jiangzhuo Chen, Madhav Marathe
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models. CoRR (2020)
Lijing Wang, Jiangzhuo Chen, Madhav Marathe
TDEFSI: Theory Guided Deep Learning Based Epidemic Forecasting with Synthetic Information. CoRR (2020)
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan L. Lewis, Madhav Marathe
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting. CoRR (2020)
Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning
Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction. CIKM (2020)
Lijing Wang, Jiangzhuo Chen, Achla Marathe
A framework for discovering health disparities among cohorts in an influenza epidemic. World Wide Web 22 (6) (2019)
Lijing Wang, Jiangzhuo Chen, Madhav Marathe
DEFSI: Deep Learning Based Epidemic Forecasting with Synthetic Information. AAAI (2019)
Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction. CoRR (2019)
Ting Hua, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu, Naren Ramakrishnan
Social Media based Simulation Models for Understanding Disease Dynamics. IJCAI (2018)
Lijing Wang, Jin-Hee Cho, Ing-Ray Chen, Jiangzhuo Chen
PDGM: Percolation-based directed graph matching in social networks. ICC (2017)