Recent Preprints/Submissions

1. Integrating Expert Knowledge with Deep Learning Improves QSAR Models for CADD Modeling.
   Yunchao ‘‘Lance’’ Liu, Rocco Moretti, Yu Wang, Bobby Bodenheimer, Tyler Derr, Jens Meiler.
   

2. Distance-wise Prototypical Graph Neural Network for Imbalanced Node Classification.
   Yu Wang, Charu Aggarwal, and Tyler Derr.
   [Code repo]

2023

1. Adversarial Attacks for Black-box Recommender Systems via Copying Transferable Cross-domain User Profiles.
   Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang.
   IEEE Transactions on Knowledge and Data Engineering, 2023.

2. ADEPT: Autoencoder with Differentially Expressed Genes and Imputation for a Robust Spatial Transcriptomics Clustering.
   Yunfei Hu, Yuying Zhao (co-first author), Curtis T. Schunk, Yingxiang Ma, Tyler Derr, and Xin Maizie Zhou.
   iScience (also accepted and presented at RECOMB-Seq), 2023. [Code repo]

3. Collaboration-Aware Graph Neural Network for Recommender Systems.
   Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr.
   In Proceedings of the ACM Web Conference (TheWebConf), Austin, TX, USA, April 30 - May 4, 2023.
   [Code repo]

4. Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations.
   Yuying Zhao, Yu Wang, Tyler Derr.
   In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, February 7-14, 2023.
   [Code repo]
   

5. Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Relationship Modeling in Drug Discovery.
   Yunchao “Lance” Liu, Yu Wang, Oanh Vu, Rocco Moretti, Bobby Bodenheimer, Jens Meiler, Tyler Derr.
   In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, February 7-14, 2023.
   [Code repo]

2022

1. Degree-related Bias in Link Prediction.
   Yu Wang and Tyler Derr.
   In Proceedings of the 22nd International Conference on Data Mining Workshop (ICDMW) Machine Learning on Graphs (MLoG), Orlando, FL, USA, November 28 - December 1, 2022.

2. THINK: Temporal Hypergraph Hyperbolic Network.
   Shivam Agarwal, Ramit Sawhney, Megh Thakkar, Preslav Nakov, Jiawei Han, and Tyler Derr.
   In Proceedings of the 22nd International Conference on Data Mining (ICDM), Orlando, FL, USA, November 28 - December 1, 2022.
   Coming soon!

3. Decision Boundaries of Deep Neural Networks.
   Hamid Karimi and Tyler Derr.
   In Proceedings of the 21th IEEE International Conference on Machine Learning and Applications (ICMLA), Nassau, The Bahamas, December 12-15, 2022.
   [Code repo]

4. Enhancing Individual Fairness through Propensity Score Matching.
   Hamid Karimi, Muhammad Fawad Akbar Khan, Haochen Liu, Tyler Derr, and Hui Liu.
   In Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics (DSAA), Virtual, October 13-16, 2022.
   Coming soon!

5. Imbalanced Graph Classification via Graph-of-Graph Neural Networks.
   Yu Wang, Yuying Zhao, Neil Shah, and Tyler Derr.
   In Proceedings of the 31th ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, GA, USA, October 17-21, 2022.
   [Code repo]
   

6. Inferring EHR Utilization Workflows through Audit Logs.
   Xinmeng Zhang, Yuying Zhao (co-first author), Chao Yan, Tyler Derr, and You Chen.
   AMIA Annual Symposium Proceedings. Vol. 2022. American Medical Informatics Association, Washington D.C., USA, November 5-9, 2022.
   Coming soon!

7. Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage.
   Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr.
   In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington D.C., USA, August 14-18, 2022.
   [Code repo]

8. On Structural Explanation of Bias in Graph Neural Networks.
   Yushun Dong, Song Wang, Yu Wang, Tyler Derr, and Jundong Li.
   In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington D.C., USA, August 14-18, 2022.
   Coming soon!

9. ChemicalX: A Deep Learning Library for Drug Pair Scoring.
   Benedek Rozemberczki, Charles Hoyt, Anna Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michael Ughetto, Yu Wang, Tyler Derr, and Benjamin Gyori.
   In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington D.C., USA, August 14-18, 2022.
   [Code repo]

10. Graph Neural Networks: Self-supervised Learning.
    Yu Wang, Wei Jin, and Tyler Derr.
    In Graph Neural Networks: Foundations, Frontiers, and Applications, Lingfei Wu, Peng Cui, Jian Pei, and Liang Zhao (Eds.). Springer. Chapter 18. 2022.
    [Springer pdf] [preprint pdf]
    

2021

1. Tree Decomposed Graph Neural Network.
   Yu Wang and Tyler Derr.
   In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), Virtual Conference, November 1-5, 2021.
   [Code repo]

2. Deep Adversarial Network Alignment.
   Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu, and Jiliang Tang.
   In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), Virtual Conference, November 1-5, 2021.
   

3. Graph Feature Gating Network.
   Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu Aggarwal and Jiliang Tang.
   In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), Virtual Conference, November 1-5, 2021.
   

4. Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries.
   Aaron Brookhouse, Tyler Derr (co-first author), Hamid Karimi (co-first author), H. Russell Bernard, and Jiliang Tang.
   In Proceedings of the 32nd ACM Conference on Hypertext and Social Media, Virtual Conference, August 30 - September 2, 2021.
   

5. Interpretable Visual Understanding with Cognitive Attention Network.
   Xuejiao Tang, Wenbin Zhang, Yi Yu, Kea Turner, Tyler Derr, Mengyu Wang, Eirini Ntoutsi.
   In Proceedings of the 30th International Conference on Artificial Neural Networks (ICANN), Virtual Conference, September 14-17, 2021.
   [Code repo]

6. Graph Adversarial Attack via Rewiring.
   Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, and Jiliang Tang.
   In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), Singapore (Virtual Conference), August 14-18, 2021.
   [Code repo]

7. Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach.
   Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa, Tyler Derr, Rajiv Shah.
   In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), Virtual Conference, February 2-9, 2021.
   [Code repo]

8. Node Similarity Preserving Graph Convolutional Networks.
   Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang.
   In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM), Jerusalem, Israel, March 8-12, 2021.
   [Code repo]

9. CopyAttack: Attacking Black-box Recommendations via Copying Cross-domain User Profiles.
   Wenqi Fan, Tyler Derr, Xiangyu Zhao,Yao Ma,Hui Liu, Jianping Wang, Jiliang Tang, Qing Li.
   In Proceedings of the IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, April 19-22, 2021.
   

2020

1. Understanding and Promoting Teacher Connections in Online Social Media: A Case Study on Pinterest.
   Hamid Karimi, Kaitlin T. Torphy, Tyler Derr, Kenneth A. Frank, and Jiliang Tang.
   In Proceedings of the IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), Takamatsu, Japan, December 8-11, 2020.
   

2. Deep Graph Learning: Foundations, Advances and Applications.
   Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma.
   Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), San Diego, USA, August 22-27, 2020.
   [Tutorial site link]

3. Learning from Incomplete Labeled Data via Adversarial Data Generation.
   Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, and Jiliang Tang.
   In Proceedings of the 20th International Conference on Data Mining (ICDM), Sorrento, Italy, November 17-20, 2020.
   

4. Online Academic Course Performance Prediction using Relational Graph Convolutional Neural Network.
   Tyler Derr, Hamid Karimi (co-first authors), Jiangtao Huang, and Jiliang Tang.
   In Proceedings of 13th International Conference on Educational Data Mining (EDM), Ifrane, Morocco, July 10-13, 2020.
   

5. Characterizing Teacher Connections in Online Social Media: A Case Study on Pinterest.
   Hamid Karimi, Kaitlin T. Torphy, Tyler Derr, Kenneth A. Frank, and Jiliang Tang.
   (Work-in-Progress) In Proceedings of the 7th Learning@ Scale (L@S), Atlanta, USA, August 12-14, 2020.
   

6. Towards Improving Sample Representativeness of Teachers on Online Social Media: A Case Study on Pinterest.
   Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank, and Jiliang Tang.
   In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED), Ifran, Morocco, July 6-10, 2020.
   

7. Link and Interaction Polarity Predictions in Signed Networks.
   Tyler Derr, Zhiwei Wang, Jamell Dacon, and Jiliang Tang.
   Social Network Analysis and Mining. 10(18). 2020.
   

8. ROSE: Role-based Signed Network Embedding.
   Amin Javari, Tyler Derr, Pouya Esmalian, Jiliang Tang, and Kevin Chen-Chuan Chang.
   In Proceedings of the 29th International Conference on The World Wide Web (WWW), Taipei, Taiwan, April 20-24, 2020.
   

9. A Deep Model for Predicting Online Course Performance.
   Hamid Karimi, Jiangtao Huang (co-first author), Tyler Derr.
   Workshop on Artificial Intelligence for Education (AI4EDU) at the 34th AAAI Conference on Artificial Intelligence (AAAI), New York, USA, February 7-12, 2020.
   

10. Epidemic Graph Convolutional Network.
    Tyler Derr, Yao Ma, Wenqi Fan, Xiarui Liu, Charu Aggarwal, and Jiliang Tang.
    In Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM)/, Houston, USA, February 3-7, 2020.
    [Code repo]

11. Network Analysis with Negative Links.
    Tyler Derr.
    In Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM)/, Houston, USA, February 3-7, 2020.
    [Dataset repo]
    

2019

1. Balance in Signed Bipartite Networks.
   Tyler Derr, Cassidy Johnson, Yi Chang, and Jiliang Tang.
   In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM)/, Beijing, China, November 3-7, 2019.
   [Code repo]

2. Multi-Factor Congressional Vote Prediction.
   Tyler Derr, Hamid Karimi (co-first authors), Aaron Brookhouse, and Jiliang Tang.
   In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Vancouver, Canada, August 27-30, 2019.
   

3. Deep Adversarial Social Recommendation.
   Wenqi Fan, Tyler Derr, Yao Ma, Qing Li, Jiliang Tang, and Jianping Wang.
   In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, August 10-16, 2019.
   [Code repo]

4. A Roadmap for Incorporating Online Social Media in Educational Research.
   Hamid Karimi, Tyler Derr, Kaitlin T. Torphy, Kenneth A. Frank, and Jiliang Tang.
   In Teachers College Record Volume 121 Number 14, 2019. [TCR pdf]

2018 and before

1. Signed Graph Convolutional Networks.
   Tyler Derr, Yao Ma, and Jiliang Tang.
   In Proceedings of the 18th International Conference on Data Mining (ICDM), Singapore, November 17-20, 2018.
   [IEEE pdf] [Code repo] [3rd party code repo]

2. Congresional Vote Analysis Using Signed Networks.
   Tyler Derr and Jiliang Tang.
   In Proceedings of the 18th International Conference on Data Mining Workshops (ICDMW), Singapore, November 17-20, 2018.
   

3. Signed Network Modeling Based on Structural Balance Theory.
   Tyler Derr, Charu Aggarwal, and Jiliang Tang.
   In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM), Turin, Italy, October 22-26, 2018.
   

4. Opinions Power Opinions: Joint Link and Interaction Polarity Predictions in Signed Networks.
   Tyler Derr, Zhiwei Wang, and Jiliang Tang.
   In Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, Spain, August 28-31, 2018.
   

5. Understanding and Predicting Weight Loss with Mobile Social Networking Data.
   Zhiwei Wang, Tyler Derr, Dawei Yin, and Jiliang Tang.
   Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM)/, 2017.

Preprints

• Self-supervised Learning on Graphs: Deep Insights and New Directions.
  Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, and Jiliang Tang.
  

• Chat as Expected: Manipulating Black-box Neural Dialogue Models.
  Haochen Liu, Zhiwei Wang, Tyler Derr, Zitao Liu, and Jiliang Tang.
  

• A Survey of Computational Methods in Massive Open Online Courses.
  Jiangtao Huang, Tyler Derr, Hamid Karimi, and Jiliang Tang.
  

• Say What I Want: Towards the Dark Side of Neural Dialogue Models.
  Haochen Liu, Tyler Derr, Zitao Liu, and Jiliang Tang.
  

Symposiums / Workshops

1. Degree-related Bias in Link Prediction
   Yu Wang and Tyler Derr.
   In Proceedings of the 22nd International Conference on Data Mining Workshop (ICDMW), Orlando, FL, USA, November 28, 2022.

2. Distance-wise Prototypical Graph Neural Network for Imbalanced Node Classification.
   Yu Wang, Charu Aggarwal, and Tyler Derr.
   KDD 17th International Workshop on Mining and Learning with Graphs (MLG), Washington D.C., USA, August 15, 2022. [Code repo]
   

3. Self-supervised Learning on Graphs: Deep Insights and New Directions.
   Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, and Jiliang Tang.
   The Workshop on Self-Supervised Learning for the Web @ WWW, Presentation and poster, 2020.
   [pdf]
   

4. Network Analysis with Negative Links.
   Tyler Derr.
   Michigan AI Symposium - AI For Society, Poster, 2019.

5. Network Analysis with Negative Links.
   Tyler Derr.
   International Conference on Data Mining (SDM19) Doctoral Forum, SIAM, Poster, 2019. Best Poster Award

6. Why Do People Unfollow on Twitter.
   Aaron Brookhouse*, Tyler Derr, Hamid Karimi, and Jiliang Tang.
   Mid-Michigan Symposium for Undergraduate Research (MID-SURE), Poster. 2019 *Undergraduate student mentored

7. Signed Graph Convolutional Networks.
   Tyler Derr, Yao Ma, and Jiliang Tang.
   Michigan State University Engineering Graduate Research Symposium, Poster, 2019.

8. Multi-Factor Congressional Vote Prediction.
   Tyler Derr, Hamid Karimi, and Jiliang Tang.
   Michigan State University Graduate Academic Conference - Three-Minute Thesis Competition, Presentation, 2019. ‘‘People's Choice’’ Award

9. Deep Congressional Vote Prediction.
   Tyler Derr, Hamid Karimi, and Jiliang Tang.
   Southeast Michigan Postdoctoral Symposium, Presentation, 2018. 2nd Prize Awarded by University of Michigan's Postdoctoral Association

10. Congressional Vote Analysis using Signed Networks.
    Tyler Derr and Jiliang Tang.
    IEEE International Conference on Data Mining (ICDM18) Ph.D. Forum, Presentation, 2018.

11. Relevance Measurements in Online Signed Social Networks.
    Tyler Derr, Chenxing Wang, Suhang Wang, and Jiliang Tang.
    KDD 14th International Workshop on Mining and Learning with Graphs (MLG), London, United Kingdom, August 20, 2018.
    

12. Node Relevance Measurements in Online Signed Social Networks.
    Tyler Derr, Chenxing Wang, Suhang Wang, and Jiliang Tang.
    Michigan State University Engineering Graduate Research Symposium, Poster, 2018.

13. Opinions Power Opinions: Joint Link and Interaction Polarity Predictions in Signed Networks.
    Tyler Derr.
    International Conference on Data Mining (SDM17) Doctoral Forum, SIAM, Poster, 2017.

14. Opinions Power Opinions: Joint Link and Interaction Polarity Predictions in Signed Networks.
    Tyler Derr, Zhiwei Wang, and Jiliang Tang.
    Michigan State University Engineering Graduate Research Symposium, Poster, 2017.

15. A Supervised Learning Approach to the Prediction of Hi-C Data.
    Tyler Derr, Yanli Wang, and Feng Yue.
    ENCODE 2015: Research Applications and Users Meeting, Poster and presentation, 2015.

16. Visualizing three-dimensional organization and long-range interactions of the mammalian genome with the 3D Genome Browser.
    Yanli Wang, Gal Yaroslavsky, Tyler Derr, and Feng Yue.
    ENCODE 2015: Research Applications and Users Meeting, Poster, 2015.

17. Archimedes and His Approximation of sqrt(3).
    Tyler Derr.
    MAA-EPaDel Regional Spring Conference, Student Paper Session Talk, 2013.