About Me

My name is Maryam Tabar (My legal last name is Gholamalitabar-firouzjaei). I am a second-year Ph.D. student in the College of Information Sciences and Technology at Pennsylvania State University. I am currently working under the supervision of Prof. Amulya Yadav and Prof. Dongwon Lee. Prior to that, I received my bachelor’s and master’s degrees in Computer Engineering from the Sharif University of Technology in 2016 and 2018, respectively.

[Curriculum Vitae]


Research Interests

  • Artificial Intelligence for Social Good
  • Machine Learning
  • Data Mining
  • Time-series Data Analysis
  • Social Network Analysis
  • Convex and Combinatorial Optimization

Publications

[1] Maryam Tabar, Heesoo Park, Stephanie Winkler, Dongwon Lee, Anamika Barman-Adhikari, and Amulya Yadav. Identifying Homeless Youth At-Risk of Substance Use Disorder: Data-Driven Insights for Policymakers. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’20), 2020. Acceptance Rate: 16% (121/756)

[2] Limeng Cui, Haeseung Seo, Maryam Tabar, Fenglong Ma, Suhang Wang, and Dongwon Lee. DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’20), 2020. Acceptance Rate: 16.9% (216/1,279)

[3] Maryam Tabar, Chi Yang Hsu, Hangzhi Guo, Amirreza Bagherzadehkhorasani, and Amulya Yadav. Ameliorating Farmer Suicides by Predicting Crop Price Trends using a Deep Learning Approach. In ECAI 2020 workshop on Advancing Towards the SDGs: Artificial Intelligence For a Fair, Just and Equitable World (AI4EQ), 2020.

[4] Maryam Tabar, Ahmad Haji Mohammadkhani, and Gholamreza Ghassem-Sani. Improving the Accuracy of a Persian Neural Dependency Parser using Ezafe Construction. In Proceedings of the 9th Language and Technology Conference (LTC), pages 227–231, 2019.

[5] Maryam Tabar, Aliakbar Nafar, and Gholamreza Ghassem-Sani. New Transition Systems for Dependency Parsing of Sentences with Non-Projective Relations. In Proceedings of the 9th Language and Technology Conference (LTC), pages 236–240, 2019.


 

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