Tina Eliassi-Rad
(The correct pronunciation of my last name is ëlee-ásee rád.)

• Curriculum Vitae (September 2021)
• Short Bio (August 2021)
• High-resolution Photo

Current Employment

Professor, Khoury College of Computer Sciences
Northeastern University, Boston, MA

• Network Science Institute, Northeastern University
• Institute for Experiential AI, Northeastern University

• Santa Fe Institute
• Vermont Complex Systems Center

• NULab for Texts, Maps, and Networks, Northeastern University
• Global Resilience Institute, Northeastern University
• Cybersecurity and Privacy Institute, Northeastern University

Research Interests: Data Mining, Machine Learning, Network Science, Ethics of Artificial Intelligence.

• Publications
• DBLP
• Google Scholar

Recently Co-organized Events

• Latest Advances in Spectral Linear Algebra in Network Science
• May 19, 2021
• Symposium at the 2021 SIAM Conference on Applied Linear Algebra (LA21), Virtual Conference

• Higher-Order Graph Models: From Theoretical Foundations to Machine Learning
• August 29 - September 1, 2021
• Workshop at Schloss Dagstuhl, Wadern, Germany

Teaching

• [Fall 2021] Introduction to Computer Science Research (CS 3950)
• [Fall 2021] Computer Science Research Seminar (CS 4950)
• [Spring 2021] Network Science Data 2 (PHYS 7332)
• [Fall 2020] Algorithms that Affect Lives (HONR 1310)
• [Spring 2020] Algorithms that Affect Lives (HONR 1310)
• [Fall 2019] Data Mining Techniques (CS 6220) cross-listed with Unsupervised Machine Learning and Data Mining (DS 5230)
• [Spring 2019] Data Mining Techniques (CS 6220) cross-listed with Unsupervised Machine Learning and Data Mining (DS 5230)
• [Fall 2018] Data Mining Techniques (CS 6220)
• [Spring 2017] Data Mining Techniques (CS 6220)
• [Spring 2016] Network Science Research (NETS 8984)
• [Fall 2015] Pattern Recognition: Theory & Applications (16:198:535)
• [Spring 2015] Introduction to Data Science (01:198:443)
• [Fall 2014] Topics in Artificial Intelligence (16:198:598) -- Machine Learning with Large-scale Data
• [Spring 2014] Machine Learning (16:198:536)
• [Fall 2013] Introduction to Data Science (01:198:444)
• [Spring 2013] Information in Networks: Theory, Algorithms, and Applications (16:198:672)
• [Spring 2012] Machine Learning (16:198:536)
• [Fall 2011] Introduction to Network Science: Theory, Algorithms, and Applications (01:198:442)
• [Spring 2011] Graduate Seminar on Graph Mining and Network Analysis (16:198:672)
• [Spring 2011] Light Seminar on Machine Learning (16:198:500:01)

Tutorials

• Incompleteness in Networks: Biases, Skewed Results, and Some Solutions (with Rajmonda Caceres and Timothy LaRock)
• [ACM KDD 2019] Abstract, Slides, and Resources

• Graph Metric Spaces (with Jose Bento, Stratis Ioannidis, and Leo Torres)
• [SIAM SDM 2019] Abstract, Slides, and Resources
• [ACM KDD 2018] Abstract, Slides, and Resources

• Problems with Partially Observed (Incomplete) Networks: Biases, Skewed Results, and Solutions (with Sucheta Soundarajan and Sahely Bhadra)
• [SIAM SDM 2018] Abstract, Slides, and Resources

• Mining Smartphone and Mobility Data (with Spiros Papadimitriou, Katharina Morik, and Dimitrios Gunopulos)
• [IEEE ICDM 2016] Abstract, Slides, and Resources

• Mining Smartphone Mobility Data (with Spiros Papadimitriou)
• [ICWSM 2016] Abstract, Slides, and Resources

• Problems with Incomplete Networks: Biases, Skewed Results, and Solutions (with Sucheta Soundarajan, Ali Pinar, and Brian Gallagher)
• [SIAM SDM 2016] Abstract, Slides, and Resources

• Understanding Offline Political Systems by Mining Online Political Data (with David Lazer and Oren Tsur)
• [WSDM 2016] Abstract, Slides

• Mining Mobility Data (with Spiros Papadimitriou)
• [WWW 2015] Abstract, Slides, Resources

• Node and Graph Similarity: Theory and Applications (with Danai Koutra and Christos Faloutsos)
• [IEEE ICDM 2014] Abstract and Slides

• Node Similarity, Graph Similarity and Matching: Theory and Applications (with Danai Koutra and Christos Faloutsos)
• [SIAM SDM 2014] Abstract and Slides

• Mining Data from Mobile Devices: A Survey of Smart Sensing and Analytics (with Spiros Papadimitriou)
• [ACM KDD 2013] Abstract, Slides, Resources

• Discovering Roles and Anomalies in Graphs: Theory and Applications (with Christos Faloutsos)
• [ECML PKDD 2013] Slides Part 1 and Part 2 (includes guided role discovery and role discovery over time )
• [SIAM SDM 2012] Slides Part 1 and Part 2

Other Information