Temporal analysis of telecom call graphs. - Saket Gurukar; Balaraman Ravindran (COMSNETS, 2014)

COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks. - Saket Gurukar; Sayan Ranu; Balaraman Ravindran (SIGMOD Conference, 2015)

Time-series as Background Data for Relating Medical Diagnoses Terms. - Saket Gurukar; Srikanta Bedathur (BCB, 2019)

Network Representation Learning: Consolidation and Renewed Bearing. - Saket Gurukar; Priyesh Vijayan; Aakash Srinivasan; Goonmeet Bajaj; Chen Cai; Moniba Keymanesh; Saravana Kumar; Pranav Maneriker; Anasua Mitra; Vedang Patel; Balaraman Ravindran; Srinivasan Parthasarathy 001 (CoRR, 2019)

Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods. - Moniba Keymanesh; Saket Gurukar; Bethany Boettner; Christopher R. Browning; Catherine A. Calder; Srinivasan Parthasarathy 001 (CoRR, 2019)

Towards Quantifying the Distance between Opinions. - Saket Gurukar; Deepak Ajwani; Sourav Dutta 001; Juho Lauri; Srinivasan Parthasarathy 001; Alessandra Sala (ICWSM, 2020)

LocationTrails: a federated approach to learning location embeddings. - Saket Gurukar; Srinivasan Parthasarathy 001; Rajiv Ramnath; Catherine A. Calder; Sobhan Moosavi (ASONAM, 2021)

DistMILE: A Distributed Multi-Level Framework for Scalable Graph Embedding. - Yuntian He; Saket Gurukar; Pouya Kousha; Hari Subramoni; Dhabaleswar K. Panda 001; Srinivasan Parthasarathy 001 (HiPC, 2021)

MILE: A Multi-Level Framework for Scalable Graph Embedding. - Jiongqian Liang; Saket Gurukar; Srinivasan Parthasarathy 001 (ICWSM, 2021)

FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification. - Sean Current; Yuntian He; Saket Gurukar; Srinivasan Parthasarathy 001 (EAAMO, 2022)

Leveraging network representation learning and community detection for analyzing the activity profiles of adolescents. - Saket Gurukar; Bethany Boettner; Christopher R. Browning; Catherine A. Calder; Srinivasan Parthasarathy 001 (Appl. Netw. Sci., 2022)

FairMod: Fair Link Prediction and Recommendation via Graph Modification. - Sean Current; Yuntian He; Saket Gurukar; Srinivasan Parthasarathy 001 (CoRR, 2022)

FairMILE: A Multi-Level Framework for Fair and Scalable Graph Representation Learning. - Yuntian He; Saket Gurukar; Srinivasan Parthasarathy 001 (CoRR, 2022)

MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest. - Saket Gurukar; Nikil Pancha; Andrew Zhai; Eric Kim; Samson Hu; Srinivasan Parthasarathy 001; Charles Rosenberg 001; Jure Leskovec (Proc. VLDB Endow., 2022)

WebMILE: Democratizing Network Representation Learning at Scale. - Yuntian He; Yue Zhang; Saket Gurukar; Srinivasan Parthasarathy 001 (Proc. VLDB Endow., 2022)

Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress. - Saket Gurukar; Priyesh Vijayan; Srinivasan Parthasarathy 001; Balaraman Ravindran; Aakash Srinivasan; Goonmeet Bajaj; Chen Cai; Moniba Keymanesh; Saravana Kumar; Pranav Maneriker; Anasua Mitra; Vedang Patel (Trans. Mach. Learn. Res., 2022)

PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks. - Saket Gurukar; Shaileshh Bojja Venkatakrishnan; Balaraman Ravindran; Srinivasan Parthasarathy 001 (ASONAM, 2023)

FairMILE: Towards an Efficient Framework for Fair Graph Representation Learning. - Yuntian He; Saket Gurukar; Srinivasan Parthasarathy 001 (EAAMO, 2023)

Efficient Fair Graph Representation Learning Using a Multi-level Framework. - Yuntian He; Saket Gurukar; Srinivasan Parthasarathy 001 (WWW (Companion Volume), 2023)

HeteroMILE: a Multi-Level Graph Representation Learning Framework for Heterogeneous Graphs. - Yue Zhang; Yuntian He; Saket Gurukar; Srinivasan Parthasarathy 001 (CoRR, 2024)

Long-VMNet: Accelerating Long-Form Video Understanding via Fixed Memory. - Saket Gurukar; Asim Kadav (CoRR, 2025)