Spatially-Localized Compressed Sensing and Routing in Multi-hop Sensor Networks. - Sungwon Lee; Sundeep Pattem; Maheswaran Sathiamoorthy; Bhaskar Krishnamachari; Antonio Ortega (GSN, 2009)

Backpressure with Adaptive Redundancy (BWAR). - Majed Alresaini; Maheswaran Sathiamoorthy; Bhaskar Krishnamachari; Michael J. Neely (INFOCOM, 2012)

Minimum Latency Data Diffusion in Intermittently Connected Mobile Networks. - Maheswaran Sathiamoorthy; Wei Gao 006; Bhaskar Krishnamachari; Guohong Cao (VTC Spring, 2012)

Analysis of Twitter Traffic based on Renewal Densities - Javier Esteban; Antonio Ortega; Sean McPherson; Maheswaran Sathiamoorthy (CoRR, 2012)

Short paper: Dynamic online storage allocation for multi-content dissemination in two-tier hybrid mobile vehicular networks. - Keyvan R. Moghadam; Maheswaran Sathiamoorthy; Bhaskar Krishnamachari; Fan Bai 002 (VNC, 2013)

XORing Elephants: Novel Erasure Codes for Big Data. - Maheswaran Sathiamoorthy; Megasthenis Asteris; Dimitris S. Papailiopoulos; Alexandros G. Dimakis; Ramkumar Vadali; Scott Chen; Dhruba Borthakur (Proc. VLDB Endow., 2013)

Helper node allocation strategies for content dissemination in intermittently connected mobile networks. - Maheswaran Sathiamoorthy; Keyvan R. Moghadam; Bhaskar Krishnamachari; Fan Bai 002 (SECON, 2014)

Optimizing Content Dissemination in Vehicular Networks with Radio Heterogeneity. - Joon Ahn; Maheswaran Sathiamoorthy; Bhaskar Krishnamachari; Fan Bai 002; Lin Zhang 001 (IEEE Trans. Mob. Comput., 2014)

Distributed Storage Codes Reduce Latency in Vehicular Networks. - Maheswaran Sathiamoorthy; Alexandros G. Dimakis; Bhaskar Krishnamachari; Fan Bai 002 (IEEE Trans. Mob. Comput., 2014)

Opportunities and Challenges Of Machine Learning Accelerators In Production. - Rajagopal Ananthanarayanan; Peter Brandt; Manasi Joshi; Maheswaran Sathiamoorthy (OpML, 2019)

Recommending what video to watch next: a multitask ranking system. - Zhe Zhao 001; Lichan Hong; Li Wei; Jilin Chen; Aniruddh Nath; Shawn Andrews; Aditee Kumthekar; Maheswaran Sathiamoorthy; Xinyang Yi; Ed H. Chi (RecSys, 2019)

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. - Hussein Hazimeh 001; Zhe Zhao 001; Aakanksha Chowdhery; Maheswaran Sathiamoorthy; Yihua Chen; Rahul Mazumder; Lichan Hong; Ed H. Chi (NeurIPS, 2021)

Algorithms for Efficiently Learning Low-Rank Neural Networks. - Kiran Vodrahalli; Rakesh Shivanna; Maheswaran Sathiamoorthy; Sagar Jain; Ed H. Chi (CoRR, 2022)

Improving Training Stability for Multitask Ranking Models in Recommender Systems. - Jiaxi Tang; Yoel Drori; Daryl Chang; Maheswaran Sathiamoorthy; Justin Gilmer; Li Wei; Xinyang Yi; Lichan Hong; Ed H. Chi (KDD, 2023)

Recommender Systems with Generative Retrieval. - Shashank Rajput; Nikhil Mehta 002; Anima Singh; Raghunandan Hulikal Keshavan; Trung Vu 002; Lukasz Heldt; Lichan Hong; Yi Tay; Vinh Q. Tran 002; Jonah Samost; Maciej Kula; Ed H. Chi; et al. (NeurIPS, 2023)

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. - Wang-Cheng Kang; Jianmo Ni; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (CoRR, 2023)

Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. - Anima Singh; Trung Vu 002; Raghunandan H. Keshavan; Nikhil Mehta 002; Xinyang Yi; Lichan Hong; Lukasz Heldt; Li Wei; Ed H. Chi; Maheswaran Sathiamoorthy (CoRR, 2023)

A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). - Yashar Deldjoo; Zhankui He; Julian J. McAuley; Anton Korikov; Scott Sanner; Arnau Ramisa; René Vidal; Maheswaran Sathiamoorthy; Atoosa Kasirzadeh; Silvia Milano (KDD, 2024)

Aligning Large Language Models with Recommendation Knowledge. - Yuwei Cao; Nikhil Mehta 002; Xinyang Yi; Raghunandan Hulikal Keshavan; Lukasz Heldt; Lichan Hong; Ed H. Chi; Maheswaran Sathiamoorthy (NAACL-HLT (Findings), 2024)

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. - Anima Singh; Trung Vu 002; Nikhil Mehta 002; Raghunandan H. Keshavan; Maheswaran Sathiamoorthy; Yilin Zheng; Lichan Hong; Lukasz Heldt; Li Wei; Devansh Tandon; Ed H. Chi; Xinyang Yi (RecSys, 2024)

Large Language Model Driven Recommendation. - Anton Korikov; Scott Sanner; Yashar Deldjoo; Zhankui He; Julian J. McAuley; Arnau Ramisa; René Vidal; Mahesh Sathiamoorthy; Atoosa Kasirzadeh; Silvia Milano; Francesco Ricci (CoRR, 2024)

Multi-modal Generative Models in Recommendation System. - Arnau Ramisa; René Vidal; Yashar Deldjoo; Zhankui He; Julian J. McAuley; Anton Korikov; Scott Sanner; Mahesh Sathiamoorthy; Atoosa Kasrizadeh; Silvia Milano; Francesco Ricci (CoRR, 2024)

Recommendation with Generative Models. - Yashar Deldjoo; Zhankui He; Julian J. McAuley; Anton Korikov; Scott Sanner; Arnau Ramisa; René Vidal; Maheswaran Sathiamoorthy; Atoosa Kasrizadeh; Silvia Milano; Francesco Ricci (CoRR, 2024)

Toward Holistic Evaluation of Recommender Systems Powered by Generative Models. - Yashar Deldjoo; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Shuai Zhang 007; Pablo Castells; Julian J. McAuley (SIGIR, 2025)

Tutorial on Recommendation with Generative Models (Gen-RecSys). - Yashar Deldjoo; Zhankui He; Julian J. McAuley; Anton Korikov; Scott Sanner; Arnau Ramisa; René Vidal; Maheswaran Sathiamoorthy; Atoosa Kasirzadeh; Silvia Milano (WSDM, 2025)

OpenThoughts: Data Recipes for Reasoning Models. - Etash Kumar Guha; Ryan Marten; Sedrick Keh; Negin Raoof; Georgios Smyrnis; Hritik Bansal; Marianna Nezhurina; Jean Mercat; Trung Vu 002; Zayne Sprague; Ashima Suvarna; Benjamin Feuer; et al. (CoRR, 2025)