Mahesh Sathiamoorthy

Staff Software Engineer at Google DeepMind

Brief Bio

I am Maheswaran Sathiamoorthy, but go by Mahesh Sathiamoorthy.

I am a Staff Software Engineer at Google DeepMind (previously called Google Brain). I work on Large Recommender Models and make use of LLMs to improve recommendations, such as for YouTube. I have been with Google since 2014. From 2008 to 2013, I was a PhD student at Department of Electrical Engineering, University of Southern California. I worked with Prof. Bhaskar Krishnamachari and Prof. Alex Dimakis.

Before that, I did my B.Tech(H) in Electronics and Electrical Communication Engineering at the Indian Institute of Technology Kharagpur, India.

Contact me at mahesh at smahesh dot com.

Research/Current Work

I am a Tech Lead in Google DeepMind and currently work on LLM based recommender models.
I have been instrumental in scaling up our recommender models and delivered numerous launches that improve either the quality or the performance of recommender models.
I work on all aspects of recommender models: infrastructure and productionization, research and engagements. My work benefits surfaces such as YouTube.

Selected Publications

  1. Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy. "Recommender Systems with Generative Retrieval". arxiv. NeurIPS 2023
  2. Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi, "Improving Training Stability for Multitask Ranking Models in Recommender Systems". arxiv. KDD 2023, Best Paper Award in Data Science Track.
  3. Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed Chi, Derek Zhiyuan Cheng. "Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction". arxiv. Workshop on Personalized Generative AI, CIKM 2023.
  4. Anima Singh, Trung Vu, Raghunandan Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed Chi, Maheswaran Sathiamoorthy. "Better Generalization with Semantic IDs: A case study in Ranking for Recommendations". Preprint 2023
  5. Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi. "Algorithms for Efficiently Learning Low-Rank Neural Networks". 2022 (preprint)
  6. Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H Chi. "DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning". NeurIPS 2021 [arxiv]
  7. Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, and Ed Chi. 2019. "Recommending what video to watch next: a multitask ranking system". In Proc. of the 13th ACM Conference on Recommender Systems (RecSys '19). ACM, New York, NY, USA, 43-51. DOI: [Google]
  8. Stephen Macke, Alex Beutel, Tim Kraska, Maheswaran Sathiamoorthy, Derek Zhiyuan Cheng, Ed H. Chi. Lifting the Curse of Multidimensional Data with Learned Existence Indexes. ML for Systems workshop at NeurIPS, 2018. [pdf]
  9. Maheswaran Sathiamoorthy, Megasthenis Asteris, Dimitris Papailiopoulos, Alex G. Dimakis, Ramkumar Vadali, Scott Chen, Dhruba Borthakur, "XORing Elephants: Novel Erasure Codes for Big Data", VLDB 2013.