Aniruddh Nath

(FirstnameLastname)@google.com

LinkedIn

 

I'm currently a senior staff software engineer at Google, working on the YouTube recommendation algorithm. Previously, I earned my PhD at the University of Washington. Earlier still, I was an undergrad at the University of Illinois.

Papers

• Zero-shot Cross-domain Knowledge Distillation: A Case study on YouTube Music. S. Ranganathan, C. Lo, B. Cunha, N. Khani, L. Wei, A. Nath, S. Andrews, G. Varady, Y. Song, J. Klingenhoefer, T. Steele. RecSys 2025.
• Enhancing Online Ranking Systems via Multi-Surface Co-Training for Content Understanding. G. Zhao, Y. Zheng, R. Keshavan, L. Heldt, Q. Sun, F. Soldo, L. Wei, A. Nath, N. Khani, W. Yang, D. Omidiran, R. Zhang, M. Chen, L. Hong, X. Yi. RecSys 2025.
• Bridging the gap: Unpacking the hidden challenges in knowledge distillation for online ranking systems. N. Khani, L. Wei, A. Nath, S. Andrews, S. Yang, Y. Liu, P. Abbo, M. Kula, J. Kahn, Z. Zhao, L. Hong, E. Chi. RecSys 2024.
  • Related patent pending: Artificial intelligence system for media item recommendations. US20250254375A1.
• Recommending what video to watch next: a multitask ranking system. Z. Zhao, L. Hong, L. Wei, J. Chen, A. Nath, S. Andrews, A. Kumthekar, M. Sathiamoorthy, X. Yi, E. Chi. RecSys 2019.
• Learning Tractable Probabilistic Models for Fault Localization. A. Nath and P. Domingos. AAAI 2016.
  • Earlier version. StaR-AI 2015.
• Learning and Exploiting Relational Structure for Efficient Inference. A. Nath. PhD Dissertation, University of Washington, 2015.
• Learning Relational Sum-Product Networks. A. Nath and P. Domingos. AAAI 2015.
  • Earlier version: Learning Tractable Statistical Relational Models. StaR-AI 2014.
• Automated Debugging with Tractable Probabilistic Programming. A. Nath and P. Domingos. StaR-AI 2014. (Position paper.)
• Approximate Lifting Techniques for Belief Propagation. P. Singla, A. Nath and P. Domingos. AAAI 2014.
  • Supplementary Materials
  • Earlier version: Approximate Lifted Belief Propagation. StaR-AI 2010.
• Counting-MLNs: Learning Relational Structure for Decision Making. A. Nath and M. Richardson. AAAI 2012.
  • Related patent: Relational Learning for System Imitation. US8862523B2.
• Learning Multiple Hierarchical Relational Clusterings. A. Nath and P. Domingos. SRL 2012.
• Markov Logic: A Language and Algorithms for Link Mining. P. Domingos, D. Lowd, S. Kok, A. Nath, H. Poon, M. Richardson and P. Singla. Chapter in P. Yu, C. Faloutsos, and J. Han (eds.), Link Mining: Models, Algorithms and Applications, 2010.
• Efficient Belief Propagation for Utility Maximization and Repeated Inference. A. Nath and P. Domingos. AAAI 2010.
• Efficient Lifting for Online Probabilistic Inference. A. Nath and P. Domingos. AAAI 2010.
  • Workshop version. StaR-AI 2010.
  • Dataset
• A Language for Relational Decision Theory. A. Nath and P. Domingos. SRL 2009.
  • Code