I am currently a Software Engineer at Google, where I work in the XLA:TPU optimizations team. I am interested in compiler autotuning, compiler optimizations, and ML Systems work in general.
Prior to Google, I completed my PhD in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, advised by Professor Arvind Krishnamurthy. During my studies, I worked at the intersection of Systems and Machine Learning. I also hold a MS (Computer Science) from the University of Washington, and a MEng. and Specialization (Systems) from Universidad Tecnológica Nacional FRC in Argentina. I received my BEng. (Telecommunications) degree from Universidad Blas Pascal, also in Argentina.
You can find me on: LinkedIn
Github
Google Scholar
CATWILD: Compiler Autotuning for TPU Workloads in the Wild [slides] [poster] conference
Ignacio Cano, Yu Emma Wang, Mike Burrows, Ziqiang Feng, Matheus Camargo, Chao Wang, David Liu, Tengyu Sun, Alexander Wertheim, Arissa Wongpanich, Christof Angermueller, Hyojun Kim, Wenqi Cao, Aleksey Orekhov, Amit Sabne, Emma Sevastian, Mehrdad Khani, Karthik Murthy, Berkin Ilbeyi, Subhankar Shah, Ryan Lefever, Arjun Khare, Ankit Sinha, Peter Ma, Matt Bierbaum, Jeremiah Wilke, Emily Donahue, Sami Abu-El-Haija, Nikhil Sarda, Vineetha Govindaraj, Shobha Vasudevan, Kirill Gugaev, Idan Nachman, Jie Sun, Jose Baiocchi Paredes, Samrat Ghosh, Domagoj Babic, Zongwei Zhou, Naveen Kumar, Phitchaya Mangpo Phothilimthana
Ninth Annual Conference on Machine Learning and Systems (MLSys), 2026
Optimizing Distributed Systems using Machine Learning [slides] phd thesis
Ignacio Cano
Paul G. Allen School of Computer Science & Engineering, University of Washington, 2019
AdaRes: Adaptive Resource Management for Virtual Machines preprint
Ignacio Cano, Lequn Chen, Pedro Fonseca, Tianqi Chen, Chern Cheah, Karan Gupta, Ramesh Chandra, Arvind Krishnamurthy
arXiv, 2018
Towards Geo-Distributed Machine Learning journal
Ignacio Cano, Markus Weimer, Dhruv Mahajan, Carlo Curino, Giovanni Matteo Fumarola, Arvind Krishnamurthy
In IEEE Data Engineering Bulletin, Global-scale Data Management Issue, December 2017
Extended version of NIPS LearningSys 2015 workshop paper
Curator: Self-Managing Storage for Enterprise Clusters [slides] conference
Ignacio Cano, Srinivas Aiyar, Varun Arora, Manosiz Bhattacharyya, Akhilesh Chaganti, Chern Cheah, Brent Chun, Karan Gupta, Vinayak Khot, Arvind Krishnamurthy
In Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2017
Characterizing Private Clouds: A Large-Scale Empirical Analysis of Enterprise Clusters [slides] [poster] conference
Ignacio Cano, Srinivas Aiyar, Arvind Krishnamurthy
In Proceedings of the 7th ACM Symposium on Cloud Computing (SoCC), 2016
Towards Geo-Distributed Machine Learning [poster] workshop
Ignacio Cano, Markus Weimer, Dhruv Mahajan, Carlo Curino, Giovanni Matteo Fumarola
In Neural Information Processing Systems LearningSys Workshop (NIPS), 2015
Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014 [slides] [poster] conference
Ignacio Cano, Sameer Singh, Carlos Guestrin
In Proceedings of the 23rd Text REtrieval Conference, Knowledge Base Acceleration Track (TREC KBA), 2014
Argentine Presidential Fellowship in Science & Technology
Argentina's Presidential Cabinet - Fulbright Commission, 2013-2015
Group Recognition Award (highest recognition)
Software & Services Group, Intel Corporation, Q4 2012
Teamwork Role Model
Argentina Software Design Center, Intel Corporation, 2012
Undergraduate Merit-based Scholarship (top 5%)
Universidad Blas Pascal, 2002-2006