Sotabase

Career

· Chief Scientist, Virtue AI2024–
· Chief Scientist, Visual Layer2022–
· Professor, Computer Science, Stanford University2021–
· Board of Directors, OctoAI2019–
· Senior Director of Machine Learning and AI, Apple2016–2021
· CEO and Co-founder, Turi, Inc.2013–2016
· Amazon Professor of Machine Learning, University of Washington2012–2021
· Finmeccanica Associate Professor, Carnegie Mellon University2004–2012
· Senior Researcher, Intel Research Lab2003–2004
· PhD in Computer Science, Stanford University1998–2003
· Mechatronics Engineer, University of São Paulo1993–1998

Publications (423)

XGBoost: A Scalable Tree Boosting System
Knowledge Discovery and Data Mining · 2016
48,670
cited
“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
North American Chapter of the Association for Computational Linguistics · 2016
20,081
cited
Cost-effective outbreak detection in networks
Knowledge Discovery and Data Mining · 2007
2,699
cited
Anchors: High-Precision Model-Agnostic Explanations
AAAI Conference on Artificial Intelligence · 2018
2,241
cited
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs
USENIX Symposium on Operating Systems Design and Implementation · 2012
1,982
cited
Near-optimal sensor placements in Gaussian processes
International Conference on Machine Learning · 2005
1,929
cited
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
2018
1,763
cited
Max-Margin Markov Networks
Neural Information Processing Systems · 2003
1,512
cited
Training Deep Nets with Sublinear Memory Cost
arXiv.org · 2016
1,367
cited
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
Annual Meeting of the Association for Computational Linguistics · 2020
1,261
cited
Model-Driven Data Acquisition in Sensor Networks
Very Large Data Bases Conference · 2004
1,252
cited
GraphChi: Large-Scale Graph Computation on Just a PC
USENIX Symposium on Operating Systems Design and Implementation · 2012
1,188
cited
Distributed GraphLab: A Framework for Machine Learning in the Cloud
Proceedings of the VLDB Endowment · 2012
1,086
cited
Stochastic Gradient Hamiltonian Monte Carlo
International Conference on Machine Learning · 2014
976
cited
GraphLab: A New Framework For Parallel Machine Learning
Conference on Uncertainty in Artificial Intelligence · 2010
923
cited
Model-Agnostic Interpretability of Machine Learning
arXiv.org · 2016
921
cited
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
Neural Information Processing Systems · 2023
781
cited
Learning structured prediction models: a large margin approach
International Conference on Machine Learning · 2005
574
cited
The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms
2008
567
cited
Efficient Solution Algorithms for Factored MDPs
Journal of Artificial Intelligence Research · 2003
554
cited
Sotabase