Formal Bio & Photo
Professor, Computer Science, Stanford
Chief Scientist, Visual Layer
Chief Scientist, Virtue AI
Member of National Academy of Engineering
- My formal bio for announcements
- My formal photo for announcements
Honors and Awards
- Member of the National Academy of Engineering, elected in 2024.
- VLDB 2023 Test of Time Award for Distributed GraphLab: A framework for machine learning in the cloud with Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, and Joseph M. Hellerstein
- ACL 2020 Best Paper Award for Beyond Accuracy: Behavioral Testing of NLP models with CheckList with Marco Ribeiro and Sameer Singh
- KDD 2019 Test of Time Award for Cost-effective Outbreak Detection in Networks with Jure Leskovec, Andreas Krause, Christos Faloutsos, Jeanne VanBriesen and Natalie Glance
- IEEE Micro Best Paper of 2019 Award for A Hardware–Software Blueprint for Flexible Deep Learning Specialization with Thierry Moreau, Tianqi Chen, Luis Vega, Jared Roesch, Eddie Yan, Lianmin Zheng, Josh Fromm, Ziheng Jiang, Luis Ceze and Arvind Krishnamurthy
- ACL 2018 Honorable Mention for Best Paper Award for Semantically Equivalent Adversarial Rules for Debugging NLP Models with Marco Ribeiro and Sameer Singh
- CNET 20 most influential Latinos in tech, 2017
- KDD 2016 Audience Appreciation Award for “Why Should I Trust You?”: Explaining the Predictions of Any Classifier with Marco Ribeiro and Sameer Singh
- ICML 2016 Interpretability in Machine Learning Workshop Best Paper Award for Model- Agnostic Interpretability of Machine Learning with Marco Ribeiro and Sameer Singh
- Amazon Professorship of Machine Learning
- IJCAII-JAIR 2012 Best Paper runner-up prize in the Journal of Artificial Intelligence Research (JAIR) for Optimal Value of Information in Graphical Models with Andreas Krause. This prize is awarded to an outstanding paper and a runner-up published in JAIR in the preceding five calendar years.
- KDD 2010 Best Paper Award for Connecting the Dots Between News Articles with Dafna Shahaf
- AISTATS 2010 Best Student Paper Award for Focused Belief Propagation for Query-Specific Inference with Anton Chechetka
- PECASE 2009 – Presidential Early Career Award for Scientists and Engineers
- IJCAI 2009 Computers and Thought Award – see the slides and video of the talk
- Best Research Paper Award from the ASCE Journal of Water Resources Planning and Management Engineering for Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks with Andreas Krause, Jure Leskovec, Jeanne VanBriesen, and Christos Faloutsos
- Member of the DARPA Information Sciences and Technology (ISAT) advisory group
- Finmeccanica Chair
- “Brilliant 10” by Popular Science Magazine, 2008
- ONR Young Investigator Award, 2008
- NIPS 2007 Honorable Mention for Outstanding Paper Award for Efficient Inference for Distributions on Permutations with Jon Huang and Leo Guibas
- KDD 2007 Best Paper Award for Cost-effective Outbreak Detection in Networks with Jure Leskovec, Andreas Krause, Christos Faloutsos, Jeanne VanBriesen and Natalie Glance
- IBM Faculty Fellowship, 2006, 2007
- IJCAII-JAIR 2007 Best Paper prize in the Journal of Artificial Intelligence Research (JAIR) for Efficient Solution Algorithms for Factored MDPs with Daphne Koller, Ron Parr and Shobha Venkataraman. This prize is awarded to an outstanding paper published in JAIR in the preceding five calendar years.
- NSF CAREER Award, 2007
- IBM Faculty Fellowship, 2006, 2007
- IPSN 2006 Best Paper Award for Near-optimal Sensor Placements: Maximizing Information while Minimizing Communication Cost with Andreas Krause, Anupam Gupta and Jon Kleinberg
- Alfred P. Sloan Research Fellowship, 2006
- ICML 2005 Best Paper Runner-Up Award for Near-Optimal Sensor Placements in Gaussian Processes with Andreas Krause and Ajit Singh
- UAI 2005 Best Paper Runner-Up Award for Near-Optimal Nonmyopic Value of Information in Graphical Models with Andreas Krause
- IPSN 2005 Best Paper Award for A Robust Architecture for Distributed Inference in Sensor Networkswith Mark Paskin and Jim McFadden
- VLDB 2004 Best Paper Award for Model-Driven Data Acquisition in Sensor Networks with Amol Deshpande, Sam Madden, Joseph Hellerstein and Wei Hong
- NIPS 2003 Best Paper Award for Max-Margin Markov Networks with Ben Taskar and Daphne Koller
- Siebel Scholarship, 2009
- Stanford Centennial Teaching Assistant Award, 2000
Overview of Current and Previous Positions
Stanford University (since 2021)
I am a professor in the Computer Science Department at Stanford University. I am a member of the Stanford AI Lab (SAIL) and of the Stanford Center for AI Safety.
Visual Layer (since 2022)
I am the Chief Scientist at Visual Layer, which provides a highly scalable interactive tools for managing, enriching and curating visual data (images and videos). This company created the popular fastdup open-source project.
Virtue AI (since 2024)
I am the Chief Scientist at Virtue AI, which provides highly accurate and scalable guardrails, red-teaming and safe training for AI applications.
OctoML (since 2019)
I am on the board of directors at OctoAI (previously a technical advisor), which focuses on automatically accelerating machine learning model performance, enabling seamless deployment while maintaining accuracy. This company builds on and contributes to our Apache TVM project.
Apple (2016-2021)
I was the Senior Director of Machine Learning and AI at Apple, where I run the central ML team, which researched and developed new methods and product features, built the machine learning platform for the company, created the ML developer tools for the Apple ecosystem, and designed and offered education programs in AI.
Turi (2013-2016)
I was the CEO and co-founder of Turi, Inc. (formerly GraphLab and Dato), which developed a platform for developers and data scientist to build and deploy intelligent applications. (Acquired by Apple)
University of Washington (2012-2021)
I was the Amazon Professor of Machine Learning in Computer Science & Engineering at the University of Washington. I co-directed SAMPL with Luis Ceze, Arvind Krishnamurthy, and Zachary Tatlock, an interdisciplinary ML research group addressing problems in the intersection between ML, systems, computer architecture and programming languages. I also co-directed the MODE Lab with Emily Fox and Ben Taskar (in memoriam).
Carnegie Mellon University (2004-2012)
I was the Finmeccanica Associate Professor in the Machine Learning Department and in the Computer Science Department at Carnegie Mellon University, where I co-directed the Sense, Learn, and Act (Select) Lab with Geoff Gordon.
Intel (2003-2004)
I was a senior researcher at the Intel Research Lab in Berkeley, focusing on wireless sensor networks.
Education
- Ph.D. and M.Sc. in Computer Science from Stanford University, advised by Daphne Koller.
- Mechatronics Engineer (Mechanical Engineering, with emphasis in Automation and Systems) degree from the Polytechnic School of the University of São Paulo, Brazil.