Research director at Meta leading the Adaptive Experimentation team. Bayesian optimization, Bayesian ML, bandits, RL, experiments, causal inference.
Joined May 2007
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36 Photos and videos
19 Nov 2025
Proud to share the 1.0 release of Ax, our platform for adaptive experimentation platform. We've been using it for the past 6 years for optimizing everything from end-to-end AI systems, recommender systems, AR hardware, and material science applications.
engineering.fb.com/2025/11/1…
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19 Nov 2025
In our paper, we demonstrate superior optimization performance on tiny budgets for a variety of tasks, including single- and multi-objective, high-dimensional inputs, discrete inputs noisy outcomes, including parallel/async and early termination settings. proceedings.mlr.press/v293/o…
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19 Nov 2025
Ax 1.0 includes simplified interfaces for efficient optimization and experiment understanding, ax.dev/docs/tutorials/gettin…, as well as APIs for aiding the development, integration, and benchmarking of novel methods for BayesOpt and active learning with BoTorch.
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eytan bakshy retweeted
16 Jul 2025
Big thanks to my amazing collaborators: Sebastian Ament, @MaxBalandat , @davidmeriksson , @jmhernandez233 , and @eytan !
If you are attending ICML 2025, feel free to check out our poster and have a chat with us!
Thu 11:00am - 1:30pm in East Exhibition Hall A-B, # E-1308
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16 Jul 2025
Did you know that concrete accounts for 8% of global CO2 emissions? I'm delighted to share that after 2 years of development, we've successfully deployed our strong, low-carbon emission "AI concrete mix" at the latest Meta datacenter.
engineering.fb.com/2025/07/1…
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16 Jul 2025
This work was a collaboration between the Meta Adaptive Experimentation and Infrastructure Data Science teams, UIUC, and Amrize. This mix was designed using batch multi-objective Bayesian optimization with BoTorch. Source code and data is available at github.com/facebookresearch/…
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6 Aug 2024
Doing research on probabilistic modeling, decision-making under uncertainty, or efficient learning and optimization? Come to NeurIPS to present your work! Submissions due August 29th. gp-seminar-series.github.io/…
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24 May 2024
Interested in AutoML, active learning, Bayesian machine learning, or Bayesian optimization? We are hiring post-docs for the Adaptive Experimentation team! Experience with BoTorch, GenAI, or causal inference is a plus! Position in NYC, SF, and Menlo Park.
metacareers.com/jobs/8316830…
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26 Apr 2024
Is there a bug in OpenReview for #UAI2024? We submitted 3 papers, and none of the reviewers updated their responses and there are only reject or accept decisions—no meta-review.
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eytan bakshy retweeted
23 Apr 2024
Software package announcement!
The Geometric Kernels package, which implements various geometric Gaussian process models from my papers - on manifolds, graphs, and similar - is now on PyPi!
It can be installed with `pip install geometric_kernels`.
Check it out!
23 Apr 2024
Excited to announce a new release of GeometricKernels!
You can now install the package via `pip install geometric_kernels`!
Featuring new spaces, efficient GP sampling, and a much simpler interface, in addition to brand new tutorials & enhanced docs!
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15 Feb 2024
Now hiring research scientists for the AE team!
14 Feb 2024
I'm hiring! We have an exciting opportunity for a full-time Research Scientist to join me and my amazing colleagues on Meta’s Adaptive Experimentation (AE) team. We specialize in Bayesian optimization, probabilistic modeling, and sample-efficient decision-making.
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9 Feb 2024
@overleaf your "green" status is not accurate status.overleaf.com/ Multiple colleagues are having issues. I have also reported this issue via the Overleaf bug report flow.
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11 Dec 2023
Very much looking forward to the Adaptive Experimental Design workshop at NeurIPS this Saturday!
10 Dec 2023
🚀 Just one week until the #NeurIPS2023 workshop on Adaptive Experimental Design & Active Learning in the Real World! 🔬 Exciting lineup of speakers awaits you, featuring cutting-edge insights.
Explore our fantastic schedule at:
neurips.cc/virtual/2023/work…
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eytan bakshy retweeted
11 Dec 2023
Two fantastic hands-on tutorials on Ax and Pearl from @eytan and @ZheqingZhu’s teams at @AIatMeta!
Definitely check out the colab tutorial file for Ax: tinyurl.com/ax-neurips2023
The Pearl colab file is linked to in their GitHub readme: github.com/facebookresearch/…
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28 Nov 2023
We are now accepting applications for internships on our team. If you are interested in Bayesian optimization active learning, learning with human feedback, or applications of transformers to probabilistic modeling and causal inference please consider this opportunity!
21 Nov 2023
2024 PhD Internship opportunity! Join me and my amazing colleagues on Meta's Adaptive Experimentation team to work on Bayesian optimization, probabilistic modeling / Gaussian Processes, and sample-efficient decision making: metacareers.com/jobs/9056341…
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3 Nov 2023
EI its variants are the most popular acquisition functions in BayesOpt, but is no longer SoTA. We show that this is bc EI is hard to optimize numerically due to vanishing gradients, study consequences of this & propose a drop in replacement. Follow below for a sick BoTorch demo!
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eytan bakshy retweeted
24 Oct 2023
New working paper with a fantastic team of coauthors:
we study when and how to design cluster experiments with network spillovers.
arxiv.org/pdf/2310.14983.pdf
with @lihua_lei_stat , @guido_imbens, Brian Karrer, Okke Schrijvers, Liang Shi
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