Research Scientist Manager, Adaptive Experimentation team @Meta. Creator of BoTorch. Interested in Bayesian Optimization and the like. Scuba Instructor.
Joined September 2018
- Tweets 35
- Following 65
- Followers 329
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2 Photos and videos
Max Balandat retweeted
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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Max Balandat retweeted
16 Jul 2025
Excited to share our ICML 2025 paper:
"Scalable Gaussian Processes with Latent Kronecker Structure"
We unlock efficient linear algebra for your kernel matrix which *almost* has Kronecker product structure.
Check out our paper here:
arxiv.org/abs/2506.06895
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Max Balandat retweeted
8 Jul 2025
Compute is increasing much faster than data. How can we improve classical supervised learning long term (the underlying tech of most of GenAI)?
Our ICML position paper's answer: simply train on a bunch of artificial data (noise) and only do inference on real-world data! 1/n
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10 Dec 2023
Heading to NOLA for #NeurIPS2023 - find me at our (spotlight!) poster on logEI (Poster Session 2 on Tue): x.com/SebastianAment/status/… - or DM me if you want to chat about Bayesian Optimization on the side.
P.S.: We're hiring PhD Research Interns for 2024: x.com/MaxBalandat/status/172…
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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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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Max Balandat retweeted
23 Oct 2023
Pleased to share that we have a post-doctoral position on the Adaptive Experimentation team at Meta. Please share this on with others interested in Bayesian optimization, active learning, or Bayesian deep learning! metacareers.com/v2/jobs/3474…
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Max Balandat retweeted
23 Apr 2023
High-Dimensional Combinatorial BO via Dictionary-based Embeddings (BODi) will be presented at AISTATS @aistats_conf next week.
Paper: arxiv.org/pdf/2303.01774.pdf
Code: github.com/aryandeshwal/BODi
w/ @deshwal_aryan, @SebastianAment, @davidmeriksson, @MaxBalandat, and @eytan
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Max Balandat retweeted
1 Mar 2023
Are you attending #SIAMCSE23 and want to learn about how Bayesian optimization can be used for problems such as peptide design, molecular design, and optimizing stellarator coils?
Join @MaxBalandat and I tomorrow in our minisymposium on Bayesian optimization in the real-world.
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Max Balandat retweeted
21 Dec 2022
On this darkest day of the year, allow me to share a bit of light in the form of a fantastic tutorial on adaptive experimentation put together by my student @SterlingBaird1. Here is the first video in the series: youtu.be/Evua529dAgc
new posts through Christmas ;)
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22 Nov 2022
I’m looking forward to presenting our poster on LinearOperator [github.com/cornellius-gp/lin…] - a library for structured linear algebra in @PyTorch - at this year's #PyTorchConference (co-located w/ NeurIPS).
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Max Balandat retweeted
3 Dec 2022
📢 Come to our @NeurIPSConf tutorial on Advances in Bayesian Optimization
Dec 5, Mon, 11am to 1:30pm PST
bayesopt-tutorial.github.io/
Speakers: @VGAglietti, Jake Gardner, me
Panelists: @StefanieJegelka, @jmhernandez233, Roman Garnett, @eytan, @syrineblk
Post your questions below.
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If you want to meet @MaxBalandat & @davidmeriksson and learn more, register here for #PyTorchConference on December 2:
🤝In-Person in New Orleans Registration: cvent.me/WX4Yaa
📺Virtual Streaming Event RSVP: cvent.me/G4AzoW
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22 Nov 2022
Apply to attend in-person or watch the live stream of the conference on Dec. 2nd. [ pytorchconference22.splashth…]
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29 Oct 2022
Came across this paper bringing together two of my passions: The ocean and sample-efficient optimization (the paper uses BoTorch for multi-objective optimization of a catamaran hull design via CFD simulations): sciencedirect.com/science/ar…
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Max Balandat retweeted
20 Oct 2022
I am excited to share our new NeurIPS paper "Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization"! Many thanks to my collaborators @wanxingchen_, @davidmeriksson, @MaxBalandat, @maosbot, @eytan
#NeurIPS2022
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Max Balandat retweeted
20 Jul 2022
Come by our spotlight talk today (535p ET) and poster session (630-830p ET) at #ICML2022 on robust multi-objective Bayesian optimization (icml.cc/virtual/2022/spotlig…)!
We now have a simple tutorial in BoTorch! botorch.org/tutorials/robust…
with Sait, @MaxBalandat, @maosbot, Enlu, @eytan
15 May 2022
Excited to share that our paper "Robust Multi-Objective Bayesian Optimization under Input Noise" has been accepted at ICML!
Preprint: arxiv.org/abs/2202.07549
Code: github.com/facebookresearch/…
with Sait Cakmak, @MaxBalandat, @maosbot, Enlu Zhou, and @eytan
#icml2022
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Max Balandat retweeted
17 Jun 2022
I am excited to share that our paper “Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces” has been accepted for an oral presentation at UAI 2022!
w/ @davidmeriksson, @MaxBalandat, @eytan
Paper: arxiv.org/abs/2109.10964
#uai2022
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Max Balandat retweeted
15 May 2022
Excited to share that our paper "Robust Multi-Objective Bayesian Optimization under Input Noise" has been accepted at ICML!
Preprint: arxiv.org/abs/2202.07549
Code: github.com/facebookresearch/…
with Sait Cakmak, @MaxBalandat, @maosbot, Enlu Zhou, and @eytan
#icml2022
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Max Balandat retweeted
7 Dec 2021
Our paper on Bayesian optimization w/heterogenous & unknown evaluation costs, subject to a total budget: arxiv.org/pdf/2111.06537.pdf. This is work led by Raul Astudillo, along w/@maxbalandat, @eytan, @peter_i_frazier. Join us at #NeurIPS2021 poster session 4 (12/8, 4:30 PST)!
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