PhD Candidate at LIAC, EPFL @SchwallerGroup. GRILL Bot 2 team member, Amazon Alexa Prize 2nd Place. 🇬🇧 in 🇨🇭
Lausanne
Joined December 2022
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Daniel Armstrong retweeted
Synthesis is a major bottleneck in drug discovery. AI synthesis planning can help propose better routes and make generative molecular design tractable.
With our retroChimera model we have been pushing the boundaries of these models further - out in @Nature today. 1/2
Daniel Armstrong retweeted
Exciting postdoc opportunity in the @SchwallerGroup at EPFL!
We're hiring a postdoc to advance ML-driven synthesis planning after Zlatko Joncev’s successful exit to co-found B-12 (YC '25) 🚀
Work on:
- LLMs for strategic synthesis planning
- Chemical reasoning at scale
- Building the next-gen framework for retrosynthesis
Our recent preprint shows that LLMs can guide synthesis planning with natural-language strategies — combining AI reasoning with traditional chemical tools (arxiv.org/abs/2503.08537).
Join us at the intersection of chemistry & AI. Up to 2 years. Based in Lausanne 🇨🇭
Apply: forms.fillout.com/t/nnxVE3Rc…
#ChemTwitter #MachineLearning #SynthesisPlanning #PostdocPosition
Daniel Armstrong retweeted
Out now! @pschwllr, @SchwallerGroup, @loic_roch, @VictorSabanza and colleagues provide guidelines and recommendations for when to use multi-fidelity Bayesian optimization over their single-fidelity counterparts
nature.com/articles/s43588-0…
🔓rdcu.be/exyUh
Happy to present a poster of my work on starting material constrained synthesis planning, Tango*, in the AI4Materials workshop at #ICLR2025 in 🇸🇬 Thanks to collaborators @JeffGuo__ and @ZJoncev and my PI
@pschwllr!
1/ Starting material constrained synthesis planning is now possible using a general retrosynthesis algorithm *without* training a dedicated value network!
Check-out our new paper, TangoStar.
Preprint : arxiv.org/abs/2412.03424
Daniel Armstrong retweeted
AdsMT is finally out in @NatureComms 🥳
It is designed for rapid prediction of global minimum adsorption energy (GMAE) from surface graphs and adsorbate descriptors.
Thanks to @XuHuang461675 , @pschwllr and @NCCR_Catalysis!
Paper & code: nature.com/articles/s41467-0…
@SchwallerGroup
New LIAC ( @SchwallerGroup ) pre-print out! Here we show that language models understand synthetic strategy, reaction mechanism and chemical structure.
Many thanks to my co-authors @drecmb, @TheoNeukomm and @ZJoncev along-with our PI @pschwllr.
Paper:
arxiv.org/abs/2503.08537
LLMs are pretty bad at writing molecules, but quite good at analyzing mols and reactions!
In our new work we use LLMs+search in chemical tasks, unlocking steerable synth. planning and mechanism prediction 🌟
1/
@TheoNeukomm @d_armstr @ZJoncev @pschwllr
arxiv.org/abs/2503.08537
Reaction feasibility is a huge issue in retrosynthesis tools; models often propose reactions which are incompatible with different regions in the molecule. Here the LLM correctly tags the highlighted alcohol group as incompatible with the bromide and suggests MOM/TBS protection.
1/ Starting material constrained synthesis planning is now possible using a general retrosynthesis algorithm *without* training a dedicated value network!
Check-out our new paper, TangoStar.
Preprint : arxiv.org/abs/2412.03424
4/ We thank developed this work using code and models provided by the Coley Group (@cwcoley) in their recent work, DESP.
Code : github.com/coleygroup/desp
Paper : arxiv.org/abs/2407.06334
5/ Thanks to my PI @pschwllr (@SchwallerGroup), my collaborators @JeffGuo__ and @ZJoncev, and the Swiss National Science Foundation (@snsf_ch) for funding this work.
Daniel Armstrong retweeted
Another great #Ellis workshop on ML for Molecular Discovery. Thanks to @gklambauer, @fra_grisoni, and the whole organizing team!
Proud of our team's contributions - 3 posters (@d_armstr, @kelmannson, @ZJoncev) and an excellent talk by @SarinaKopf! Very well done!
#compchem
Daniel Armstrong retweeted
ChemCrow is finally our in @NatMachIntell! 🥳🔥
nature.com/articles/s42256-0…
It took us more than a year since the preprint, but we made it
With @SamCox822 @andrewwhite01 @CarloBalda97 @OSchilter @CarloBalda97 @andrewwhite01 @pschwllr.
@EPFL_en @NCCR_Catalysis @FutureHouseSF
