Using SOTA techniques, we're now able
to accurately predict exact molecular structures of NOVEL compounds directly from mass
spectra—INDEPENDENT of instrument type.
Future developments may incorporate additional modalities,
such as FTIR, to enable multimodal data fusion and further enhance structural inference.
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Expert chemist-level molecular insight
Our AI ingests SMILES data to assemble a complete molecular dossier—substructure, functional groups,
receptor-binding profiles, and key physicochemical metrics—leveraging this rich information to pinpoint the
true identity of novel compounds.
I'm Alexander Huynh, a Software Developer with a strong Physics and Math background from Purdue University.
Skilled in languages like C#
and Python, I excel in both high-level and lower-level programming challenges. My aim is to innovate and
optimize software systems,
bringing a research-driven problem-solving approach to any tech team.
