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DTSTART;TZID=UTC:20251101T080000
DTEND;TZID=UTC:20260109T120000
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SUMMARY:Catechol Benchmark Hackathon (NeurIPS 2025 DnB)
DESCRIPTION:ML model-building challenge for reaction yield prediction for catechol rearrangement reaction from transient flow dataset.\n\n\n\n\n\n\n\n\n\n\n\nKEY DETAILS\n\n\n\n\nLAUNCH DATE3rd November 8:00 AM CLOSING DATE9th January 12:00 PM \n\n\n\nVIEW COMPETITION ON kaggle\n\n\n\n\n\n\n\n\nOverview:\n\n\n\nWelcome to the Catechol Benchmark Hackathon competition!  \n\n\n\nIn this competition\, we will have multiple teams trying to prediction reaction outcomes of the rearrangement of allyl substituted catechol under different solvent and process conditions. \n\n\n\nThe data-set consists of multiple transient flow ramps\, which allow us to assess the amount of starting material and products after seeing the reaction at different temperatures and residence times (i.e. how long the chemicals reacted for). We also include many data-points for binary mixtures of solvents\, allowing us to treat the usually discrete solvent selection problem as a semi-continuous one. \n\n\n\nGoal: Build a machine learning model that achieves the best predictions on the collected data\, as measured by a cross-validation procedure\, which will demonstrate the ability of your model to predict on unseen solvent data.  \n\n\n\nDescription\n\n\n\nMore details of the data-set: \n\n\n\nData size and inputs\n\n\n\nThe data-set consists of 1227 data points on the allyl substituted catechol reaction\, covering 24 solvents at different temperatures and residence times. The inputs of the model will consist of: \n\n\n\n(1) A selection of two different solvents\, Solvent A and Solvent B\, with the corresponding amount of Solvent B in the mixture given by the percentage %B. \n\n\n\n(2) The temperature in °C at which the reaction was carried out. \n\n\n\n(3) The residence time of the reaction\, i.e.\, how long the reactants were subject to the reaction conditions applied. \n\n\n\nThe outputs consist of the yield of the starting material and the two observed products. We also created a smaller data set of 656 data-points in which solvent mixtures are not considered\, and only single solvent data\, along with residence times and temperatures is considered. \n\n\n\nEvaluation\n\n\n\nSubmissions will be evaluated according to a cross-validation procedure. This public notebook (https://www.kaggle.com/code/josepablofolch/catechol-benchmark-hackathon-template) shows the structure any submitted notebook must follow. In order to ensure fair participation among all competitors\, the submission must have the same last three cells as in the notebook template\, with the only allowed change being the line where the model is defined.  \n\n\n\nFor the avoidance of doubt\, the line  model = MLPModel() can be replaced with a new model definition in the third to last and second to last cells\, but everything else must remain the same. \n\n\n\nPrizes\n\n\n\nPrizes will be awarded on a per-person basis as follows: \n\n\n\nTotal Prizes Available: £2\,000 (GBP) \n\n\n\n\n1st Place – £250 per person (maximum £1000 total for a team of four)\n\n\n\n2nd Place – £150 per person (maximum £600 total for a team of four)\n\n\n\n3rd Place – £100 per person (maximum £400 total for a team of four)
URL:https://aichemy.ac.uk/event/catechol-benchmark-hackathon-neurips-2025-dnb/
CATEGORIES:Hackathon
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260121T140000
DTEND;TZID=UTC:20260121T150000
DTSTAMP:20260412T154650
CREATED:20251125T150202Z
LAST-MODIFIED:20260128T132906Z
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SUMMARY:AIchemy’s Monthly Webinar Series - January 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE21 January 2026 TIME14:00 – 15:00 COSTFree LOCATIONOnline MS Teams \n\n\n\nREGISTRATION CLOSED\n\n\n\n\n\n\n\n\nWe are delighted to welcome you to our AIchemy Hub’s monthly webinar series. \n\n\n\nThis month’s talks: \n\n\n\nAndrea Dimitracopoulos – COO & Co-founder\, Deepmirror \n\n\n\nTalk Title: Tackling Drug Design Challenges with Molecular Assay FingerprintsIn the journey from idea to clinic\, drug discovery teams must balance potency with a wide set of ADMET constraints (solubility\, permeability\, CNS penetration\, clearance\, toxicity risk\, and more). AI can reduce the cost and time of small-molecule drug design by improving both property prediction and molecule prioritisation across the design–make–test–analyse (DMTA) cycle. In this talk\, we introduce molecular assay fingerprints as a learned representation for modelling assay endpoints. This approach combines pre-training on a large assay database with programme-specific fine-tuning to improve prediction accuracy. It also leverages Gaussian processes to quantify predictive uncertainty\, which can then be used to prioritise compounds and explore chemical space efficiently – accelerating programme progression. Benchmarking on private drug programmes illustrates how assay fingerprints can improve predictive accuracy for both potency and key ADMET properties\, dramatically reducing the number of design cycles. \n\n\n\nFederico Ottomano – Imperial College LondonTalk Title: Scalable molecular elucidation from IR and NMR spectroscopy using Machine Learning \n\n\n\n\n\nSpeakers\n\n\n\n\n\nAndrea DimitracopoulosCOO & Co-founder\, Deepmirror\n\n\n\n\n\nFederico Ottomano Postdoctoral Research Assistant\, Imperial College London\n\n\n\n\n\nGabriella Pizzuto – Webinar ChairLecturer (Assistant Professor)
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-january-2026/
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260127T090000
DTEND;TZID=UTC:20260127T170000
DTSTAMP:20260412T154650
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SUMMARY:New Starters in AI for Chemistry
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE27 January 2026 TIME09:00 – 17:00 COSTFREE REGISTRATION DEADLINE23rd January 2026 \n\n\n\nView Agenda\n\n\n\nread the highlights blog\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nUNIVERSITY OF LEEDSCLOTH HALL COURT\, QUEBEC ST\, LS1 2HA \n\n\n\n\n\n\n\n\nJoin us for a one day Symposium at Cloth Hall Court\, University of Leeds where we aim to bring together recently appointed academics\, postdoctoral researchers and late-stage PhD students who are developing and deploying AI at the chemistry interface.We welcome researchers from all backgrounds across the physical sciences. Our aim is to build a supportive and inclusive community where you can learn\, share experiences\, and explore topical areas such as molecular and materials design\, generative models\, robotics and automation for autonomous experimentation\, data-driven simulation\, and green and sustainable chemistry.AI and ML is opening new frontiers across the chemical sciences from accelerating materials discovery\, to enabling sustainable reactions and autonomous experimentation. If you’re ready to join the community\, and be part of shaping the future of AI in chemistry\, this is the place to begin.  \n\n\n\n\n\n\n\nWho Should Attend: \n\n\n\nThe event will be open to all but is ideally suited to academic staff\, postdoctoral researchers and PhD students from a range of backgrounds and operating at the AI for Chemistry interface.Early-career academics are encouraged to submit applications for oral presentations.Postdoctoral researchers are encouraged to submit applications for an oral presentation or a poster presentation\, depending on the stage of the work that will be presented..PhD students are encouraged to submit applications for poster presentations. \n\n\n\n\n\nConfirmed Speakers\n\n\n\n\n\nDr Gabriella PizzutoUniversity of Liverpool\n\n\n\n\n\nDr Sam Parkinson Aston University\n\n\n\n\n\nDr Emma King-Smith University of Edinburgh\n\n\n\n\n\nDr Michael TilbyUniversity of Bristol\n\n\n\n\n\n\n\nDr Angelo FreiUniversity of York\n\n\n\n\n\nDr Xenfon EvangelopoulosUniversity of Liverpool\n\n\n\n\n\nDr Joe Marsden University of Leeds\n\n\n\n\n\nDr Elenora RicciUniversity of Edinburgh\n\n\n\n\n\nDr William RobinsonRadboud University\n\n\n\n\n\n\n\nContact Details\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk. \n\n\n\n\n\nThe Organising Committee\n\n\n\nAIchemy HubUniversity of LeedsDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr Adam ClaytonDr Gilian Thomas
URL:https://aichemy.ac.uk/event/new-starters-in-ai-for-chemistry/
CATEGORIES:Symposium
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