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BEGIN:VEVENT
DTSTART;TZID=UTC:20260323T090000
DTEND;TZID=UTC:20260324T170000
DTSTAMP:20260417T121204
CREATED:20251127T122359Z
LAST-MODIFIED:20260401T132322Z
UID:435-1774256400-1774371600@ocamm.fi
SUMMARY:TurboGAP School 2026
DESCRIPTION:Motivation and overview\nThe field of atomistic ML has exploded in recent years. These models allow us to tackle materials modeling problems that were completely out of reach just a few years ago. Although most of the developments in this field have gravitated around ML interatomic potentials (MLPs)\, other properties which are a function of atomic coordinates\, like core-electron binding energies\, local electronic density of states\, and so on\, have also benefited from these developments. The software ecosystem has flourished in parallel with the methodological advancements. Unlike for DFT\, where a few codes dominate\, the MLP scene is fragmented due to the relative ease of producing functional code. While this might seem to be problematic\, in practice it has helped drive many methodological advancements because the barrier to implementation of new features and experimental ideas is comparatively low and many more groups can participate. \nThe TurboGAP code (turbogap.fi) is developed at Aalto University by the Caro group\, with support from CSC and participation of other local groups for specific features. The development of the code was initially motivated by the need for speeding up calculations based on GAP MLPs\, but has since branched out; beyond-state-of-the-art methodologies in van der Waals corrections [PRB 111\, 054103 (2025)] or inverse structure prediction [JACS 146\, 14645 (2024); arXiv:2508.17132] have been developed and implemented within the TurboGAP development efforts. The code has full MPI support and a development branch\, to be merged soon\, has full MPI+GPU support. TurboGAP is\, to our knowledge\, the only MLP engine whose development is currently led by a Finnish institution. The purpose of this School is to gather the local community from Finnish higher-education and research institutions interested in MLP modeling of molecules and materials and introduce the general MLP methodology as well as the TurboGAP code specifically. The hope is that this will serve to both train local junior scientists in these new techniques and expand the TurboGAP user base\, potentially also leading to new collaborations in development and applications. In addition\, the School is keen to accept international attendees whose presence might contribute to these goals. \nParticipating in the School\nThe number of participants is limited to 20. Interested candidates can apply until 21 December 2025 at midnight (Finnish time) by following the link to the application form. The application form is very short\, we only collect contact and institutional information as well as a brief motivation statement to participate. A maximum of 20 applicants will be invited by 31 December 2025 to participate and will have until 18 January 2026 to register. The registration is free of cost thanks to the financial support of CECAM-FI. If more than 20 applications are received\, the selection of participants will be done by considering the motivation statement and trying to balance the participation from institutions across Finland and some representation from international institutions. \nProgram\nAll the lectures take place in room D311 (Ke 5) of the main building of the School of Chemical Engineering\, Aalto University\, Kemistintie 1\, 02150 Espoo. The classroom is located on floor 3\, one flight of stairs up from the buiding’s main entrance. The coffee and lunch breaks take place in an adjacent lobby. \nAll the hands-on sessions will be run within a JupyterLab virtual environment\, Noppe\, provided by CSC\, the Finnish supercomputing center. The TurboGAP School’s lecturers have set up all the hands-on tutorials and you do not have to do any preparations to run the examples: just bring your own laptop\, a web browser is enough. Instructions for using Noppe will be given to you during Session 2 of the School. \n\n\n\n\n\n\n\nMonday 23 March\n\n\nTuesday 24 March\n\n\n\n\n9:00-10:30\n\n\nSession 1: Introduction to MLIPs and GAP (Miguel Caro)\n\n\nSession 5: Radiation damage simulations (Ali Hamedani)\n\n\n\n\n10:30-11:00\n\n\nCoffee break\n\n\nCoffee break\n\n\n\n\n11:00-12:30\n\n\nSession 2: Overview of the TurboGAP code\, virtual environment for the hands-on session and basic example simulation (Miguel Caro & Tigany Zarrouk)\n\n\nSession 6: Van der Waals corrections and their integration with MLIP (Heikki Muhli)\n\n\n\n\n12:30-13:30\n\n\nLunch (catered)\n\n\nLunch (catered)\n\n\n\n\n13:30-15:00\n\n\nSession 3: Database curation and model training (Rina Ibragimova)\n\n\nSession 7: Experimental observable prediction and reverse structure optimization: Molecular augmented dynamics (Tigany Zarrouk)\n\n\n\n\n15:00-15:30\n\n\nBreak (smoothies)\n\n\nBreak (smoothies)\n\n\n\n\n15:30-17:00\n\n\nSession 4: Analysis and visualization of simulation results (Patricia Hernández-León)\n\n\nSession 8: Grand canonical Monte Carlo simulations for variable-particle-number simulation (Alexis Front)\n\n\n\n\n17:00-20:00\n\n\nSocial gathering at Masis Brewery (with pizzas\, including vegan and vegetarian options)\n\n\n\n\n\nThe lecturers will be the TurboGAP development team\, members of the Caro group\, and collaborators: \n\nProf. Miguel Caro (TurboGAP team PI)\nDr. Tigany Zarrouk (TurboGAP lead developer)\nDr. Rina Ibragimova\nDr. Heikki Muhli\nPatricia Hernández-León\nDr. Alexis Front\nDr. Ali Hamedani\n\nParticipants\nTrainees\n\n\n\nName\nInstitution\nEmail\n\n\nBiswarup Biswas\nUniversity of Turku\nbiswarup.biswas@utu.fi\n\n\nXiaoya Chang\nAalto University\nxiaoya.chang@aalto.fi\n\n\nFarshad Esmaeilian\nUniversity of Eastern Finland\nfarshad.esmaeilian@uef.fi\n\n\nLeonardo Andres Espinosa Leal\nVTT – Technical Research Center of Finland\n\n\n\nArtem Glova\nAalto University\nartem.glova@aalto.fi\n\n\nAapo Haavisto\nAalto University\naapo.2.haavisto@aalto.fi\n\n\nAdam Harmat\nAalto University\nadam.harmat@aalto.fi\n\n\nHanan Ibrahim\nUniversity of Jyväskylä\nhanan.h.ibrahim@jyu.fi\n\n\nRasmus Ikonen\nUniversity of Jyväskylä\nrasmus.l.o.ikonen@jyu.fi\n\n\nAatif Imran\nUniversity of Turku\naatif.a.imran@utu.fi\n\n\nJyri Kimari\nUniversity of Helsinki\n\n\n\nKonstantinos Konstantinou\nUniversity of Turku\nkonstantinos.konstantinou@utu.fi\n\n\nTiago Lopes\nUniversity of Helsinki\ntiago.lopes@helsinki.fi\n\n\nSanni Määttänen\nAalto University\nsanni.maattanen@aalto.fi\n\n\nMario Mäkinen\nAalto University\nmario.makinen@aalto.fi\n\n\nGianmarco Midena\nAalto University\ngianmarco.midena@aalto.fi\n\n\nAneta Niklas\nUniversity of Oxford\naneta.niklas@chem.ox.ac.uk\n\n\nFatemeh Safari\nUniversity of Turku\nfatemeh.f.safari@utu.fi\n\n\nNasrullah Sarker\nUniversity of Eastern Finland\nnasarker@uef.fi\n\n\nTimo Weckman\nUniversity of Jyväskylä\n\n\n\nLitong Wu\nUniversity of Oxford\nlitong.wu@jesus.ox.ac.uk\n\n\nYongchao Wu\nAalto University\nyongchao.wu@aalto.fi\n\n\n\nDAS group members\n\n\n\nName\nInstitution\nEmail\n\n\nReece Brooking\nAalto University\nreece.brooking@aalto.fi\n\n\nYuto Iwasaki\nFujitsu Ltd.\next-yuto.iwasaki@aalto.fi\n\n\nOndrej Krejci\nAalto University\nondrej.krejci@aalto.fi\n\n\nSampsa Mäenpää\nAalto University\nsampsa.maenpaa@aalto.fi\n\n\nVeera Mäkimartti\nAalto University\nveera.makimartti@aalto.fi\n\n\nHenrik Stenbrink\nAalto University\nnilshenriksamuli.stenbrink@aalto.fi\n\n\nMatias Vartiainen\nAalto University\nmatias.vartiainen@aalto.fi\n\n\nMilona Weck\nAalto University\nmilona.weck@aalto.fi\n\n\nYucheng Zhang\nAalto University\nyucheng.zhang@aalto.fi\n\n\n\nLecturers\n\n\n\nName\nInstitution\nEmail\n\n\nMiguel Caro\nAalto University\nmiguel.caro@aalto.fi\n\n\nAlexis Front\nAalto University\nalexis.front@aalto.fi\n\n\nAli Hamedani\nAalto University\nali.hamedani@aalto.fi\n\n\nPatricia Hernández-León\nAalto University\npatricia.hernandezleon@aalto.fi\n\n\nRina Ibragimova\nAalto University\nrina.ibragimova@aalto.fi\n\n\nHeikki Muhli\nAalto University\nheikki.muhli@aalto.fi\n\n\nTigany Zarrouk\nAalto University\ntigany.zarrouk@aalto.fi\n\n\n\nImportant dates\n\n21 December 2025 – Deadline for applications\nBy 31 December 2025 – Notification to selected participants\n18 January 2026 – Deadline for registration of accepted participants\n23-24 March 2026 – TurboGAP School 2026\n\nVenue\, transportation & accommodation\nVenue\n \nThe conference will take place in the main campus of Aalto University\, in the Helsinki metropolitan area. The venue is the Aalto University’s School of Chemical Engineering’s main building\, Kemistintie 1\, Espoo\, 02150 Finland. \nGetting there & around\nAalto University is very well connected within the Helsinki metro area. The Otaniemi campus can be reached via metro (“Aalto University” stop) and the light rail (“Maari”\, “Aalto-yliopisto” and “Otaranta” stops\, from west to east). Please visit the website of HSL\, the company operating the public transport system in the Helsinki metro area. This includes buses\, the metro\, trains\, downtown trams\, the light rail\, and some municipal ferry services (e.g.\, to the Suomenlinna fortress island). Public transport in the Helsinki metro area is safe\, clean and reliable. The easiest way to use the public transport system is to download the HSL app on your phone. \nThe Aalto University campus can be reached from Helsinki airport\, e.g.\, by combining the train with the metro (changing at Helsinki’s Central Railway Station). Non-collective public transport options like taxis are also available\, including popular apps like Uber; these are significantly pricier than collective transportations but might be more convenient depending on the situation (e.g.\, if you are in a hurry to reach the airport). \nAccommodation\nAalto University is located on the Otaniemi campus. Otaniemi is a district of the city of Espoo\, located within the Helsinki metropolitan area. There are various on-campus accommodation options in Otaniemi\, for instance the Radisson Blu Espoo hotel. Since the Otanimi campus is connected to Helsinki by metro\, and the commuting time is ~15 minutes from Helsinki city center\, it is entirely possible to stay in Helsinki and commute every day to the School. This opens the door to a wider variety of accommodation options in terms of quality and price. Two options for on-campus accommodation are: \n\nRadisson Blu Espoo (from ~100 EUR/night)\nHeymo 1 by Sokos (from ~85 EUR/night)\n\nFor accommodation options in Helsinki\, popular aggregators like Booking.com offer a “map-view” of the city and their user ratings are usually a good indicator of quality and value. If you opt for booking accommodation in Helsinki city center and commuting every day to the Aalto campus\, we recommend that you reserve a hotel within walking distance of a metro station for convenience\, e.g.\, stations “Ruoholahti”\, “Kamppi”\, “Central Railway Station”\, etc. \nFunding\nThe TurboGAP School 2026 is possible thanks to the financial support from CECAM-FI.
URL:https://ocamm.fi/event/turbogap-school-2026/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:School
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2025/11/Turbogap_logo.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260325T101500
DTEND;TZID=UTC:20260325T110000
DTSTAMP:20260417T121204
CREATED:20260213T125711Z
LAST-MODIFIED:20260225T063525Z
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SUMMARY:Seminar by Volker Deringer
DESCRIPTION:Prof. Volker Deringer from the University of Oxford will deliver an invited seminar on Wednesday 25 March 2025 at 10:15-11:00 in hall A304 (Ke2) of the Aalto University School of Chemical Engineering main building\, Kemistintie 1\, Espoo. \nMachine-learned interatomic potentials for materials chemistry \nVolker Deringer \nDepartment of Chemistry\, University of Oxford \nMachine-learned interatomic potentials (MLIPs) are now widely used in atomistic simulations\, giving access to length and time scales that are otherwise inaccessible to first-principles methods. Their reliability in practice\, however\, depends crucially on the quality and coverage of the training data. In this talk\, I will discuss data-efficient approaches to constructing MLIPs\, including ML-accelerated first-principles molecular dynamics for generating reference configurations\, and automated de novo exploration of relevant configurational spaces using the autoplex software. I will also highlight model-distillation strategies (specifically\, a teacher–student approach) using accurate but computationally costly models to train fast\, task-specific MLIPs for downstream applications. I will illustrate these ideas using examples of structurally complex materials: amorphous silicon\, graphene oxide\, and phase-change materials that are used in data storage and neuromorphic computing.
URL:https://ocamm.fi/event/seminar-by-volker-deringer/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2023/09/volker-deringer.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
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DTSTART;TZID=UTC:20260416T100000
DTEND;TZID=UTC:20260416T153500
DTSTAMP:20260417T121204
CREATED:20260213T124618Z
LAST-MODIFIED:20260213T124623Z
UID:450-1776333600-1776353700@ocamm.fi
SUMMARY:ChemBio Finland: Session Machine Learning in Chemistry
DESCRIPTION:As part of the ChemBio Finland 2026 Exhibition\, held at Messukeskus in Helsinki\, OCAMM and Aalto University professors Kari Laasonen and Miguel Caro are chairing a session on Machine Learning in Chemistry. The sympossium will take place on the second day of the ChemBio Finland event\, 16 April 2026 between 10:00 and 15:35 in room 5 (“Sali 5”). The official website of the event is this\, where you can find more information about the venue and the other parallel sessions. \nRegistration\nThe registration is free of charge. To register as a visitor\, go to the official website or go directly to the registration page. \nProgram\nThe official web site for the program is here. There\, you can also check the other sessions taking place in parallel at the same venue during ChemBio 2026. \nChairs: Kari Laasonen and Miguel Caro \nChairperson 10-12 Kari Laasonen \n\n10:00–10:05 Opening. Kari Laasonen\, Aalto University\n10:05–10:30 Autonomous analysis\, manipulation and reactions in Scanning Probe Microscopy. Nian Wu\, Aalto University\n10:30–10:55 Decoding Surface Adsorption Chemistry with Active Learning. Milica Todorovic\, University of Turku\n10:55–11:20 LUMI-AI: A novel platform for AI4Science. Pekka Manninen\, CSC Tieteen tietotekniikan keskus\n11:20–11:55 ML-trained interaction potential for simulations of graphite nucleation from paramagnetic Fe-C melt. Jaakko Akola\, NTNU\, Trondheim\n12:00–13:00 Lunch break\n\nChairperson 13-14:15 Miguel Caro \n\n13:00–13:25 Advancing Biomolecular Simulations with ML: GROMACS Integration and QM/ML/MM Synergies. Dmitry Morozov\, University of Jyväskylä\n13:25–13:50 Machine Learning in soft matter systems. Mikko Karttunen\, University of Eastern Finland\n13:50–14:15 Machine Learning in drug discovery. Serhii Vakal\, Orion Pharma\n14:15–14:35 small break/coffee break\n\nChairperson 14:35–15:25 N.N. \n\n14:35–15:00 Inferring the atomic-scale structure of complex materials from experimental observables with MAD. Tigany Zarrouk\, Aalto University\n15:00–15:25 ML search for new catalyst structures. Timo Weckman\, University of Jyväskylä\n15:25–15:35 Closing. Miguel Caro\, Aalto University
URL:https://ocamm.fi/event/chembio-finland-session-machine-learning-in-chemistry/
LOCATION:Messukeskus\, Messuaukio 1\, Helsinki\, 00520\, Finland
CATEGORIES:Conference
ORGANIZER;CN="Kari Laasonen":MAILTO:kari.laasonen@aalto.fi
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