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SUMMARY:2nd SMASHING Workshop
DTSTART:20261019T070000Z
DTEND:20261023T120000Z
DTSTAMP:20260710T232100Z
UID:indico-event-55@indico.ung.si
DESCRIPTION:This workshop is the second network meeting of the SMASH proje
 ct (here you can find the first edition https://indico.ung.si/event/35). S
 MASH is a multidisciplinary program centered on developing cutting-edge Ma
 chine Learning (ML) and Artificial Intelligence (AI) applications for scie
 nce and humanities. These include climate science\, precision medicine\, f
 undamental physics and linguistics.  It is co-funded by the European Unio
 n via the Marie Skłodowska-Curie COFUND action and connects scholars from
  five top-level institutions in Slovenia with 52 associated partners\, Slo
 venian businesses and academic institutions globally.\nThe Second SMASHING
  workshop will gather scientists working in the SMASH research areas with 
 the aim to create a multi-disciplinary environment that will foster knowle
 dge exchange between different fields and between academia and industry\, 
 thereby building the SMASH community. The workshop will be structured arou
 nd discussions of different classes of ML/AI techniques\, followed up with
  examples on the successful application in SMASH research areas. More spec
 ifically the workshop will focus on:\n\nAgentic AI approaches to science\n
 Foundation models\nGenerative models and computer vision\nStatistical appr
 oaches (simulation based inference\, etc) \nGraphs/transformers and time 
 series\n\nIn addition to invited talks the workshop will have discussion s
 essions and there will be plenty of time to exchange ideas and build the c
 ommunity. \nSpeakers include:\n\nAida Alvera-Azcárate (University of Li
 ège\, Belgium)\, Data analysis methods for oceanographic applications\nSa
 tardu Bag (Max Planck Institute for Astrophysics\, Garching)\, Discovering
  Strongly Lensed Transients in the Era of LSST: Machine Learning for a Nee
 dle-in-a-Haystack Problem\nMaria Benito (Instituto de Astrofísica de Cana
 rias\, Spain)\, Representation learning for dark matter searches in the Mi
 lky Way stellar halo\n\nMatteo Cagiada (University of Copenhagen and Oxfor
 d University)\, Towards improved prediction of protein dynamics\n\nImad El
  Haddad (Paul Scherrer\, Switzerland)\, AI-Enabled Atmospheric Chemistry: 
 Harmonized Measurements\, Exposure Mapping\, and Causal Inference \nFabio 
 Iocco (University of Naples\, Italy)\, Determining dark matter distributio
 n in Galaxies with machine learning \nŽeljko Ivezić (University of Washi
 ngton\, USA)\, Rubin Obs. science in the AI era\, TBC\nAdriana Milic (CERN
 \, Switzerland)\, The Art of Finding Needles in Haystacks: Event Selection
  at ATLAS\nSoebur Razzaque (University of Johannesburg\, South Africa)\, A
 pplication of Machine Learning in Astrophysical Transient Data\nJohannes S
 chneider (University of Liechtenstein)\, How Using AI agents alters our th
 inking and speaking\nGad Shaulsky (Baylor College of Medicine\, Houston\, 
 USA)\, Agentic approach to studies of the Dictyostelium discoideum\nDimita
 r Trajanov (University of Skoplje and Boston University)\, LLM based agent
 ic systems and knowledge graphs\nSaman Vinke\, MD (Radboud University Medi
 cal Center)\, AI application to the field of Deep brain stimulation\nLili 
 Yang (Sun Yat-sen University\, China)\, The application of ML in astrophys
 ics and astroparticle experiments\nJure Zupan (University Cincinnati\, USA
 )\, Simulating Particle Physics Hadronization with Machine Learning\n\n \
 n\n\nhttps://indico.ung.si/event/55/
IMAGE;VALUE=URI:https://indico.ung.si/event/55/logo-3156997623.png
LOCATION:Lanthieri Mansion\, Vipava
URL:https://indico.ung.si/event/55/
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