{"id":12030,"date":"2023-07-06T15:02:57","date_gmt":"2023-07-06T13:02:57","guid":{"rendered":"https:\/\/new.sano.science\/?post_type=people&p=12030"},"modified":"2026-03-31T23:05:41","modified_gmt":"2026-03-31T21:05:41","slug":"luca-gherardini","status":"publish","type":"people","link":"https:\/\/sano.science\/people\/luca-gherardini\/","title":{"rendered":"Luca Gherardini"},"excerpt":{"rendered":"

Postdoctoral Researcher in Computational Intelligence<\/p>\n","protected":false},"featured_media":18404,"template":"","people_teams":[19,32],"class_list":["post-12030","people","type-people","status-publish","has-post-thumbnail","hentry","people_teams-research","people_teams-computational-intelligence"],"yoast_head":"\nLuca Gherardini - Centre for Computational Personalized Medicine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sano.science\/people\/luca-gherardini\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Luca Gherardini\" \/>\n<meta property=\"og:description\" content=\"Postdoctoral Researcher in Computational Intelligence\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/people\/luca-gherardini\/\" \/>\n<meta property=\"og:site_name\" content=\"Centre for Computational Personalized Medicine\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/sano.science\/\" \/>\n<meta property=\"article:modified_time\" content=\"2026-03-31T21:05:41+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/07\/Luca-Gherardini_Sano-1024x1024.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@sanoscience\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/sano.science\\\/people\\\/luca-gherardini\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/people\\\/luca-gherardini\\\/\",\"name\":\"Luca Gherardini - 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His research spans several fields, such as Machine Learning, multi-agent systems, neuroscience, and autonomous driving.<\/p>\n","email":"","social_media":[{"icon":{"ID":11994,"id":11994,"title":"linkedin","filename":"linkedin.svg","filesize":914,"url":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","link":"https:\/\/sano.science\/people\/maciej-malawski\/linkedin-2\/","alt":"","author":"5","description":"","caption":"","name":"linkedin-2","status":"inherit","uploaded_to":531,"date":"2023-07-06 11:24:13","modified":"2023-07-06 11:24:13","menu_order":0,"mime_type":"image\/svg+xml","type":"image","subtype":"svg+xml","icon":"https:\/\/sano.science\/wp-includes\/images\/media\/default.png","width":1,"height":1,"sizes":{"thumbnail":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","thumbnail-width":150,"thumbnail-height":150,"medium":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","medium-width":300,"medium-height":300,"medium_large":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","medium_large-width":768,"medium_large-height":1,"large":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","large-width":1024,"large-height":1024,"1536x1536":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","1536x1536-width":1,"1536x1536-height":1,"2048x2048":"https:\/\/sano.science\/wp-content\/uploads\/2023\/05\/linkedin.svg","2048x2048-width":1,"2048x2048-height":1}},"link":"https:\/\/www.linkedin.com\/in\/luca-gherardini-3b32b11a7\/","name":"LinkedIn"}],"tabs":false,"quote":"","position_with_team":{"text_before_link":"Postdoctoral Researcher in","link_text":"Computational Intelligence","text_after_link":"","link":"https:\/\/sano.science\/research-teams\/computational-intelligence\/"},"publications":[{"ID":14930,"post_author":"5","post_date":"2024-01-16 13:04:33","post_date_gmt":"2024-01-16 12:04:33","post_content":"<!-- wp:heading {\"epAnimationGeneratedClass\":\"edplus_anim-jlzOq6\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<h2 class=\"wp-block-heading eplus-wrapper\">L. Gherardini, G. Cabri, M. Montangero<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-pchBAX\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-Z3FnHt\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">The coordination of autonomous vehicles is an open field that is addressed by different researches comprising many different techniques. In this paper we focus on decentralized approaches able to provide adaptability to different infrastructural and traffic conditions. We formalize an Emergent Behavior Approach that, as per our knowledge, has never been performed for this purpose, and a Decentralized Auction approach. We compare them against existing centralized negotiation approaches based on auctions and we determine under which conditions each approach is preferable to the others.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"49px\",\"epAnimationGeneratedClass\":\"edplus_anim-pchBAX\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:49px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:acf\/button {\"id\":\"block_65a6708d4ae5d\",\"name\":\"acf\/button\",\"data\":{\"title\":\"READ HERE\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.398\",\"_url\":\"field_61d4039bc2f0b\",\"button_style\":\"primary\",\"_button_style\":\"field_63872d045d0f0\",\"target\":\"_blank\",\"_target\":\"field_63872c705d0ef\",\"button_extra_classes\":\"\",\"_button_extra_classes\":\"field_642beab6a97de\"},\"align\":\"\",\"mode\":\"edit\"} \/-->","post_title":"Decentralized approaches for Autonomous Vehicles Coordination","post_excerpt":"In: Internet Technology Letters, 2022.","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"decentralized-approaches-for-autonomous-vehicles-coordination","to_ping":"","pinged":"","post_modified":"2024-01-16 13:04:33","post_modified_gmt":"2024-01-16 12:04:33","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&p=14930","menu_order":44,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":15074,"post_author":"5","post_date":"2024-01-18 20:40:02","post_date_gmt":"2024-01-18 19:40:02","post_content":"<!-- wp:heading {\"epAnimationGeneratedClass\":\"edplus_anim-i03vtW\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<h2 class=\"wp-block-heading eplus-wrapper\">Luca Gherardini, Aleksandra Pestka, Lorenzo Pini, Alessandro Crimi<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-NSRzPr\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-a2eeGr\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">The pervasive impact of Alzheimer\u2019s disease on aging society represents one of the main challenges at this time. Current investigations highlight 2 specific misfolded proteins in its development: Amyloid-B\u00a0and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on 2 machine learning approaches which we compare with known simulation models. The first approach applies an autoregressive model constrained by structural connectivity, while the second is based on graph convolutional networks. The aim is to predict concentrations of Amyloid-B\u00a02 yr after a provided baseline. We also evaluate its real-world effectiveness and suitability by providing a web service for physicians and researchers. In experiments, the autoregressive model generally outperformed state-of-the-art models resulting in lower prediction errors. While it is important to note that a comprehensive prognostic plan cannot solely rely on amyloid beta concentrations, their prediction, achieved by the discussed approaches, can be valuable for planning therapies and other cures, especially when dealing with asymptomatic patients for whom novel therapies could prove effective.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-NSRzPr\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:acf\/button {\"id\":\"block_65a97e4d6a5ef\",\"name\":\"acf\/button\",\"data\":{\"title\":\"\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"\",\"_url\":\"field_61d4039bc2f0b\",\"button_style\":\"primary\",\"_button_style\":\"field_63872d045d0f0\",\"target\":\"_self\",\"_target\":\"field_63872c705d0ef\",\"button_extra_classes\":\"\",\"_button_extra_classes\":\"field_642beab6a97de\"},\"align\":\"\",\"mode\":\"edit\"} \/-->","post_title":"Prediction of misfolded proteins spreading in Alzheimer\u2019s disease using machine learning and spreading models","post_excerpt":"In: CEREBRAL CORTEX, 2023.","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"prediction-of-misfolded-proteins-spreading-in-alzheimers-disease-using-machine-learning-and-spreading-models","to_ping":"","pinged":"","post_modified":"2024-01-18 20:40:02","post_modified_gmt":"2024-01-18 19:40:02","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&p=15074","menu_order":12,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":12905,"post_author":"5","post_date":"2023-07-25 22:09:27","post_date_gmt":"2023-07-25 20:09:27","post_content":"<!-- wp:heading {\"epAnimationGeneratedClass\":\"edplus_anim-IxLYNe\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<h2 class=\"wp-block-heading eplus-wrapper\"><strong>Alfredo Ibias, Varun Ravi Varma, Karol Capa\u0142a, Luca Gherardini, Jose Sousa<\/strong> <\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-G8C2CJ\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-D5g7jz\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">In personalized health, small datasets with missing data are quite common. Current Machine Learning methods are unable to process such datasets in a meaningful way due to the huge data volume requirement. To address this problem, we propose a new Small and iNcomplete Dataset Analyser (SaNDA) to process such datasets in a meaningful way. Due to the characteristics of these datasets and the criticality of the domain, an explainable method is mandatory to facilitate decision-making interpretation. Thus, SaNDA prioritises explainability over efficiency by design. We evaluated our proposal against Random Forest as a baseline for explainable methods, and against gcForest as state-of-the-art for small datasets. We observed that our proposal outperforms Random Forest when there is more missing data and\/or a lower number of entries in the dataset, obtaining less favourable results over larger, well-curated datasets. It is also preferable than gcForest due to its explainability and privacy protection capabilities. Given the difficulties in obtaining complete, reliable data in the healthcare field, we consider that our proposal could be useful for practitioners.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-Zsu9XH\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:acf\/button {\"id\":\"block_64ca5efe15ebe\",\"name\":\"acf\/button\",\"data\":{\"title\":\"READ HERE\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025523006631\",\"_url\":\"field_61d4039bc2f0b\",\"button_style\":\"primary\",\"_button_style\":\"field_63872d045d0f0\",\"target\":\"_blank\",\"_target\":\"field_63872c705d0ef\",\"button_extra_classes\":\"\",\"_button_extra_classes\":\"field_642beab6a97de\"},\"align\":\"\",\"mode\":\"edit\"} \/-->","post_title":"SaNDA: A small and iNcomplete dataset analyser","post_excerpt":"In: Information Sciences, 2023","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"sanda-a-small-and-incomplete-dataset-analyser","to_ping":"","pinged":"","post_modified":"2024-01-05 13:39:25","post_modified_gmt":"2024-01-05 12:39:25","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&p=12905","menu_order":6,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"}]},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12030","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people"}],"about":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/types\/people"}],"version-history":[{"count":7,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12030\/revisions"}],"predecessor-version":[{"id":30223,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12030\/revisions\/30223"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media\/18404"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=12030"}],"wp:term":[{"taxonomy":"people_teams","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people_teams?post=12030"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}