{"id":12028,"date":"2023-07-06T15:00:30","date_gmt":"2023-07-06T13:00:30","guid":{"rendered":"https:\/\/new.sano.science\/?post_type=people&p=12028"},"modified":"2026-03-02T10:18:05","modified_gmt":"2026-03-02T09:18:05","slug":"magdalena-otta","status":"publish","type":"people","link":"https:\/\/sano.science\/people\/magdalena-otta\/","title":{"rendered":"Magdalena Otta"},"excerpt":{"rendered":"

Postdoctoral Researcher in Extreme-scale Data and Computing<\/p>\n","protected":false},"featured_media":21604,"template":"","people_teams":[19,34],"class_list":["post-12028","people","type-people","status-publish","has-post-thumbnail","hentry","people_teams-research","people_teams-extreme-scale-data-and-computing"],"yoast_head":"\nMagdalena Otta - 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\/magdalena-otta\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Magdalena Otta\" \/>\n<meta property=\"og:description\" content=\"Postdoctoral Researcher in Extreme-scale Data and Computing\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/people\/magdalena-otta\/\" \/>\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=\"2026-03-02T09:18:05+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/08\/Sano_w.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"1000\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\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\\\/magdalena-otta\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/people\\\/magdalena-otta\\\/\",\"name\":\"Magdalena Otta - 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The subject of her thesis was modelling a response of a single cell to the use of fractionated radiotherapy in order to induce the abscopal effect in cancer treatment. She joined Sano’s Extreme-Scale Data and Computing Team as a PhD student and is currently working on modelling venous flow in patients presenting with deep vein thrombosis of the lower limb.<\/p>\n","email":"","social_media":false,"tabs":false,"quote":"","position_with_team":{"text_before_link":"Postdoctoral Researcher","link_text":"Extreme-scale Data and Computing","text_after_link":"","link":"https:\/\/sano.science\/research-teams\/extreme-scale-data-and-computing\/"},"publications":[{"ID":14937,"post_author":"5","post_date":"2024-01-16 13:33:06","post_date_gmt":"2024-01-16 12:33:06","post_content":"<!-- wp:heading {\"epAnimationGeneratedClass\":\"edplus_anim-G1GWMI\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<h2 class=\"wp-block-heading eplus-wrapper\">Piotr Kica, Magdalena Otta, Krzysztof Czechowicz, Karol Zaj\u0105c, Piotr Nowakowski, Andrew Narracott, Ian Halliday, Maciej Malawski<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-vSoDxU\",\"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-sGaBCh\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">Digital twins are virtual representations of physical objects or systems used for the purpose of analysis, most often via computer simulations, in many engineering and scientific disciplines. Recently, this approach has been introduced to computational medicine, within the concept of Digital Twin in Healthcare (DTH). Such research requires verification and validation of its models, as well as the corresponding sensitivity analysis and uncertainty quantification (VVUQ). From the computing perspective, VVUQ is a computationally intensive process, as it requires numerous runs with variations of input parameters. Researchers often use high-performance computing (HPC) solutions to run VVUQ studies where the number of parameter combinations can easily reach tens of thousands. However, there is a viable alternative to HPC for a substantial subset of computational models - serverless computing. In this paper we hypothesize that using the serverless computing model can be a practical and efficient approach to selected cases of running VVUQ calculations. We show this on the example of the EasyVVUQ library, which we extend by providing support for many serverless services. The resulting library - CloudVVUQ - is evaluated using two real-world applications from the computational medicine domain adapted for serverless execution. Our experiments demonstrate the scalability of the proposed approach.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"50px\",\"epAnimationGeneratedClass\":\"edplus_anim-vSoDxU\",\"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_65a6776af10b8\",\"name\":\"acf\/button\",\"data\":{\"title\":\"READ HERE\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"https:\/\/www.computer.org\/csdl\/proceedings-article\/ccgrid\/2023\/011900a627\/1OFrjleAbTy\",\"_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":"Serverless Approach to Sensitivity Analysis of Computational Models","post_excerpt":"In: CCGrid2023, 2023.","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"serverless-approach-to-sensitivity-analysis-of-computational-models","to_ping":"","pinged":"","post_modified":"2024-01-16 13:33:06","post_modified_gmt":"2024-01-16 12:33:06","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&p=14937","menu_order":27,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"}]},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12028","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":5,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12028\/revisions"}],"predecessor-version":[{"id":29455,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12028\/revisions\/29455"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media\/21604"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=12028"}],"wp:term":[{"taxonomy":"people_teams","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people_teams?post=12028"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}