{"id":9,"date":"2016-10-06T09:08:59","date_gmt":"2016-10-06T09:08:59","guid":{"rendered":"http:\/\/localhost:8888\/wordpress\/?page_id=2"},"modified":"2026-04-05T16:59:39","modified_gmt":"2026-04-05T16:59:39","slug":"sample-page-2","status":"publish","type":"page","link":"http:\/\/rtds.aueb.gr\/","title":{"rendered":"About"},"content":{"rendered":"<p>The Real Time Distributed Systems Group is lead by Prof. <a href=\"http:\/\/www.cs.aueb.gr\/~vana\">Vana Kalogeraki<\/a>.<img loading=\"lazy\" class=\"wp-image-316 alignright\" src=\"http:\/\/rtds.aueb.gr\/wp-content\/uploads\/2016\/10\/bestcanvas-2-300x249.png\" alt=\"bestcanvas\" width=\"278\" height=\"231\" srcset=\"http:\/\/rtds.aueb.gr\/wp-content\/uploads\/2016\/10\/bestcanvas-2-300x249.png 300w, http:\/\/rtds.aueb.gr\/wp-content\/uploads\/2016\/10\/bestcanvas-2.png 684w\" sizes=\"(max-width: 278px) 100vw, 278px\" \/><\/p>\n<p style=\"text-align: justify;\">We explore the world around us by turning sensed data into information. For years, research in fields such as distributed systems, participatory sensing systems, crowdsourcing, social networks and machine learning (ML), has steadily improved techniques for revealing underlying and hidden information from crowdsensed data. Together these trends have the potential for ushering in a new era in understanding and improving the world we live in.<\/p>\n<hr \/>\n<p><div class=\"gdc_row\"><div class=\"gdc_column gdc_cquarter\"><div class=\"gdc_inner\"><\/p>\n<h3 style=\"text-align: center;\">Research Highlights<\/h3>\n<p><\/div><\/div><div class=\"gdc_column gdc_cthree-quarters\"><div class=\"gdc_inner\"><\/p>\n<h3 style=\"text-align: center; font-weight: bold;\">Featured Project<\/h3>\n<p><\/div><\/div><\/div><div class=\"gdc_row\"><div class=\"gdc_column gdc_cquarter\"><div class=\"gdc_inner\"><br \/>\n<div class=\"pt-cv-wrapper\"><div class=\"pt-cv-view pt-cv-scrollable pt-cv-colsys\" id=\"pt-cv-view-fa321d0s71\"><div data-id=\"pt-cv-page-1\" class=\"pt-cv-page\" data-cvc=\"1\"><div id=\"d9e9c82rax\" class=\"pt-cv-carousel pt-cv-slide\" data-ride=\"cvcarousel\" data-interval=false><ol class=\"pt-cv-carousel-indicators\"><li data-target=\"#d9e9c82rax\" data-cvslide-to=\"0\" class=\"active\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"1\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"2\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"3\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"4\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"5\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"6\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"7\" class=\"\"><\/li>\n<li data-target=\"#d9e9c82rax\" data-cvslide-to=\"8\" class=\"\"><\/li><\/ol>\n<div class=\"carousel-inner\"><div class=\"item active\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/04\/05\/ignite-scheduling-pipeline-parallel-dnn-training-jobs-on-heterogeneous-infrastructures-debs-2025\/\" class=\"_self\" target=\"_self\" >IgNITE: Scheduling Pipeline-Parallel DNN Training Jobs on Heterogeneous Infrastructures, DEBS, 2025<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/04\/05\/trustworthy-scheduling-for-big-data-applications-ieee-big-data-2025\/\" class=\"_self\" target=\"_self\" >Trustworthy Scheduling for Big Data Applications, IEEE Big Data, 2025<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/04\/05\/vertical-scaling-can-save-time-optimizing-container-scheduling-to-handle-sudden-bursts-debs-2025\/\" class=\"_self\" target=\"_self\" >Vertical Scaling Can Save Time: Optimizing Container Scheduling to Handle Sudden Bursts, DEBS, 2025<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/04\/05\/exploring-gpu-based-workload-scheduling-techniques-for-edge-computing-ic2e-2025\/\" class=\"_self\" target=\"_self\" >Exploring GPU-Based Workload Scheduling Techniques for Edge Computing, IC2E, 2025<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/04\/05\/strata-random-forests-going-serverless-middleware-2024\/\" class=\"_self\" target=\"_self\" >STRATA: Random Forests going Serverless, Middleware, 2024<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/04\/07\/dynamic-storage-selection-for-mitigating-tail-latency-in-serverless-pipelinesacsos2024\/\" class=\"_self\" target=\"_self\" >Dynamic storage selection for mitigating tail latency in serverless pipelines, ACSOS, 2024<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/06\/06\/fault-tolerance-enhancements-for-redundancy-conversion-with-diagonally-interleaved-coding\/\" class=\"_self\" target=\"_self\" >Fault Tolerance Enhancements for Redundancy Conversion with Diagonally Interleaved Coding, EDCC 2026<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/06\/06\/autofairml-an-automated-middleware-for-fairness-auditing-in-real-world-ai-pipelines-icdcs-2025\/\" class=\"_self\" target=\"_self\" >AutoFairML: An Automated Middleware for Fairness Auditing in Real-world AI Pipelines, ICDCS 2025<\/a><\/h4><\/div><\/div><\/div><\/div>\n<div class=\"item\"><div class=\"row\"><div class=\"col-md-12 pt-cv-content-item pt-cv-1-col\" ><div class=\"pt-cv-carousel-caption pt-cv-cap-wo-img\"><h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/2026\/06\/06\/ragnn-a-resource-aware-system-for-graph-neural-network-training-at-scale\/\" class=\"_self\" target=\"_self\" >RAGNN: A Resource-Aware System for Graph Neural Network Training at Scale<\/a><\/h4><\/div><\/div><\/div><\/div><\/div>\n<a class=\"left carousel-control\" data-target=\"#d9e9c82rax\" data-cvslide=\"prev\">\r\n\t\t\t\t\t\t<span class=\"glyphicon glyphicon-chevron-left\"><\/span>\r\n\t\t\t\t\t<\/a>\r\n\t\t\t\t\t<a class=\"right carousel-control\" data-target=\"#d9e9c82rax\" data-cvslide=\"next\">\r\n\t\t\t\t\t\t<span class=\"glyphicon glyphicon-chevron-right\"><\/span>\r\n\t\t\t\t\t<\/a><\/div><\/div><\/div><\/div><br \/>\n<\/div><\/div><div class=\"gdc_column gdc_cthree-quarters\"><div class=\"gdc_inner\"><br \/>\n<div class=\"pt-cv-wrapper\"><div class=\"pt-cv-view pt-cv-grid pt-cv-colsys pt-cv-nolf\" id=\"pt-cv-view-3f1b94a8lh\"><div data-id=\"pt-cv-page-1\" class=\"pt-cv-page\" data-cvc=\"1\"><div class=\"col-md-12 col-sm-12 col-xs-12 pt-cv-content-item pt-cv-2-col\" ><div class='pt-cv-ifield'><a href=\"http:\/\/rtds.aueb.gr\/index.php\/codiet-combatting-diet-related-non-communicable-disease-through-enhanced-surveillance\/\" class=\"_self pt-cv-href-thumbnail pt-cv-thumb-left\" target=\"_self\" ><\/a>\n<h4 class=\"pt-cv-title\"><a href=\"http:\/\/rtds.aueb.gr\/index.php\/codiet-combatting-diet-related-non-communicable-disease-through-enhanced-surveillance\/\" class=\"_self\" target=\"_self\" >CoDiet: Combatting Diet Related Non-Communicable Disease Through Enhanced Surveillance<\/a><\/h4>\n<div class=\"pt-cv-content\">\n<div class=\"wp-block-image\"><figure class=\"alignright size-large is-resized\"><img loading=\"lazy\" src=\"http:\/\/rtds.aueb.gr\/wp-content\/uploads\/2026\/04\/horizon_europe-1.png\" alt=\"\" class=\"wp-image-1124\" width=\"115\" height=\"117\"\/><\/figure><\/div>\n\n\n\n<p>Unhealthy diets are associated with metabolic changes and increased risk of non-communicable diseases (NCDs). However, little is known about the dietary mechanisms that actually drive NCDs, and the tools used to collect dietary information are still inaccurate. There is also a lack of data among vulnerable groups, where NCDs are often over-represented. The EU-funded CoDiet project will address the knowledge gaps and develop a tool that will assess diet-induced NCD risk. Specifically, <\/p>\n\n\n\n<ul><li>it will develop an enhanced method of dietary assessment using AI technologies. <\/li><li>It will also develop a diet\u2013NCD monitoring tool that will enable change in NCDs in response to diet to be monitored at the population level. <\/li><li>The overall goal is to promote the uptake of an NCD-protective diet at a population level.<\/li><\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p>For more information, visit the project page <a href=\"https:\/\/www.codiet.eu\/\">here<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><br \/>\n<\/div><\/div><\/div><\/p>\n<hr \/>\n<p><!-- <img loading=\"lazy\" class=\"wp-image-159 aligncenter\" src=\"http:\/\/rtds.aueb.gr\/wp-content\/uploads\/2016\/10\/bestcanvas-2.png\" alt=\"bestcanvas\" width=\"320\" height=\"240\" \/> --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Real Time Distributed Systems Group is lead by Prof. Vana Kalogeraki. We explore the world around us by turning sensed data into information. For years, research in fields such as distributed systems, participatory sensing systems, crowdsourcing, social networks and machine learning (ML), has steadily improved techniques for revealing underlying and hidden information from crowdsensed &#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"homepage.php","meta":[],"_links":{"self":[{"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/pages\/9"}],"collection":[{"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/comments?post=9"}],"version-history":[{"count":29,"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/pages\/9\/revisions"}],"predecessor-version":[{"id":1129,"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/pages\/9\/revisions\/1129"}],"wp:attachment":[{"href":"http:\/\/rtds.aueb.gr\/index.php\/wp-json\/wp\/v2\/media?parent=9"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}