{"id":1114,"date":"2021-09-24T09:56:23","date_gmt":"2021-09-24T09:56:23","guid":{"rendered":"https:\/\/alexiabriassouli.com\/?page_id=1114"},"modified":"2026-06-01T11:50:32","modified_gmt":"2026-06-01T11:50:32","slug":"collaborations-student-theses","status":"publish","type":"page","link":"https:\/\/alexiabriassouli.com\/?page_id=1114","title":{"rendered":"Collaborations, Student theses"},"content":{"rendered":"<div\n      class=\"kv-control-placeholder kv-_page\"\n      data-kv-control=\"1\">\n    <\/div> <section class=\"background-id_0adjacent section-1633004490457 goveda96\" style=\" position:relative;\">\n  <a name=\"section1633004490457\"><\/a>\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"background\">\n  <\/div> <div class='kv-background  ' style=\" background-color: rgb(249,249,249);\">\n        \n        <div class='kv-background-inner '  style=\"\n          \n          \n          \n          background-color: rgb(249,249,249);\n          \"><\/div>\n          \n<\/div>\n\n  <div class=\"position-relative kv-content\">\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"content\">\n  <\/div> <div class=\"kv-ee-section kv-ee-section--md \"><div class=\"kv-ee-container kv-ee-align-left\"><div class=\"kv-ee-row\"><div class=\"kv-ee-col-lg-12 kv-ee-mx-auto\">  <div class=\"kv-ee-text\">  <h1 class=\"kv-ee-cover-title kv-ee-section-title kv-ee-hide-desktop kv-ee-page-title--sm\" data-type=\"text\" tabindex=\"0\">Collaborations\/student theses<span data-prop=\"title\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/h1> <p class=\"kv-ee-cover-description kv-ee-section-description kv-ee-body--md\" data-type=\"text\" tabindex=\"0\">This page contains a partial list of collaborations with companies, organizations and student theses\/internships organized by topic.<span data-prop=\"description\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/p> <\/div>   <\/div><\/div><div class=\"kv-ee-row\"><div class=\"kv-ee-col-12\"><div class=\"kv-ee-image\">  <\/div><\/div><\/div><\/div><\/div>\n  <\/div>\n<\/section>\n<style scoped>.goveda96 .kv-ee-section{display:flex;align-items:center}.goveda96 .kv-ee-text{margin-bottom:2rem}.goveda96 .kv-ee-cover-title{margin-bottom:1rem}.goveda96 .kv-ee-cover-description{color:rgba(var(--kv-ee-text1-rgb),.75);max-width:32rem}.goveda96 .kv-ee-buttons{display:flex;flex-direction:column;align-items:center;margin-bottom:2.75rem}.goveda96 .kv-ee-button{display:inline-flex;position:relative}.goveda96 .kv-ee-button i{order:2}.goveda96 .kv-ee-button div{order:1}.goveda96 .kv-ee-button:not(:first-child):before{content:'';display:block;height:1.25rem;width:1px;background-color:rgba(var(--kv-ee-text1-rgb),.12);position:absolute;top:0;left:50%;transform:translate(-50%,calc(-100% - .375rem))}.goveda96 .kv-ee-cover-image{width:100%;padding-bottom:45%;background-size:cover;background-position:center;background-repeat:no-repeat}.goveda96 .kv-ee-align-left{text-align:left}.goveda96 .kv-ee-align-left .kv-ee-buttons{align-items:flex-start}.goveda96 .kv-ee-align-center{text-align:center}.goveda96 .kv-ee-align-center .kv-ee-cover-description{margin-left:auto;margin-right:auto}.goveda96 .kv-ee-align-right{text-align:right}.goveda96 .kv-ee-align-right .kv-ee-cover-description{margin-left:auto;margin-right:0}.goveda96 .kv-ee-align-right .kv-ee-buttons{align-items:flex-end}<\/style><div\n      class=\"kv-control-placeholder kv-_page\"\n      data-kv-control=\"2\">\n    <\/div> <section class=\"background-id_0 section-1633004412064 goveda96\" style=\" position:relative;\">\n  <a name=\"section1633004412064\"><\/a>\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"background\">\n  <\/div> <div class='kv-background  ' style=\" background-color: rgb(255,255,255);\">\n        \n        <div class='kv-background-inner '  style=\"\n          \n          \n          \n          background-color: rgb(255,255,255);\n          \"><\/div>\n          \n<\/div>\n\n  <div class=\"position-relative kv-content\">\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"content\">\n  <\/div> <div class=\"kv-ee-section kv-ee-section--md \"><div class=\"kv-ee-container kv-ee-align-left\"><div class=\"kv-ee-row\"><div class=\"kv-ee-col-lg-12 kv-ee-mx-auto\">  <div class=\"kv-ee-text\">  <h1 class=\"kv-ee-cover-title kv-ee-section-title kv-ee-hide-desktop kv-ee-page-title--sm\" data-type=\"text\" tabindex=\"0\">Medical imaging<span data-prop=\"title\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/h1> <p class=\"kv-ee-cover-description kv-ee-section-description kv-ee-body--md\" data-type=\"text\" tabindex=\"0\">1)\tRobustness And Explainablitiy Of OOD Detection In Medical Images (J. Delember)\n<br><br>\n2)\tSample-level Out-Of-Distribution Detection in the context of Medical Image Segmentation with \u03b2-VAE and Likelihood Regret (E. Simon)\n<br><br>\n3)\tOOD Detection on Medical Images and Explainable OOD (I. Berk)\n<br><br>\n4)\tDetecting Rare Diseases: Autoencoders for Detecting Anomalies in Medical Imaging (S. Reve)\n<br><br>\n5)\tDeep learning AI model evaluation for anomaly detection and domain shift according toOut-Of-Distribution detection (G. Cho)\n<br><br>\n6)\tMicroNeRF: Scanning Electron Microscopy 3D Scene of Cellular Scaffolding Matrices (M. Panourgias)\n<br><br>\n7)\tDeep Learning Segmentation Of Heart Substructures (L. N\u00fcrnberg, Maastro Clinic)\n<br><br>\n8)\tVolume effect in hand-crafted Radiomics feature (A. Romita, Maastro Clinic)\n<br><br>\n9)\tPredicting Tumor Hypoxia Map from FDG-PET\/CT Images using GANs (C. Rao, Maastro Clinic)\n<br><br>\n10)\tA Comparative Study of Visual Transformers for Thoracic Disease Classification (D. Demirkiran)\n<br><br>\n11)\t3D Unpaired GANs in Solving the Domain Shift Problem Encountered Across Medical Imaging Scenarios (H. Ibrahim, Maastro Clinic)\n<br><br>\n12)\tDeep Learning approach on Survival Outcome Prognostication for Oesophageal Cancer (V. Prudente, Maastro Clinic)\n<br><br>\n13)\tAutomated Diagnostic System of Skin Cancer using Deep Convolutional Neural Networks on Dermoscopic Images (W. Aljbawi)\n<br><br>\n14)\tDeep Learning Techniques for Detection and Diagnosis of Brain Metastases using Medical Image Analysis (M. Pliusnova)\n<br><br>\n15)\tVision Transformer for Brain Tumor Classification (E. Simon)\n<br><br>\n16)\tDeep learning based auto-segmentation of Head-and-Neck cancer using bi-modal medical image data (C. Rao, Maastro Clinic)\n<br><br>\n17)\tDeep Learning for domain adaptation and synthetic imaging of medical images (J. Posch, Maastro Clinic)\n\n18)\tAutomatic segmentation of organs at risk in head and neck region using 3D Unets (S. Datta, Maastro Clinic)&nbsp;&nbsp;<span data-prop=\"description\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/p> <\/div>   <\/div><\/div><div class=\"kv-ee-row\"><div class=\"kv-ee-col-12\"><div class=\"kv-ee-image\">  <\/div><\/div><\/div><\/div><\/div>\n  <\/div>\n<\/section>\n<style scoped>.goveda96 .kv-ee-section{display:flex;align-items:center}.goveda96 .kv-ee-text{margin-bottom:2rem}.goveda96 .kv-ee-cover-title{margin-bottom:1rem}.goveda96 .kv-ee-cover-description{color:rgba(var(--kv-ee-text1-rgb),.75);max-width:32rem}.goveda96 .kv-ee-buttons{display:flex;flex-direction:column;align-items:center;margin-bottom:2.75rem}.goveda96 .kv-ee-button{display:inline-flex;position:relative}.goveda96 .kv-ee-button i{order:2}.goveda96 .kv-ee-button div{order:1}.goveda96 .kv-ee-button:not(:first-child):before{content:'';display:block;height:1.25rem;width:1px;background-color:rgba(var(--kv-ee-text1-rgb),.12);position:absolute;top:0;left:50%;transform:translate(-50%,calc(-100% - .375rem))}.goveda96 .kv-ee-cover-image{width:100%;padding-bottom:45%;background-size:cover;background-position:center;background-repeat:no-repeat}.goveda96 .kv-ee-align-left{text-align:left}.goveda96 .kv-ee-align-left .kv-ee-buttons{align-items:flex-start}.goveda96 .kv-ee-align-center{text-align:center}.goveda96 .kv-ee-align-center .kv-ee-cover-description{margin-left:auto;margin-right:auto}.goveda96 .kv-ee-align-right{text-align:right}.goveda96 .kv-ee-align-right .kv-ee-cover-description{margin-left:auto;margin-right:0}.goveda96 .kv-ee-align-right .kv-ee-buttons{align-items:flex-end}<\/style><div\n      class=\"kv-control-placeholder kv-_page\"\n      data-kv-control=\"3\">\n    <\/div> <section class=\"background-id_0adjacent section-1633004619866 goveda96\" style=\" position:relative;\">\n  <a name=\"section1633004619866\"><\/a>\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"background\">\n  <\/div> <div class='kv-background  ' style=\" background-color: rgb(249,249,249);\">\n        \n        <div class='kv-background-inner '  style=\"\n          \n          \n          \n          background-color: rgb(249,249,249);\n          \"><\/div>\n          \n<\/div>\n\n  <div class=\"position-relative kv-content\">\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"content\">\n  <\/div> <div class=\"kv-ee-section kv-ee-section--md \"><div class=\"kv-ee-container kv-ee-align-left\"><div class=\"kv-ee-row\"><div class=\"kv-ee-col-lg-12 kv-ee-mx-auto\">  <div class=\"kv-ee-text\">  <h1 class=\"kv-ee-cover-title kv-ee-section-title kv-ee-hide-desktop kv-ee-page-title--sm\" data-type=\"text\" tabindex=\"0\">Precision farming <span data-prop=\"title\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/h1> <p class=\"kv-ee-cover-description kv-ee-section-description kv-ee-body--md\" data-type=\"text\" tabindex=\"0\">1) Detection And Classification Of Insects Catched By Yellow Sticky Traps (M. Deserno, <a href=\"https:\/\/www.augmenta.ag\/\" target=\"_blank\" rel=\"noopener noreferrer\">Augmenta<\/a>) <br><br>2) Real-time optical flow estimation with cost learning (F. Debrauwer, <a href=\"https:\/\/www.augmenta.ag\/\" target=\"_blank\" rel=\"noopener noreferrer\">Augmenta<\/a>) <br><br>3) Mask R-CNN for apple segmentation (C. Callum) <br><br>4) Improving accuracy and efficiency in plant detection on a novel, benchmarking real-world dataset (L. Ohnem\u00fcller) <br><br>5) Approximated polynomial complexity Multiple Hypothesis Tracker with rigidity constrained Extended Kalman Filter (M. Mitchell) <br><br>6) Deep Learning for Fruits Image Recognition (N. Gheza) <br><br>7) Broccoli Head Classification and Segmentation (D. Acquaviva) <br><br>8) Soil detection for precision agriculture (F. Debrauwer, <a href=\"https:\/\/www.augmenta.ag\/\" target=\"_blank\" rel=\"noopener noreferrer\">Augmenta<\/a>) <br><br>9) Grape detection in real-world conditions (N. Oikonomou, <a href=\"https:\/\/www.augmenta.ag\/\" target=\"_blank\" rel=\"noopener noreferrer\">Augmenta<\/a>)&nbsp;<span data-prop=\"description\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/p> <\/div>   <\/div><\/div><div class=\"kv-ee-row\"><div class=\"kv-ee-col-12\"><div class=\"kv-ee-image\">  <\/div><\/div><\/div><\/div><\/div>\n  <\/div>\n<\/section>\n<style scoped>.goveda96 .kv-ee-section{display:flex;align-items:center}.goveda96 .kv-ee-text{margin-bottom:2rem}.goveda96 .kv-ee-cover-title{margin-bottom:1rem}.goveda96 .kv-ee-cover-description{color:rgba(var(--kv-ee-text1-rgb),.75);max-width:32rem}.goveda96 .kv-ee-buttons{display:flex;flex-direction:column;align-items:center;margin-bottom:2.75rem}.goveda96 .kv-ee-button{display:inline-flex;position:relative}.goveda96 .kv-ee-button i{order:2}.goveda96 .kv-ee-button div{order:1}.goveda96 .kv-ee-button:not(:first-child):before{content:'';display:block;height:1.25rem;width:1px;background-color:rgba(var(--kv-ee-text1-rgb),.12);position:absolute;top:0;left:50%;transform:translate(-50%,calc(-100% - .375rem))}.goveda96 .kv-ee-cover-image{width:100%;padding-bottom:45%;background-size:cover;background-position:center;background-repeat:no-repeat}.goveda96 .kv-ee-align-left{text-align:left}.goveda96 .kv-ee-align-left .kv-ee-buttons{align-items:flex-start}.goveda96 .kv-ee-align-center{text-align:center}.goveda96 .kv-ee-align-center .kv-ee-cover-description{margin-left:auto;margin-right:auto}.goveda96 .kv-ee-align-right{text-align:right}.goveda96 .kv-ee-align-right .kv-ee-cover-description{margin-left:auto;margin-right:0}.goveda96 .kv-ee-align-right .kv-ee-buttons{align-items:flex-end}<\/style><div\n      class=\"kv-control-placeholder kv-_page\"\n      data-kv-control=\"4\">\n    <\/div> <section class=\"background-id_0 section-1633005173795 goveda96\" style=\" position:relative;\">\n  <a name=\"section1633005173795\"><\/a>\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"background\">\n  <\/div> <div class='kv-background  ' style=\" background-color: rgb(255,255,255);\">\n        \n        <div class='kv-background-inner '  style=\"\n          \n          \n          \n          background-color: rgb(255,255,255);\n          \"><\/div>\n          \n<\/div>\n\n  <div class=\"position-relative kv-content\">\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"content\">\n  <\/div> <div class=\"kv-ee-section kv-ee-section--md \"><div class=\"kv-ee-container kv-ee-align-left\"><div class=\"kv-ee-row\"><div class=\"kv-ee-col-lg-12 kv-ee-mx-auto\">  <div class=\"kv-ee-text\">  <h1 class=\"kv-ee-cover-title kv-ee-section-title kv-ee-hide-desktop kv-ee-page-title--sm\" data-type=\"text\" tabindex=\"0\">Computer Vision<span data-prop=\"title\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/h1> <p class=\"kv-ee-cover-description kv-ee-section-description kv-ee-body--md\" data-type=\"text\" tabindex=\"0\">1)\tPOG: Proportionality-based Occlusion Grid contextual explanations for semantic segmentation (A. Herbert)\n<br><br>2)\tAerial to street view image translation using cascaded conditional GANs (K. Singh)\n<br><br>3)\tAutomatic Emotion Analysis Using A Deep Learning Fusion Model On Audio And Video Data (T. Cuong)\n<br><br>4)\tCounting People in the Street from Video (E. Korzen)\n<br><br>5)\tDeep Learning for Robust &amp; Fast end-to-end Tone Mapping (R. Montulet)\n<br><br>6)\tImage Classification with Convolutional Neural Networks and Cubical Persistence (G. Giouvanis, <a href=\"https:\/\/faunawatch.org\/\" target=\"_blank\" rel=\"noopener noreferrer\">Faunawatch<\/a>)\n<br><br>7)\tFine Grained Action Recognition of Skateboarding Tricks (F. Calsius)\n<br><br>8)\tUnsupervised Domain Adaptation for Image Classification (D. Acquaviva)\n<span data-prop=\"description\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/p> <\/div>   <\/div><\/div><div class=\"kv-ee-row\"><div class=\"kv-ee-col-12\"><div class=\"kv-ee-image\">  <\/div><\/div><\/div><\/div><\/div>\n  <\/div>\n<\/section>\n<style scoped>.goveda96 .kv-ee-section{display:flex;align-items:center}.goveda96 .kv-ee-text{margin-bottom:2rem}.goveda96 .kv-ee-cover-title{margin-bottom:1rem}.goveda96 .kv-ee-cover-description{color:rgba(var(--kv-ee-text1-rgb),.75);max-width:32rem}.goveda96 .kv-ee-buttons{display:flex;flex-direction:column;align-items:center;margin-bottom:2.75rem}.goveda96 .kv-ee-button{display:inline-flex;position:relative}.goveda96 .kv-ee-button i{order:2}.goveda96 .kv-ee-button div{order:1}.goveda96 .kv-ee-button:not(:first-child):before{content:'';display:block;height:1.25rem;width:1px;background-color:rgba(var(--kv-ee-text1-rgb),.12);position:absolute;top:0;left:50%;transform:translate(-50%,calc(-100% - .375rem))}.goveda96 .kv-ee-cover-image{width:100%;padding-bottom:45%;background-size:cover;background-position:center;background-repeat:no-repeat}.goveda96 .kv-ee-align-left{text-align:left}.goveda96 .kv-ee-align-left .kv-ee-buttons{align-items:flex-start}.goveda96 .kv-ee-align-center{text-align:center}.goveda96 .kv-ee-align-center .kv-ee-cover-description{margin-left:auto;margin-right:auto}.goveda96 .kv-ee-align-right{text-align:right}.goveda96 .kv-ee-align-right .kv-ee-cover-description{margin-left:auto;margin-right:0}.goveda96 .kv-ee-align-right .kv-ee-buttons{align-items:flex-end}<\/style><div\n      class=\"kv-control-placeholder kv-_page\"\n      data-kv-control=\"5\">\n    <\/div> <section class=\"background-id_0adjacent section-1633004739125 goveda96\" style=\" position:relative;\">\n  <a name=\"section1633004739125\"><\/a>\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"background\">\n  <\/div> <div class='kv-background  ' style=\" background-color: rgb(249,249,249);\">\n        \n        <div class='kv-background-inner '  style=\"\n          \n          \n          \n          background-color: rgb(249,249,249);\n          \"><\/div>\n          \n<\/div>\n\n  <div class=\"position-relative kv-content\">\n    <div\n    class=\"kv-control-placeholder kv-_section\"\n    data-kv-control=\"content\">\n  <\/div> <div class=\"kv-ee-section kv-ee-section--md \"><div class=\"kv-ee-container kv-ee-align-left\"><div class=\"kv-ee-row\"><div class=\"kv-ee-col-lg-12 kv-ee-mx-auto\">  <div class=\"kv-ee-text\">  <h1 class=\"kv-ee-cover-title kv-ee-section-title kv-ee-hide-desktop kv-ee-page-title--sm\" data-type=\"text\" tabindex=\"0\">Satellite imaging<span data-prop=\"title\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/h1> <p class=\"kv-ee-cover-description kv-ee-section-description kv-ee-body--md\" data-type=\"text\" tabindex=\"0\">1) A new approach to automatic neural search (NAS) applied to satellite images of farms (A. Roelofs) <br><br>2) Possibilities to improve the performance and robustness of U-Nets for image segmentation in satellite images with a focus on attention mechanisms and transfer learning (P. Rinkwitz) <br><br>3) Super-resolution and de-noising on XMM-Newton images using convolutional neural networks (S. Sweere, ESA-<a href=\"https:\/\/www.esa.int\/About_Us\/ESAC\" target=\"_blank\" rel=\"noopener noreferrer\">ESAC European Space Astronomy Center) <\/a><br><br>4) Comparison and Refinement of Convolutional Neural Network Techniques for Urban Change Detection (C. Tod) <br><br>5) Detecting Land Cover Changes in Satellite Images Using a Modified U-Net (E. Rauth) <br><br>6) Wetland Classification in Permafrost using Deep Learning for Estimation of GHG (F. Rustemeyer, <a href=\"https:\/\/www.sei.org\/\" target=\"_blank\" rel=\"noopener noreferrer\">Stockholm Environment Institute<\/a>)<br><span data-prop=\"description\" class=\"ck-editable-element\" data-editable=\"basic\" style=\"display:none;\"><\/span><\/p> <\/div>   <\/div><\/div><div class=\"kv-ee-row\"><div class=\"kv-ee-col-12\"><div class=\"kv-ee-image\">  <\/div><\/div><\/div><\/div><\/div>\n  <\/div>\n<\/section>\n<style scoped>.goveda96 .kv-ee-section{display:flex;align-items:center}.goveda96 .kv-ee-text{margin-bottom:2rem}.goveda96 .kv-ee-cover-title{margin-bottom:1rem}.goveda96 .kv-ee-cover-description{color:rgba(var(--kv-ee-text1-rgb),.75);max-width:32rem}.goveda96 .kv-ee-buttons{display:flex;flex-direction:column;align-items:center;margin-bottom:2.75rem}.goveda96 .kv-ee-button{display:inline-flex;position:relative}.goveda96 .kv-ee-button i{order:2}.goveda96 .kv-ee-button div{order:1}.goveda96 .kv-ee-button:not(:first-child):before{content:'';display:block;height:1.25rem;width:1px;background-color:rgba(var(--kv-ee-text1-rgb),.12);position:absolute;top:0;left:50%;transform:translate(-50%,calc(-100% - .375rem))}.goveda96 .kv-ee-cover-image{width:100%;padding-bottom:45%;background-size:cover;background-position:center;background-repeat:no-repeat}.goveda96 .kv-ee-align-left{text-align:left}.goveda96 .kv-ee-align-left .kv-ee-buttons{align-items:flex-start}.goveda96 .kv-ee-align-center{text-align:center}.goveda96 .kv-ee-align-center .kv-ee-cover-description{margin-left:auto;margin-right:auto}.goveda96 .kv-ee-align-right{text-align:right}.goveda96 .kv-ee-align-right .kv-ee-cover-description{margin-left:auto;margin-right:0}.goveda96 .kv-ee-align-right .kv-ee-buttons{align-items:flex-end}<\/style>","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"wb4wp-template.php","meta":{"nf_dc_page":"","WB4WB4WP_MODE":"","WB4WP_PAGE_SCRIPTS":"","WB4WP_PAGE_STYLES":"","WB4WP_PAGE_FONTS":"","WB4WP_PAGE_HEADER":"","WB4WP_PAGE_FOOTER":"","footnotes":""},"class_list":["post-1114","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=\/wp\/v2\/pages\/1114","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1114"}],"version-history":[{"count":0,"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=\/wp\/v2\/pages\/1114\/revisions"}],"wp:attachment":[{"href":"https:\/\/alexiabriassouli.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1114"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}