{"id":12045,"date":"2023-07-06T15:18:12","date_gmt":"2023-07-06T13:18:12","guid":{"rendered":"https:\/\/new.sano.science\/?post_type=people&#038;p=12045"},"modified":"2026-01-31T19:49:00","modified_gmt":"2026-01-31T18:49:00","slug":"sabina-martyniak","status":"publish","type":"people","link":"https:\/\/sano.science\/people\/sabina-martyniak\/","title":{"rendered":"Sabina Martyniak"},"excerpt":{"rendered":"<p>PhD Student in Medical Imaging and Robotics<\/p>\n","protected":false},"featured_media":18367,"template":"","people_teams":[19,35],"class_list":["post-12045","people","type-people","status-publish","has-post-thumbnail","hentry","people_teams-research","people_teams-medical-imaging-and-robotics-group"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.4 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Sabina Martyniak - Sano 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\/sabina-martyniak\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Sabina Martyniak\" \/>\n<meta property=\"og:description\" content=\"PhD Student in Medical Imaging and Robotics\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/people\/sabina-martyniak\/\" \/>\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=\"2026-01-31T18:49:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/07\/Sabina-Kaminska_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\\\/sabina-martyniak\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/people\\\/sabina-martyniak\\\/\",\"name\":\"Sabina Martyniak - 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She has nearly 2-years of experience in VR and mobile games. She has been passionate about biomedical engineering. She graduated from the Silesian University of Technology with a Master&#8217;s Degree in Biomedical Engineering specialising in Informatics in Medicine.The purpose of the engineering and master&#8217;s thesis was to improve the hand rehabilitation system. For the purpose of the project she designed game rehabilitation and glove construction. At Sano, she joined the Healthcare Informatics team and she\u2019ll be working on deep Learning-based Surgical Robots.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><iframe loading=\"lazy\" title=\"Meet Your Scientist - Sabina Kami\u0144ska\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/juZBCAS1I18?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/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\/sabina-kami\u0144ska-1788ab194\/","name":"LinkedIn"}],"tabs":false,"quote":"","position_with_team":{"text_before_link":"PhD Student in","link_text":"Medical Imaging and Robotics","text_after_link":"","link":"https:\/\/sano.science\/research-teams\/health-informatics-group-higs\/"},"publications":[{"ID":23781,"post_author":"8","post_date":"2025-05-20 17:20:11","post_date_gmt":"2025-05-20 15:20:11","post_content":"<!-- wp:heading {\"epAnimationGeneratedClass\":\"edplus_anim-sHGyzO\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-diego-dall-alba-nbsp-michal-nasket-nbsp-sabina-kaminska-nbsp-przemyslaw-korzeniowski\">Diego Dall'Alba,&nbsp;Micha\u0142 Nasket,&nbsp;Sabina Kaminska,&nbsp;Przemys\u0142aw Korzeniowski<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:spacer {\"height\":\"30px\",\"epAnimationGeneratedClass\":\"edplus_anim-UIbTWv\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-mmx73R\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">Robotic-assisted surgery is evolving at a fast pace and holds significant potential for improvements through automation. Yet, methods like Reinforcement Learning (RL), which require extensive task repetition, are challenging to apply directly in real surgical scenarios due to safety and feasibility concerns. This highlights the importance of using simulated environments that combine realism with computational efficiency and scalability.<br>In response to this need, we present FF-SRL (Fast and Flexible Surgical Reinforcement Learning) \u2014 a high-speed, GPU-based simulation platform tailored for robotic surgery. Unlike traditional setups, FF-SRL runs both the physics-based simulation and the RL training process entirely on a single GPU. This design eliminates common performance limitations caused by data exchange between the CPU and GPU, significantly boosting learning speed.<br>Experimental results demonstrate that FF-SRL can decrease the training duration for intricate tasks like tissue manipulation by approximately tenfold \u2014 achieving performance in just a few minutes compared to conventional hybrid simulators. This level of efficiency opens new possibilities for testing and refining RL algorithms in surgical contexts. To support further research and collaboration, we have made the FF-SRL framework freely accessible to the research community.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"30px\",\"epAnimationGeneratedClass\":\"edplus_anim-UIbTWv\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-jsuB1V\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\"><strong>Authors<\/strong>: <a href=\"https:\/\/sano.science\/people\/diego-dallalba\/\">Diego Dall'Alba<\/a>,&nbsp;<a href=\"https:\/\/sano.science\/people\/michal-naskret\/\">Micha\u0142 Naskret<\/a>,&nbsp;<a href=\"https:\/\/sano.science\/wp-content\/uploads\/2023\/07\/Sabina-Kaminska_Sano.png\">Sabina Kaminska<\/a>,&nbsp;<a href=\"https:\/\/sano.science\/people\/przemyslaw-korzeniowski\/\">Przemys\u0142aw Korzeniowski<\/a><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-NEuOqB\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\"><strong>DOI<\/strong>: 10.1109\/IROS58592.2024.10801658<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-NEuOqB\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\"><strong>Keywords<\/strong>: Robotic-assisted surgery, Reinforcement Learning (RL), Surgical simulation, GPU-based simulation, Fast and Flexible Surgical Reinforcement Learning (FF-SRL), Real-time physics simulation, Computational efficiency, Simulation platform<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"30px\",\"epAnimationGeneratedClass\":\"edplus_anim-UIbTWv\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:acf\/button {\"id\":\"block_682c9edf5049a\",\"name\":\"acf\/button\",\"data\":{\"title\":\"READ HERE\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"https:\/\/arxiv.org\/abs\/2503.18616\",\"_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":"FF-SRL: High Performance GPU-Based Surgical Simulation For Robot Learning","post_excerpt":"In: https:\/\/arxiv.org, 2025","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"ff-srl-high-performance-gpu-based-surgical-simulation-for-robot-learning","to_ping":"","pinged":"","post_modified":"2025-05-20 17:30:07","post_modified_gmt":"2025-05-20 15:30:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&#038;p=23781","menu_order":0,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":20967,"post_author":"8","post_date":"2025-01-21 16:51:16","post_date_gmt":"2025-01-21 15:51:16","post_content":"<!-- wp:heading {\"epAnimationGeneratedClass\":\"edplus_anim-6CqjM2\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-sabina-martyniak-joanna-kaleta-diego-dall-alba-michal-naskret-szymon-plotka-and-przemyslaw-korzeniowski\">Sabina Martyniak, Joanna Kaleta, Diego Dall'Alba, Micha\u0142 Naskr\u0119t, Szymon P\u0142otka, and Przemys\u0142aw Korzeniowski<br><\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:spacer {\"height\":\"40px\",\"epAnimationGeneratedClass\":\"edplus_anim-tI7h1k\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-aU2f7H\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">This work presents an innovative approach to advancing computer-assisted surgical (CAS) systems by addressing challenges in training data quality and realism.&nbsp;<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-A5sGbH\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">In this study, the authors introduce a comprehensive pipeline for creating high-quality synthetic data tailored for modern CAS systems. This pipeline integrates an advanced surgical simulator capable of generating complex annotations that surpass those found in existing public datasets. The simulator also models intricate surgical interactions, including the dynamics between instruments and deformable anatomical structures, ensuring a more realistic simulation environment.&nbsp;<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-qQq76G\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">To further enhance data realism, the researchers developed a novel image-to-image translation method based on Stable Diffusion (SD) and Low-Rank Adaptation (LoRA). This technique minimizes the visual gap between synthetic and real-world images while preserving the simulator's detailed annotations. By leveraging only a small amount of real-world data, the method enables efficient training and generalizes well to practical applications, thereby improving CAS training and guidance.&nbsp;<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-g7BCRx\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">This innovative pipeline has been validated experimentally and is a significant step forward in bridging the gap between synthetic and real-world datasets for surgical applications. The dataset and code are available for the research community<a href=\"https:\/\/github.com\/SanoScience\/SimuScope\" target=\"_blank\" rel=\"noreferrer noopener nofollow\"> github.com\/SanoScience\/SimuScope<\/a><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"40px\",\"epAnimationGeneratedClass\":\"edplus_anim-tI7h1k\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-H3zZ17\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\"><strong>Authors<\/strong>: Sabina Martyniak, Joanna Kaleta, Diego Dall'Alba, Micha\u0142 Naskr\u0119t, Szymon P\u0142otka, and Przemys\u0142aw Korzeniowski<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-aU2f7H\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\"><strong>DOI<\/strong>: 10.48550\/arXiv.2412.02332&nbsp;<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"40px\",\"epAnimationGeneratedClass\":\"edplus_anim-tI7h1k\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:acf\/button {\"id\":\"block_678fc2ae54c84\",\"name\":\"acf\/button\",\"data\":{\"title\":\"READ HERE\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"https:\/\/arxiv.org\/abs\/2412.02332\",\"_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":"SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models","post_excerpt":"Conference manuscript in IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), 2024","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"simuscope-realistic-endoscopic-synthetic-dataset-generation-through-surgical-simulation-and-diffusion-models","to_ping":"","pinged":"","post_modified":"2025-05-19 21:17:07","post_modified_gmt":"2025-05-19 19:17:07","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&#038;p=20967","menu_order":0,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":28554,"post_author":"8","post_date":"2026-01-31 19:47:50","post_date_gmt":"2026-01-31 18:47:50","post_content":"<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-7IiDS7\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">Mateusz W\u00f3jcikowski, Diego Dall'Alba, Sabina Martyniak, Szymon P\u0142otka, Renata Szydlak, Piotr Walecki, Andrzej A Kononowicz, Przemyslaw Korzeniowski<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"20px\",\"epAnimationGeneratedClass\":\"edplus_anim-eOcEsc\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-7IiDS7\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\"><strong>VR Simulator for Robotic-Assisted Surgery Training<br><\/strong>This study explored the use of a <strong>VR-based robotic surgery simulator<\/strong> designed for medical education. The simulator, compatible with Meta Quest 2\/3\/Pro headsets, was tested by 67 international medical students to evaluate its usability and educational value.<br>The system reproduces the cholecystectomy procedure using the Extended Position-Based Dynamics (XPBD) method to simulate soft tissue behavior in real time (1 kHz physics, 90 Hz graphics). Most participants rated the simulator as a valuable learning tool, with over 80% reporting improved understanding of anatomy and surgical workflows.<br>Students appreciated the safe, immersive practice environment and the opportunity for repeated training. Suggested improvements included enhancing tissue realism, diversifying the range of surgical scenarios, and optimizing the user interface for VR interaction. Overall, the project highlights the strong potential of VR simulators to transform surgical training.<br>Read more in the full article at the link below.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"20px\",\"epAnimationGeneratedClass\":\"edplus_anim-eOcEsc\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:paragraph {\"epAnimationGeneratedClass\":\"edplus_anim-7IiDS7\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<p class=\" eplus-wrapper\">Conference: Hamlyn Symposium on Medical Robotics 2025<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"20px\",\"epAnimationGeneratedClass\":\"edplus_anim-bNjJc0\",\"epGeneratedClass\":\"eplus-wrapper\"} -->\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n<!-- \/wp:spacer -->\n\n<!-- wp:acf\/button {\"id\":\"block_697e4d14f1bac\",\"name\":\"acf\/button\",\"data\":{\"title\":\"Read\/Download\",\"_title\":\"field_61d40397c2f0a\",\"button_type\":\"link\",\"_button_type\":\"field_63bbde3b8f0d0\",\"url\":\"https:\/\/events.plgrid.pl\/event\/89\/contributions\/745\/attachments\/195\/440\/VRSR_for_Marian_2.pdf\",\"_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":"Affordable Virtual Reality Simulation for Robotic Surgery: Preliminary Usability and Educational Evaluation","post_excerpt":"Conference abstract:  Hamlyn Symposium on Medical Robotics 2025, 2025","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"affordable-virtual-reality-simulation-for-robotic-surgery-preliminary-usability-and-educational-evaluation","to_ping":"","pinged":"","post_modified":"2026-01-31 19:47:51","post_modified_gmt":"2026-01-31 18:47:51","post_content_filtered":"","post_parent":0,"guid":"https:\/\/sano.science\/?post_type=research&#038;p=28554","menu_order":0,"post_type":"research","post_mime_type":"","comment_count":"0","filter":"raw"}]},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12045","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":12,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12045\/revisions"}],"predecessor-version":[{"id":28565,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people\/12045\/revisions\/28565"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media\/18367"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=12045"}],"wp:term":[{"taxonomy":"people_teams","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/people_teams?post=12045"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}