{"id":173,"date":"2020-09-02T12:28:18","date_gmt":"2020-09-02T12:28:18","guid":{"rendered":"https:\/\/ainst.scify.org\/?page_id=173"},"modified":"2022-03-29T06:47:30","modified_gmt":"2022-03-29T06:47:30","slug":"ainst2020-2","status":"publish","type":"page","link":"https:\/\/ainst.scify.org\/?page_id=173","title":{"rendered":"Program AINST2020"},"content":{"rendered":"\n

<\/p>\n\n\n

\n\n\n\n\n\n\n\n\n
Session 1: AI in materials and life sciences and applications<\/strong><\/td>\n<\/tr>\n
\n

17:00\u201317:40
Keynote: Prof. Y. Kevrekidis \u2013 Learning Coarse-Grained and Emergent Evolution Equations from Data<\/strong><\/p>\n

17:40\u201318:15
Presentations:
<\/strong>Shengze Cai, He Li, Fuyin Zheng, Fang Kong,Ming Dao and George Karniadakis \u2013 3D Motion and Pressure Inference of Blood Flow in a Microchip via Physics-Informed Neural Networks
Antonios Stellas, George Giannakopoulos and Vassilios Constantoudis \u2013 Hybridizing AI and domain knowledge in nanotechnology: The example of surface roughness effects on wetting behavior
Alexios Chatzigoulas and Zoe Cournia \u2013 Prediction of protein-membrane interfaces of peripheral membrane proteins using machine learning<\/p>\n

18:15\u201318:35
Virtual poster session\/Lightning talks:<\/strong>
Will Van Hyning, Behnam Ahmadikia, Orestis Paraskevas, Jonathan Hestroffer, Irene Beyerlein and Christos Thrampoulidis \u2013 Bayesian optimization for maximizing the stiffness of polycrystalline HCP titanium<\/a>
Panagiotis Krokidas, Stelios Karozis, George Giannakopoulos, Michael Kainourgiakis and Theodore Steriotis \u2013 Machine Learning-driven design of CO2-selective metal-organic framework membranes<\/a>
Effrosyni Karakitsou, Carles Foguet, Silvia Marin, Pedro de Atauri, Jean-Baptiste Cazier and Marta Cascante \u2013 Combining GSMMs with machine learning: a new tool in the development of personalised medicine<\/a>
Stelios Karozis, George Giannakopoulos and Micheal Kainourgiakis \u2013 A data-driven analysis of self-assembled lipid bilayer<\/a>
Christina Vasilopoulou, Nikiforos Pittaras and George Giannakopoulos \u2013 A study of different, personalised representations of multi-omic data for bladder cancer tissue prediction<\/a>
Anastasios Gkotzias \u2013 Carbon Nano \u2013 Injectors in Living Cells; Workflow Design of Molecular Simulations<\/a><\/p>\n<\/td>\n<\/tr>\n

Session 2: AI in environmental science<\/strong><\/td>\n<\/tr>\n
\n

18:35\u201319:15
Keynote: Prof. I. Athanasiadis \u2013 Artificial intelligence for digital twins in natural and agricultural sciences<\/strong><\/p>\n

19.15\u201320.10
Presentations:
<\/strong>Vasilis Pollatos, Loukas Kouvaras and Eleni Charou \u2013 Land Cover Semantic Segmentation Using ResUNet
Dimitrios Politikos, Elias Fakiris, Athanasios Davvetas, Iraklis Klampanos and George Papatheodorou \u2013 Deep learning for automating seafloor marine litter detection
Evangelos Athanasakis, Theodosios Kassandros and Kostas Karatzas \u2013 Analysis of traffic and air pollutant patterns in Thessaloniki city centre, Greece
Aristotelis Kyriakis and Konstantinos Karafasoulis \u2013 An AI approach in Radioactive Source Localization by a Network of small form factor CZT Sensors
Athanasios Davvetas and Iraklis Angelos Klampanos \u2013 Unsupervised Severe Weather Detection Via Joint Representation Learning Over Textual and Weather Data<\/p>\n

20.10\u201320.30
Virtual poster session\/Lightning talks:<\/strong>
Dimitrios Politikos, Georgios Petasis, Archontia Chatzispyrou, Chryssi Mytilineou and Aikaterini Anastasopoulou \u2013 Deep Learning in Fisheries: Automating fish age prediction combining otolith images and convolution neural networks<\/a>
Petros Zimianitis and Konstantinos Karatzas \u2013 Analysis and modeling of low-cost air quality sensor data towards their computational improvement<\/a>
Nikolaos Sykiniotis, Athanasios Davvetas and Iraklis Angelos Klampanos \u2013 Evaluating Clustering Strategies for Fixed and Variable Length Weather Data Segmentations<\/a>
Stelios Karozis and Iraklis Klampanos \u2013 A Deep Learning approach for spatial and time error correction of Numerical Weather Prediction simulation data<\/a>
Konstantinos Biziouras, Theodosios Kassandros and Konstantinos Karatzas \u2013 On-line environmental data analysis and modelling with Computational Intelligence method<\/a><\/p>\n<\/td>\n<\/tr>\n

Session 3: Interaction between quantum computing and AI<\/strong><\/td>\n<\/tr>\n
\n

20.30\u201321.10
Keynote: Dr. V.Katopodis \u2013 Quantum Computing for the 21st Century<\/strong><\/p>\n

21.10\u201321.35
Presentations:
<\/strong>Dionisis Stefanatos, Kostas Blekos, Ioannis Thanopulos and Emmanuel Paspalakis \u2013 Quantum control of generic quantum systems and nanostructures for quantum technologies: Different approaches
Ioannis Karafyllidis, Panagiotis Dimitrakis and Georgios Sirakoulis \u2013 Quantum computing for biological molecules and pathways<\/p>\n

21.35\u201322.00
Virtual poster session\/Lightning talks:<\/strong>
Anastasios Markellos, Filippos Filias and Kostas Blekos \u2013 Quantum machine learning for image classification using kernel methods<\/a>
Filippos Filias, Anastasios Markellos and Kostas Blekos \u2013 AI in quantum error correction: Generating self-correcting quantum circuits with genetic algorithms<\/a>
Athina Bikaki, Vasileios Vlaseros and Iraklis Klampanos \u2013 Two AI-Inspired Methods for Estimating an SME\u2019s Total Transactions Wallet<\/a>
Kostas Blekos \u2013 Particle track reconstruction with a hybrid quantum machine learning algorithm.<\/a>
Closing<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n

Private room links for lighting\/poster sessions <\/strong><\/h2>\n\n\n\n

(usable during the workshop)<\/em><\/p>\n\n\n\n

Session 1 <\/strong><\/p>\n\n\n\n

1)Will Van Hyning, Behnam Ahmadikia, Orestis Paraskevas, Jonathan Hestroffer, Irene Beyerlein and Christos Thrampoulidis \u2013 Bayesian optimization for maximizing the stiffness of polycrystalline HCP titanium<\/p>\n\n\n\n

https:\/\/meet.jit.si\/BO_HCPTi_QA<\/a><\/p>\n\n\n\n

2)Panagiotis Krokidas, Stelios Karozis, George Giannakopoulos, Michael Kainourgiakis and Theodore Steriotis \u2013 Machine Learning-driven design of CO2-selective metal-organic framework membranes<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-2020_KROKIDAS<\/a><\/p>\n\n\n\n

3)Effrosyni Karakitsou, Carles Foguet, Silvia Marin, Pedro de Atauri, Jean-Baptiste Cazier and Marta Cascante \u2013 Combining GSMMs with machine learning: a new tool in the development of personalised medicine<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-paper14<\/a><\/p>\n\n\n\n

4)Stelios Karozis, George Giannakopoulos and Micheal Kainourgiakis \u2013 A data-driven analysis of self-assembled lipid bilayer<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-2020_KAROZIS<\/a><\/p>\n\n\n\n

5)Christina Vasilopoulou, Nikiforos Pittaras and George Giannakopoulos \u2013 A study of different, personalised representations of multi-omic data for bladder cancer tissue prediction<\/p>\n\n\n\n

https:\/\/join.skype.com\/gdihsvUOu8Uy<\/a><\/p>\n\n\n\n

6)Anastasios Gkotzias \u2013 Carbon Nano \u2013 Injectors in Living Cells; Workflow Design of Molecular Simulations<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-2020_GOTZIAS<\/a><\/p>\n\n\n\n

Session 2<\/strong><\/p>\n\n\n\n

1) Dimitrios Politikos, Georgios Petasis, Archontia Chatzispyrou, Chryssi Mytilineou and Aikaterini Anastasopoulou \u2013 Deep Learning in Fisheries: Automating fish age prediction combining otolith images and convolution neural networks<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-paper7<\/a><\/p>\n\n\n\n

2) Petros Zimianitis and Konstantinos Karatzas \u2013 Analysis and modeling of low-cost air quality sensor data towards their computational improvement<\/p>\n\n\n\n

https:\/\/authgr.zoom.us\/j\/95710184005<\/a><\/p>\n\n\n\n

3) Nikolaos Sykiniotis, Athanasios Davvetas and Iraklis Angelos Klampanos \u2013 Evaluating Clustering Strategies for Fixed and Variable Length Weather Data Segmentations<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-2020_SYKINIOTIS<\/a><\/p>\n\n\n\n

4) Stelios Karozis and Iraklis Klampanos \u2013 A Deep Learning approach for spatial and time error correction of Numerical Weather Prediction simulation data<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-2020_KAROZIS<\/a><\/p>\n\n\n\n

5) Konstantinos Biziouras, Theodosios Kassandros and Konstantinos Karatzas \u2013 On-line environmental data analysis and modelling with Computational Intelligence method<\/p>\n\n\n\n

https:\/\/authgr.zoom.us\/j\/95710184005<\/a><\/p>\n\n\n\n

Session 3<\/strong><\/p>\n\n\n\n

1) Anastasios Markellos, Filippos Filias and Kostas Blekos \u2013 Quantum machine learning for image classification using kernel methods<\/p>\n\n\n\n

http:\/\/meet.jit.si\/AINST-paper20<\/a><\/p>\n\n\n\n

2) Filippos Filias, Anastasios Markellos and Kostas Blekos \u2013 AI in quantum error correction: Generating self-correcting quantum circuits with genetic algorithms<\/p>\n\n\n\n

http:\/\/meet.jit.si\/AINST-paper12<\/a><\/p>\n\n\n\n

3) Athina Bikaki, Vasileios Vlaseros and Iraklis Klampanos \u2013 Two AI-Inspired Methods for Estimating an SME\u2019s Total Transactions Wallet<\/p>\n\n\n\n

https:\/\/meet.jit.si\/AINST-paper23<\/a><\/p>\n\n\n\n

4) Kostas Blekos \u2013 Particle track reconstruction with a hybrid quantum machine learning algorithm.<\/p>\n\n\n\n

http:\/\/meet.jit.si\/AINST-paper27<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Session 1: AI in materials and life sciences and applications 17:00\u201317:40Keynote: Prof. Y. Kevrekidis \u2013 Learning Coarse-Grained and Emergent Evolution Equations from Data 17:40\u201318:15Presentations:Shengze Cai, He Li, Fuyin Zheng, Fang Kong,Ming Dao and George Karniadakis \u2013 3D Motion and Pressure Inference of Blood Flow in a Microchip via Physics-Informed Neural NetworksAntonios Stellas, George Giannakopoulos and … <\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/ainst.scify.org\/index.php?rest_route=\/wp\/v2\/pages\/173"}],"collection":[{"href":"https:\/\/ainst.scify.org\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ainst.scify.org\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ainst.scify.org\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ainst.scify.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=173"}],"version-history":[{"count":20,"href":"https:\/\/ainst.scify.org\/index.php?rest_route=\/wp\/v2\/pages\/173\/revisions"}],"predecessor-version":[{"id":247,"href":"https:\/\/ainst.scify.org\/index.php?rest_route=\/wp\/v2\/pages\/173\/revisions\/247"}],"wp:attachment":[{"href":"https:\/\/ainst.scify.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=173"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}