Academic Curriculum Vitae

Asan Agibetov, PhD

5 years of experience in developing clinical prediction models using AI/ML Python stack. 9 years of experience in biomedical data modelling and visualization using semantic web and computer graphics.

PhD 2013 – 2017, PostDoc 2017 – 2022, h-index 10, 260 citations (source: Google Scholar, as of Feb 2023)

Publication track record
16 original research journal articles, 6 as first-author
12 conference/workshop original research peer-reviewed papers, 7 as first-author
1 book chapter
Funding and fellowships
10,000 Euro, Research grant “Reducing costs of segmentation labeling in cardiac MRI using explainable AI” from Austrian Cardiological Society (Österreichishe Kardiologische Gesselschaft)
5,000 Euro, funding from internal cooperation agreement with the Cardiology department at MUW
Marie-Curie EU FP7 Initial Training Network “MultiScaleHuman” (Agreement n. 289897) Early Stage Researcher fellowship (2013 – 2015)
Research avenues
RA1: Clinical prediction models (2017–present), published: 9 journals (2 as first), 1 in review, funding: 15,000 Euro
RA2: Neuro-symbolic embeddings (2017–present), published: 5 journals (3 as first)
RA3: Virtual Physiological Human (PhD, 2013–2017), published: 2 journals (1 as first), Marie-Curie fellowship
Computational skills
Deep learning and data science (Python stack): pytorch, tensorflow, keras, numpy/scipy, sklearn, pandas
High-performance computing: Linux/Unix CLI toolchains, SLURM scheduler, dask (Python, distributed ML/DL)
Web development: Flask (Python, backend), ReactJS (JavaScript, frontend)
Languages
Native: Russian and Kyrgyz
Fluent: English (C2), French (C2), Italian (C1)
Basic University level: German (B1), Turkish (A2)

Education

2013 – 2017
PhD in Computer Science, CNR-IMATI1/University of Genoa, Genoa, Italy
Fellowship: EU FP7 Marie-Curie ITN (2013–2015), Agreement n. 289897
PhD Thesis: “Biomedical knowledge spaces: handling complexity, uncertainty and incompleteness via graph analysis”. Supervisors: Michela Spagnuolo (CNR-IMATI), Giovanna Guerrini (University of Genoa)
2008 – 2012
BSc and MSc in Computer Science, Joseph Fourier University, Grenoble, France
Master speciality “Artificial Intelligence and the Web”
Master thesis: “Essence of JSON”. Research internship at INRIA2, Grenoble, France.
Bachelor speciality “Informatics and Applied Mathematics”

Experience

Aug 2022 – present
Senior Data Scientist, Takeda Pharmaceutical, Vienna, Austria
Jun 2017 – Jun 2022
Postdoc, CeMSIIS-AID1, Medical University of Vienna, Vienna, Austria
Oct 2015 – May 2017
Research Assistant, CNR-IMATI2, Genoa, Italy.
Jan 2013 – Sep 2015
Early Stage Researcher, Marie-Curie EU FP7 ITN “MultiScaleHuman” (Agreement n. 289897), CNR-IMATI2, Genoa, Italy.
Sep 2012 – Dec 2012
Software Developer; Ausy (IT consulting company) for client France Telecom, Paris, France
Feb 2012 – Jul 2012
Research intern, WAM (Web Adaptation Media) team at INRIA3, Grenoble, France
Feb 2011 – Jul 2011
Research intern, MOAÏS4 team at INRIA, Grenoble, France
Summer 2010
Intern at Thermodata (Chemoinformatics company), Grenoble, France.

Peer-reviewed publications

publications since 2014 thematically organized according to the research avenues (see also 1 page)

Journals

Journal Impact Factor (IF) data pulled from the Journal Citation Reports 2020 from Clarivate Analytics

RA1. Clinical prediction models (2017–2022)

[J.1] IF 4.9
Bologheanu, Razvan, Lorenz Kapral, Daniel Laxar, Mathias Maleczek, Christoph Dibiasi, Sebastian Zeiner, Asan Agibetov, Ari Ercole, Patrick Thoral, Paul Elbers, Clemens Heitzinger, and Oliver Kimberger. 2023. “Development of a reinforcement learning algorithm to optimize corticosteroid therapy in critically ill patients with sepsis.” Journal of Clinical Medicine 12 (4) (February): 1513. doi:10.3390/jcm12041513. https://doi.org/10.3390/jcm12041513.
[J.2] IF 4.9
Agibetov, Asan, Andreas Kammerlander, Franz Duca, Christian Nitsche, Matthias Koschutnik, Carolina Doná, Theresa-Marie Dachs, René Rettl, Lore Schrutka, Christina Binder, Johannes Kastner, Hermine Agis, Renate Kain, Michaela Auer-Grumbach, Matthias Samwald, Christian Hengstenberg, Georg Dorffner, Julia Mascherbauer, and Diana Bonderman. 2021. “Convolutional neural networks for fully automated diagnosis of cardiac amyloidosis by cardiac magnetic resonance imaging.” Journal of Personalized Medicine 11 (12). doi:10.3390/jpm11121268. https://www.mdpi.com/2075-4426/11/12/1268.
[J.3] IF 4.6
Wallisch, Christine, Asan Agibetov, Daniela Dunkler, Maria Haller, Matthias Samwald, Georg Dorffner, and Georg Heinze. 2021. “Transparency of cardiovascular risk prediction: A question of (modeling) culture?” BMC Medical Research Methodology 21 (1) (December). doi:10.1186/s12874-021-01487-4. https://doi.org/10.1186%2Fs12874-021-01487-4.
[J.4] IF 5.9
Schrutka, Lore, Philip Anner, Asan Agibetov, Benjamin Seirer, Fabian Dusik, René Rettl, Franz Duca, Daniel Dalos, Theresa-Marie Dachs, Christina Binder, Roza Badr-Eslam, Johannes Kastner, Dietrich Beitzke, Christian Loewe, Christian Hengstenberg, Günther Laufer, Guenter Stix, Georg Dorffner, and Diana Bonderman. 2021. “Machine learning-derived electrocardiographic algorithm for the detection of cardiac amyloidosis.” Heart. doi:10.1136/heartjnl-2021-319846. https://heart.bmj.com/content/early/2021/10/28/heartjnl-2021-319846.
[J.5] IF 3.6
Motyka, Stanislav, Lukas Hingerl, Bernhard Strasser, Gilbert Hangel, Eva Heckova, Asan Agibetov, Georg Dorffner, Stephan Gruber, Siegfried Trattning, and Wolfgang Bogner. 2021. “K-space-based coil combination via geometric deep learning for reconstruction of non-cartesian MRSI data.” Magnetic Resonance in Medicine 86 (5): 2353–2367. doi:https://doi.org/10.1002/mrm.28876. https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28876.
[J.6] IF 3.3
Agibetov, Asan, Benjamin Seirer, Theresa-Marie Dachs, Matthias Koschutnik, Daniel Dalos, René Rettl, Franz Duca, Lore Schrutka, Hermine Agis, Renate Kain, Michaela Auer-Grumbach, Matthias Samwald, Christian Hengstenberg, Georg Dorffner, Julia Mascherbauer, and Diana Bonderman. 2020. “Machine learning enables prediction of cardiac amyloidosis by routine laboratory parameters: A proof-of-concept study.” Journal of Clinical Medicine 9 (5): 1334.
available online https://doi.org/10.3390/jcm9051334
[J.7] IF N/A
Beck-Tölly, Andrea, Michael Eder, Dietrich Beitzke, Farsad Eskandary, Asan Agibetov, Katharina Lampichler, Martina Hamböck, Heinz Regele, Johannes Kläger, Maja Nackenhorst, and Georg A. Böhmig. 2020. “Magnetic resonance imaging for evaluation of interstitial fibrosis in kidney allografts.” Transplantation Direct 6 (8) (July): e577. doi:10.1097/TXD.0000000000001009.
[J.8] IF 3.3
Schrutka, Lore, Benjamin Seirer, Franz Duca, Christina Binder, Daniel Dalos, Andreas Kammerlander, Stefan Aschauer, Lorenz Koller, Alberto Benazzo, Asan Agibetov, Marianne Gwechenberger, Christian Hengstenberg, Julia Mascherbauer, and Diana Bonderman. 2019. “Patients with heart failure and preserved ejection fraction are at risk of gastrointestinal bleeding.” Journal of Clinical Medicine 8 (8): 1240.
[J.9] IF 7.7
Binder, Christina, Marko Poglitsch, Asan Agibetov, Franz Duca, Caroline Zotter-Tufaro, Christian Nitsche, Stefan Aschauer, Andreas A Kammerlander, Beguem Oeztuerk, Christian Hengstenberg, Julia Mascherbauer, and Diana Bonderman. 2019. “Angs (angiotensins) of the alternative renin-angiotensin system predict outcome in patients with heart failure and preserved ejection fraction.” Hypertension: 119.
IF 7.0
Dibiasi, Christoph, and Asan Agibetov et al. 2023. “Predicting intraoperative hypothermia burden during non-cardiac surgery: A retrospective study comparing regression to six machine learning algorithms.” Computer Methods and Programs in Biomedicine: In review.
Equal contributions with C. Dibiasi

RA2. Neuro-symbolic embeddings (2017–present)

[J.10] IF 8.5
Asan Agibetov. 2022. “Neural graph embeddings as explicit low-rank matrix factorization for link prediction.” Pattern Recognition: 108977. doi:https://doi.org/10.1016/j.patcog.2022.108977. https://www.sciencedirect.com/science/article/pii/S0031320322004575.
available online https://doi.org/10.1016/j.patcog.2022.108977
[J.11] IF 2.2
Agibetov, Asan, and Matthias Samwald. 2020. “Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes.” Journal of Web Semantics 64: 100590.
available on arXiv (identical content to the published version) https://arxiv.org/abs/2005.07654
[J.12] IF 5.6
Breit, Anna, Simon Ott, Asan Agibetov, and Matthias Samwald. 2020. “OpenBioLink: a benchmarking framework for large-scale biomedical link prediction.” Bioinformatics 36 (13): 4097–4098.
[J.13] IF 3.2
Blagec, Kathrin, Hong Xu, Asan Agibetov, and Matthias Samwald. 2019. “Neural sentence embedding models for semantic similarity estimation in the biomedical domain.” BMC Bioinformatics 20 (1): 178:1–178:10.
[J.14] IF 3.2
Agibetov, Asan, Kathrin Blagec, Hong Xu, and Matthias Samwald. 2018. “Fast and scalable neural embedding models for biomedical sentence classification.” BMC Bioinformatics 19 (1): 541:1–541:9.
available online https://doi.org/10.1186/s12859-018-2496-4

RA3. Virtual Physiological Human (PhD, 2013–2017)

[J.15] IF 2.6
Agibetov, Asan, Ernesto Jiménez-Ruiz, Marta Ondrésik, Alessandro Solimando, Imon Banerjee, Giovanna Guerrini, Chiara E. Catalano, Joaquim M. Oliveira, Giuseppe Patanè, Rui L. Reis, and Michela Spagnuolo. 2018. “Supporting shared hypothesis testing in the biomedical domain.” Journal of Biomedical Semantics 9 (1): 9.
available online https://doi.org/10.1186/s13326-018-0177-x
[J.16] IF 1.4
Banerjee, Imon, Asan Agibetov, Chiara Eva Catalano, Giuseppe Patanè, and Michela Spagnuolo. 2016. “Semantics-driven annotation of patient-specific 3D data: A step to assist diagnosis and treatment of rheumatoid arthritis.” The Visual Computer 32 (10): 1337–1349.

Conferences/Workshops

[CW.1]
Jimenez-Ruiz, Ernesto, Asan Agibetov, Jiaoyan Chen, Matthias Samwald, and Valerie Cross. 2020. “Dividing the ontology alignment task with semantic embeddings and logic-based modules.” In Proc. European conf. On AI (ECAI 2020).
[CW.2]
Agibetov, Asan, Georg Dorffner, and Matthias Samwald. 2019. “Using hyperbolic large-margin classifiers for biological link prediction.” In Proc. Semantic deep learning (SemDeep-5) workshop @ international joint conference on AI (IJCAI) 2019, 26–30.
available online https://www.aclweb.org/anthology/W19-5805
[CW.3]
Agibetov, Asan, and Matthias Samwald. 2018. “Global and local evaluation of link prediction tasks with neural embeddings.” In Proc. Semantic deep learning (SemDeep-4) workshop @ international semantic web conference (ISWC 2018), 89–102.
[CW.4]
Jiménez-Ruiz, Ernesto, Asan Agibetov, Matthias Samwald, and Valerie Cross. 2018. “We divide, you conquer: From large-scale ontology alignment to manageable subtasks with a lexical index and neural embeddings.” In Proc. Ontology matching workshop @ international semantic web conferencea (ISWC 2018) 2018, 13–24.
[CW.5]
Agibetov, Asan, and Matthias Samwald. 2018. “Fast and scalable learning of neuro-symbolic representations of biomedical knowledge.” In Proc. Deep learning for knowledge graphs and semantic technologies workshop (DL4KGS) @ extended semantic web conerence (ESWC 2018), 62–71.
[CW.6]
Agibetov, Asan, Karelia Tecante, Chiara Eva Catalno, Giuseppe Patanè, Christof Hurschler, and Michela Spagnuolo. 2016. “GaitViewer: Semantic Gait Data Analysis and Visualization Tool.” In Proc. Of Knowledge Discovery on the Web. Vol. 1748.
[CW.7]
Agibetov, Asan, Chiara Eva-Catalano, Giuseppe Patané, and Michela Spagnuolo. 2016. “A Web-based Application for Difference Assessment of Medical Image Segmentations.” In Proc. Spring conference in computer graphics, ed by. The Eurographics Association.
[CW.8]
Agibetov, Asan, Ernesto Jiménez-Ruiz, Alessandro Solimando, Giovanna Guerrini, Giuseppe Patanè, and Michela Spagnuolo. 2015. “Towards Shared Hypothesis Testing in the Biomedical Domain.” In Proc. Of international conference semantic web applications and tools for life sciences SWAT4LS 2015, 1546:33–37.
[CW.9]
Agibetov, Asan, Giuseppe Patanè, and Michela Spagnuolo. 2015. “Grontocrawler: Graph-Based Ontology Exploration.” In Proc. Eurographics Italian Chapter Conference - smart Tools and Apps for Graphics, 67–76.
[CW.10]
Vaquero, Ricardo Manuel Millán, Asan Agibetov, Jan Rzepecki, Marta Ondresik, Alexander Vais, Joaquim Miguel Oliveira, Giuseppe Patanè, Karl-Ingo Friese, Rui Luis Reis, Michela Spagnuolo, and Franz-Erich Wolter. 2015. “A Semantically Adaptable Integrated Visualization and Natural Exploration of Multi-scale Biomedical Data.” In International Conference on Information Visualisation, 543–552.
[CW.11]
Banerjee, Imon, Asan Agibetov, Chiara Eva-Catalano, Giuseppe Patané, and Michela Spagnuolo. 2015. “Semantic annotation of patient-specific 3D anatomical models.” In Proc. International Conference on Cyberworlds, ed by. IEEE, 22–29.
[CW.12]
Agibetov, Asan, Ricardo Manuel Millan Vaquero, Karl-Ingo Friese, Giuseppe Patane, Michela Spagnuolo, and Franz-Erich Wolter. 2014. “Integrated Visualization and Analysis of a Multi-scale Biomedical Knowledge Space.” In Proc. EuroVis Workshop on Visual Analytics. The Eurographics Association.

Clinical conference abstracts/posters

Published posters at top cardiological conferences. Not counted as publications

[P.1]
Stria, Alessa, and Asan Agibetov. 2021. “Towards reducing segmentation labelling costs for CMR imaging using explainable AI.” In Wiener klinische wochenschrift, 133:S66–S68. Presented at the Annual meeting of Austrian Society of Cardiology (virtual), 2021
[P.2]
Agibetov, Asan, Benjamin Seirer, Theresa-Marie Dachs, Matthias Koschutnik, Daniel Dalos, René Rettl, Franz Duca, Lore Schrutka, Hermine Agis, Renate Kain, Michaela Auer-Grumbach, Matthias Samwald, Christian Hengstenberg, Georg Dorffner, Julia Mascherbauer, and Diana Bonderman. 2019. “Extremely boosted prediction of cardiac amyloidosis by routine laboratory paramaters.” In European heart journal, 40:1677–1677. Presented at the Congress of European Society of Cardiology in Paris, 2018
[P.3]
Agibetov, Asan, Benjamin Seirer, Theresa-Marie Dachs, Matthias Koschutnik, Daniel Dalos, René Rettl, Franz Duca, Lore Schrutka, Hermine Agis, Renate Kain, Michaela Auer-Grumbach, Matthias Samwald, Christian Hengstenberg, Georg Dorffner, Julia Mascherbauer, and Diana Bonderman. 2019. “Optimal variable selection for simple prediction model of cardiac amyloidosis by routine laboratory parameters.” In Wiener klinische wochenschrift, 131:367–368. Presented at the Annual meeting of Austrian Society of Cardiology in Salzburg, 2018

Invited book chapters

[B.1]
Agibetov, Asan. 2013. Essence of JSON. LAP LAMBERT Academic Publishing, OmniScriptum GmbH & Co. KG.

Third-party funding and fellowships

2021 – 2022
Research grant “Reducing costs of segmentation labeling in cardiac MRI using explainable AI” from Austrian Cardiological Society (10,000 Euro, Österreichishe Kardiologische Gesselschaft)
2020 – 2021
Funding from internal cooperation agreement at Medical University of Vienna (~5,000 Euro)
2013 – 2015
Marie-Curie EU FP7 Initial Training Network “MultiScaleHuman” (Agreement n. 289897) Early Stage Researcher fellowship

Invited lectures and talks

9–13 April 2018
PhD level: Lecture series on “Doing research in Europe”, 40 hours of lectures and final examination (100%). Kyrgyz National University (KNU) of Zh. Balassagyn, Bishkek, Kyrgyz Republic

Invited talks

Excluding accepted conference/workshop papers and posters. Ordered chronologically

Sep 2021
Keynote “Virtual screening of large chemical databases with AI”. 4th Annual STRATAGEM (EU Cost Action) conference on “New diagnostic and therapeutic tools against multidrug resistant tumours”
Nov 2019
“Case study 1: Diagnosing Cardiac Amyloidosis Based on MRI”. Jointly with Prof. Bonderman from Cardiology department, Medical University of Vienna. Symposium: Artificial Intelligence in Clinical and Preclinical Settings. Can AI revolutionize medical practice? Medical Univeristy of Vienna, Austria
Oct 2019
“Wet Lab partners with AI to inspect tumor pathways. Hallmarks of cancer in the hyperbolic space”. Cancer Research Institute, Medical University of Vienna, Austria
Jun 2018
“Diagnosing Cardiac Amyloidosis from MRI using a Deep Learning Approach”. Symposium: Data Science for Personalized Medicine, Medical University of Vienna, Austria
Mar 2017
“Biomedical knowledge spaces: handling complexity, uncertainty and incompleteness via graph analysis”. Postdoc interview at Section for AI and Decision Support, Medical University of Vienna, Austria
Jan 2017
“Biomedical knowledge spaces: handling complexity, uncertainty and incompleteness via graph analysis”. Postdoc interview at Informatics department, University of Oslo, Norway
Jun 2015
“Ontology Modularization for Multi-scale Biomedical Data Management and Visualization”. Symposium: 29th International Congress and Exhibition of Computer Assisted Radiology and Surgery (CARS), Barcelona, Spain
Oct 2014
“Collaborative knowledge formalization and visualization: detecting similarities and changes”. Symposium: Festival della Scienza, Genoa, Italy

Cooperation partners

Current

This list includes those partners with whom I have collaborated on manuscripts, such that I and partner assumed the key authorship roles, i.e., I as first-author, and the partner as a corresponding author, and with whom I have a long-term collaboration project that includes joint grant application submission and manuscript preparation. These partners could potentially join a common grant application

Diana Bonderman
(Assoc.-Prof.) Head of Cardiology Department, Kaiser Franz-Joseph Spital, Vienna, Austria/Cardiology department, Medical University of Vienna, Vienna, Austria.
Current cooperation: manuscripts published, manuscript in review, grant application in review
Oliver Kimberger
(Assoc.-Prof.) Anaesthesiology department, Medical University of Vienna, Vienna, Austria/(Co-I) Ludwig Boltzmann Institute Digital Health and Patient Safety.
Cooperation: manuscript in preparation
Ernesto Jiménez-Ruìz
(Lecturer) City, University of London, London, UK/(Researcher) Center for Scalable Data Access (SIRIUS), Oslo, Norway
Cooperation: manuscripts published
Dagmar Gromann
(Assistant-Prof.) Center for Translational Studies, University of Vienna, Austria
Andrea Stocco
(Postdoc) Software Institute, Università della Svizzera italiana (USI), Lugano, Switzerland

Past

This list excludes my previous supervisors

Franz-Erich Wolter
(Full Professor) Head of Man-Machine Communication Institute of Computer Graphics, University of Hanover, Germany
Cooperation: manuscripts published, Marie-Curie ITN consortium members
Joaquim M. Oliveira
(Vice-president) Biomaterials, Biodegradables, Biomimetics (3B’s) Research Group, University of Minho, Braga, Portugal
Cooperation: manuscripts published, Marie-Curie ITN consortium members

Teaching and supervision

WS 2017, WS 2018, WS 2020, SS2022
PhD level: “Basic Lecture Complex Systems & Artificial Intelligence”, 1 ECTS, WS 2017, WS2018 (6%), WS 2020 (12%), PhD program in Medical Informatics, Medical University of Vienna
WS 2017-2022
Master level: “Machine Learning in der Medizin”. LV 840.042 (VU), 2 ECTS, WS 2017-2018 (25%), WS 2019-2022 (50%), Medical Informatics Master, Medical University of Vienna
SS 2019
Master level: “Aktuelle Themen der Medizinischen Informatik - Deep Learning Notebooks”. LV 840.001 (VO), 2 ECTS, SS 2019 (100%), Medical Informatics Master, Medical University of Vienna

In the preparation of my lectures I use the following textbooks

Supervision

SS 2019 – present
Master thesis supervision: “Gradient class activation maps as efficient priors to convolutional neural networks. Applications in cardiac imaging” by Alessa Katherina Stria, Medical University of Vienna
Aug 7, 2020
Invited external committee: for Master thesis “Understanding the Role of Background Knowledge in Predictions” defence by Nils Petter at Informatics Department, University of Oslo
SS 2018
Bachelor thesis supervision: “Visual comparison of activations of pre-trained convolutional neural networks on medical images” by Daiana Crisan, University of Vienna

Teaching assistant

WS 2020
Medecine Doctor level: “SSM1 Medizinische Informationssuche”. Pflichtpraktikum, 0.5 ECTS, Medical University of Vienna
17-19 Sep 2019
PhD level: Training school “Computational methods in MDR research”. STRATAGEM COST Action CA17104 “New diagnostic and therapeutic tools against multidrug resistant tumours”, Vienna, Austria

Esteem factors

Journal Impact Factor (IF) data pulled from the Journal Citation Reports 2020 from Clarivate Analytics

Editorial review board
International Journal of Privacy and Health Information Management (IJPHIM) 2017–present (IF N/A)

Reviewing 2 to 3 submitted papers, taking active part in acceptance/rejection decisions, delegating reviews to external reviewers

Program committee
International Workshop on Neural-Symbolic Learning and Reasoning (NeSy) 2021
Extended Semantic Web Conference (ESWC) Posters and Demos 2017, 2018, 2019
Brain Informatics (BI) 2017

Reviewing activities

Reviewer (journal)
Journal of American College of Cardiology (JACC) 2019, 2020 (IF 20.5)
JACC-Heart Failure 2020 (IF 8.7)
Computers in Biology and Medicine, 2020 (IF 3.4)
Joural of Web Semantics 2019-2022 (IF 2.2)
Reviewer (conference/workshop)
International Semantic Web Conference (ISWC) Posters and Demos 2016
Brain Informatics (BI) 2016
Global Conference on Artificial Intelligence (GCAI) 2017
International Multidisciplinary Conference on e-Technologies (MCETECH) 2017

Memberships and volunteering

Member
European Heart Association, 2018 – 2019
Austrian Society of Cardiology (Österreichische Kardiologische Gesellschaft), 2018 – 2019
Marie Curie Alumni Association Austrian Chapter, 2018 – present
Founding member
Marie Curie Alumni Association in Central Asia Interest Group. Role: organization of events, 2019 – present
Unofficial journal club of “Data Science in clinical practice” at Medical University of Vienna. Role: organization of events, 2018 – present
Student volunteer
Eurographics 2016, 9–13 May, 2016, Lisbon, Portugal
Symposium on Geometry Processing (SGP) 2013, 3–6 July, 2013, Genoa, Italy

Attended Summer Schools

1 ECTS = ~10 hours. Ordered chronologically, latest first

Jul 2017 (3 ECTS)
“International Summer School on Deep Learning (DeepLearn)”, 1300 participants, 3 keynotes, 30 six-hour courses from top AI researchers, 17 – 21 July, 2017, Bilbao, Spain
Jul 2014 (6 ECTS)
“Summer School on Science management for scientists and engineers (SoSMSE)”, Erasmus training program on Innovation and valorization, Spin off, European Patent law, 6 ECTS (60 hours), 7 – 18 July, 2014, Genoa, Italy
Jul 2014 (2 ECTS)
“Regularization Methods for Machine Learning (RegML)”, summer school on reproducing kernel Hilbert spaces, 20 hours of courses, University of Genoa, 30 Jun – 4 July, Genoa, Italy
Jan 2014 (2 ECTS)
“Foundations and Challenges of Change in Ontologies and Databases (FCCOD)”, research school in traditional AI for PhD students and Postdocs, 29 – 31 Januray, 2014, Bolzano, Italy
Jul 2013 (1 ECTS)
“Symposium on Geometry Processing (SGP). Graduate School”, 2 day of courses on geometry processing algorithms, 1 – 2 July, 2013, Genoa, Italy
Mar 2013 (3 ECTS)
“Bertinoro international Spring School (BISS)”, 39 hours of lectures, graduate school for PhD students in Computer Science, 3 – 9 March, 2013, Bertinoro (Forlì-Cesena), Italy