PhD 2013 – 2017, PostDoc 2017 – present, h-index 8, 120 citations (source: Google Scholar, as of Mar 2021)
- Publication track record
- 10 original research journal articles, 4 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: 4 journals (1 as first), funding: ~15,000 Euro
RA2: Neuro-symbolic embeddings (2017–present), published: 4 journals (2 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):
- High-performance computing: Linux/Unix CLI toolchains, SLURM scheduler,
dask (Python, distributed ML/DL)
- Web development:
Flask (Python, backend),
- Native: Russian and Kyrgyz
- Fluent: English (C2), French (C2), Italian (C1)
- Basic University level: German (B1), Turkish (A2)
- CNR-IMATI1 : Institute of Applied Mathematics and Information Technologies, Italian National Council of Research
- INRIA2 : French Institute for Research in Computer Science and Automation
- 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”
- CeMSIIS-AID 1: Center for Medical Statistics, Informatics and Intelligent Systems (CeMSIIS), Institute of Artificial Intelligence and Decision Support
- CNR-IMATI 2: Institute of Applied Mathematics and Information Technologies, Italian National Council of Research
- INRIA 3: French Institute for Research in Computer Science and Automation
- MOAÏS 4: prograMming and scheduling design on distributed resOurces for Applications based on Interactive Simulation
- Jun 2017 – Jun 2022
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.
publications since 2014 thematically organized according to the research avenues (see also 1 page)
Journal Impact Factor (IF) data pulled from the Journal Citation Reports 2020 from Clarivate Analytics
RA1. Clinical prediction models (2017–present)
- ML and DL models for the prediction of patient clinical outcomes
- 4 journals (1 as first) published
[J.1] 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.2] 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.3] 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.4] 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 4.8
- 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.” Eur. Heart Journal: Cardiovascular Imaging: Under review since 2020.
RA2. Neuro-symbolic embeddings (2017–present)
- Merging symbolic and deep learning (neural) technologies to learn latent graph and text representations (embeddings)
- 4 journals (2 as first) published
- 5 conference/workshop (3 as first) published
[CW.1-5] (see below)
[J.5] 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.6] 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.7] 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.8] 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
- IF 5.9
- Agibetov, Asan. 2020. “Graph embeddings via matrix factorization: Truncating or smoothing negatives?” Journal of Information Sciences: Under review since July 2020.
- available on arXiv https://arxiv.org/abs/2011.09907
RA3. Virtual Physiological Human (PhD, 2013–2017)
- Multi-modal data integration, visualization and processing for advanced understanding of musculoskeletal diseases, e.g., osteoarthritis
- 2 journals (1 as first) published
- 7 conference/workshop (5 as first) published
[CW.6-12] (see below)
[J.9] 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.10] 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.
- All listed papers were peer-reviewed by at least 2 reviewers and presented at international venues
- Ordered chronologically, latest first
- 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).
- 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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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
- 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
- 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
Excluding accepted conference/workshop papers and posters. Ordered chronologically
- 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
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
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/SS 2017 - Winter/Summer semester of academic year 2017/2018
- Teaching material contribution in %, e.g., SS 2017 (25%) - prepared 25% of lectures/exercises/exam questions in summer semester 2017/2018
- WS 2017, WS 2018, WS 2020
- 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, WS 2018, WS 2019, WS 2020
- Master level: “Machine Learning in der Medizin”. LV 840.042 (VU), 2 ECTS, WS 2017, WS 2018 (25%), WS 2019, WS2020 (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
- Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. 2016. Deep learning. MIT Press.
- Strang, Gilbert. 2019. Linear algebra and learning from data. Cambridge University Press.
- Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. 2009. The elements of statistical learning 2nd edition. Springer series in statistics. Springer New York Inc.
- Nielsen, Michael A. 2018. “Neural networks and deep learning.” Determination Press.
- SS 2019 – WS 2020
- 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
- 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
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) 2020
- Extended Semantic Web Conference (ESWC) Posters and Demos 2017, 2018, 2019
- Brain Informatics (BI) 2017
- 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, 2020 (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
- 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