Research Interests and background
Abdel Aziz Taha is a senior researcher at the Data Science Studio. He received his PhD in Data Science (with distinction) from the Vienna University of Technology (TU Vienna) in 2015 and was nominated for the GI (Gesellschaft für Informatik) award for the best dissertation 2015 https://dl.gi.de/handle/20.500.12116/4410. The dissertation of Abdel Aziz Taha offers solutions for problems in the analysis of large data under extreme conditions, such as handling metric distortions and enabling highly efficient computation of complex data as well as data with very high dimensionalities . Within the framework of the Research Studio Austria, Abdel Aziz Taha has been involved in research and development projects in the field of machine learning, including genomics, medical diagnostics, fraud detection, industrial automation, anomaly detection and prediction, and large data marketing.
His experience in data analysis covers all areas, from problem analysis in companies, to data selection, reprocessing and aggregation, to modelling, reconciliation and evaluation, as well as interpretation and drawing conclusions for decisions at the company level. In addition to his teaching activities, Abdel Aziz Taha gained 12 years of professional experience in software engineering, ranging from low-level, embedded and real-time systems to application software, covering the entire software development life cycle in the private sector.
Experience
- 2017 - current: Senior researcher at Research Studios Austria (RSA) and lecturer at TU Wien
- 2012 - 2016: Senior researcher and lecturer at the Vienna University of Technology (TU Wien)
- 2000 - 2017: Software engineering in various industrial projects
- 1997 - 2000: Electrical engineer in automated industry
Publications
(For a more complete publication list, please see
scholar Abdel Aziz Taha)
2020
- Adam Hilbert, Vince I Madai, Ela M Akay, Orhun U Aydin, Jonas Behland, Jan
Sobesky, Ivana Galinovic, Ahmed A Khalil, Abdel A Taha, Jens Würfel,
Petr Dusek, Thoralf Niendorf, Jochen B Fiebach, Dietmar Frey, and Michelle Livne.
BRAVE-NET: Fully automated arterial brain vessel segmentation in patients with
cerebrovascular disease. medRxiv, 2020.
2019
- Michelle Livne, Jana Rieger, Orhun Utku Aydin, Abdel Aziz Taha, Ela Marie Akay,
Tabea Kossen, Jan Sobesky, John D. Kelleher, Kristian Hildebrand, Dietmar Frey,
and Vince I. Madai. A u-net deep learning framework for high performance vessel
segmentation in patients with cerebrovascular disease. Frontiers in Neuroscience,
13:97, 2019.
2018
- Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko
Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron
Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken,
Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März,
Oskar Maier, Klaus H. Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F.
Neher, Wiro Niessen, Nasir M. Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana,
Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der
Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin,
and Annette Kopp-Schneider. Is the winner really the best? A critical analysis
of common research practice in biomedical image analysis competitions. CoRR,
abs/1806.02051, 2018.
3/5
- Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko
Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron
Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken,
Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März,
Oskar Maier, Klaus Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher,
Wiro Niessen, Nasir Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie
Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen,
Ching Wei Wang, Marc André Weber, Guoyan Zheng, Pierre Jannin, and Annette
Kopp-Schneider. Why rankings of biomedical image analysis competitions should
be interpreted with care. Nature Communications, 9(1), December 2018.
2017
- Abdel Aziz Taha, Florina Piroi, Allan Hanbury, Thomas Troppe, Thomas Mutzl,
and Haroun Shehata. Message ranking in a factory setting using context and user
preference. In 22nd IEEE International Conference on Emerging Technologies and
Factory Automation, ETFA 2017, Limassol, Cyprus, September 12-15, 2017, pages
1–4. IEEE, 2017.
- Abdel Aziz Taha and Allan Hanbury. Evaluation metrics for medical organ segmentation
and lesion detection. In Cloud-Based Benchmarking of Medical Image
Analysis, pages 87–105, Cham, 2017. Springer International Publishing.
2017
- Oscar Alfonso Jimenez del Toro, Henning Müller, Markus Krenn, Katharina Gruenberg,
Abdel Aziz Taha, Marianne Winterstein, Ivan Eggel, Antonio Foncubierta-
RodrÃguez, Orcun Goksel, Andras Jakab, Georgios Kontokotsios, Georg Langs,
Bjoern H. Menze, Tomas Salas Fernandez, Roger Schaer, Anna Walleyo, Marc André
Weber, Yashin Dicente Cid, Tobias Gass, Mattias P. Heinrich, Fucang Jia,
Fredrik Kahl, Razmig Kéchichian, Dominic Mai, Assaf B. Spanier, Graham Vincent,
Chunliang Wang, Daniel Wyeth, and Allan Hanbury. Cloud-based evaluation of
anatomical structure segmentation and landmark detection algorithms: Visceral
anatomy benchmarks. IEEE Trans. Med. Imaging, 35(11):2459–2475, 2016.
2015
- 2015 Abdel Aziz Taha and Allan Hanbury. Metrics for evaluating 3d medical image
segmentation: analysis, selection, and tool. BMC Medical Imaging, 15(1):1–28,
- Abdel Aziz Taha and Allan Hanbury. An efficient algorithm for calculating the exact
Hausdorff distance. Pattern Analysis and Machine Intelligence, IEEE Transactions
on, 37(11):2153–2163, Nov 2015.
- Abdel Aziz Taha. Addressing metric challenges: Bias and Selection - Efficient Computation
- Hubness Explanation and Estimation. PhD thesis, Vienna University of
Technology, December 2015. http://publik.tuwien.ac.at/files/PubDat_247742.pdf.
- Henning Müller, Katharina Grünberg, Marc Andre Weber, Oscar Alfonso Jimenez del
Toro, Orcun Goksel, Bjöern Menze, Georg Langs, Ivan Eggel, Markus Holzer, Georgios
Kontokotsios, Markus Krenn, Roger Schaer, Abdel Aziz Taha, Marianne Winterstein,
and Allan Hanbury. Visceral-visual concept extraction challenge in radiology :
segmentation challenge : overview, insights and preliminary results. Proceedings of
the 9th European Congress of Radiology (ECR) 2015, (CONFERENCE):1 p., 2015.
4/5
- Katharina Gruenberg, Marc André Weber, Oscar Alfonso Jimenez del Toro, Orcun
Goksel, Bjoern Menze, Henning Müller, Georg Langs, Ivan Eggel, Markus Holzer,
Georgios Kontokotsios, Markus Krenn, Roger Schaer, Abdel Aziz Taha, Marianne
Winterstein, and Allan Hanbury. Visceral-visual concept extraction challenge in
radiology: Segmentation challenge: overview, insights and preliminary results. In
European Congress of Radiology (ECR) 2015, Vienna, Austria, 2015.
- Orcun Göksel, Oscar Alfonso Jimenez-del Toro, Antonio Foncubierta-RodrÃguez,
and Henning Müller. Overview of the visceral challenge at isbi 2015. In OrÃgun
Göksel, Oscar Alfonso Jimenez-del Toro, Antonio Foncubierta-RodrÃguez, and
Henning Müller, editors, Proceedings of the VISCERAL Anatomy Grand Challenge
at the 2015 IEEE International Symposium on Biomedical Imaging (ISBI), New
York, NY, May 2015.
2014
- Abdel Aziz Taha, Allan Hanbury, and Oscar Jimenez. A formal method for selecting
evaluation metrics for image segmentation. In Image Processing (ICIP), 2014 IEEE
International Conference on, pages 932–936, Oct 2014.
- Oscar Alfonso Jimenez del Toro, Orcun Goksel, Bjoern Menze, Henning Müller,
Georg Langs, Marc André Weber, Ivan Eggel, Katharina Gruenberg, Markus Holzer,
Andras Jakab, Georgios Kontokotsios, Markus Krenn, Tomas Salas Fernandez, Roger
Schaer, Abdel Aziz Taha, Marianne Winterstein, and Allan Hanbury. Visceral -
visual concept extraction challenge in radiology: Isbi 2014 challenge organization.
In Orcun Goksel, editor, Proceedings of the VISCERAL Challenge at ISBI, number
1194 in CEUR Workshop Proceedings, pages 6–15, 2014.
2013
- Abdel Aziz Taha. The EvaluateSegmentation Tool: An efficient tool for evaluating
3d medical segmentation using 20 evaluation metrics. https://github.com/Visceral-
Project/EvaluateSegmentation, 2013.
For a more complete publication list, please see
scholar Abdel Aziz Taha