Dr.

Hassan Errami

Researcher WG Weber
 
Endenicher Allee 19A, Room
D-53115 Bonn
Germany
3.039
Phone: +49 (0) 228 73-54191
Fax: +49 (0) 228 73-4212
Email: errami@REMOVETHISPART.cs.uni-bonn.de

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Courses

Ongoing Projects

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Physically-based analysis and synthesis of (human) motions have a number of applications. They can help to enhance the efficiency of medical rehabilitation, to improve the understanding of motions in the realm of sports or to generate realistic animations for movies and computer games.
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The goal of the project is the anticipation of full body motions. Combining purely data-driven with physics-based modeling approaches, anticipation of full body motions on the basis of very sparse sensor signals of different nature, e.g., inertial measurement units, EMG sensors, or ground-contact sensors, will be realized. Extending the information on the physics-based layer by model-based anticipation components (including information from balance control, physical constraints) is another important objective to allow robust extrapolations from the range of motions similar to ones recorded in an existing knowledge base to new motion ranges, especially those relatedto disabilities. The anticipated whole-body motions can be used to determine the optimal robot placement for collaborative tasks and for direct entrainment and modulation of ongoing motor behavior. Symbolic labels and trajectories from affordances obtained from other projects of the research unit will be incorporated as additional a priori knowledge on motions, which will reduce computations times, will stabilize short term predictions and even open the door for the method to long-term anticipations.
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On this page, we want to introduce you to our research in the field of sonification, partially carried out in cooperation with the Institute of Sport-science and Sports at the University of Bonn and the University of Hannover.
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SYMBIONT is an interdisciplinary project ranging from mathematics via computer science to systems biology and systems medicine. The project has a clear focus on fundamental research on mathematical methods, and prototypes in software, which is in turn benchmarked against models from computational biology databases. Computational models in systems biology are built from molecular interaction networks and rate parameters resulting in large systems of differential equations. These networks are foundational for systems medicine. The currently prevailing numerical approaches shall be complemented with our novel algorithmic symbolic methods, which will address fundamental problems in this area. One important problem is that statistical estimation of model parameters is computationally expensive and many parameters are not identifiable from experimental data. In addition, there is typically a considerable uncertainty about the exact form of the mathematical model itself. The parametric uncertainty (with wide potential variations of parameters by several orders of magnitudes) leads to severe limitations of numerical approaches even for rather small and low dimensional models. Furthermore, extant model inference and analysis methods suffer from the curse of dimensionality that sets an upper limit of about ten variables to the tractable models. For those reasons, the formal deduction of principle properties of large and very large models has a very high relevance. The main goal of SYMBIONT is to combine symbolic methods with model reduction methods for the analysis of biological networks. We propose new methods for symbolic analysis, which overcome the above mentioned obstacles and therefore can be applied to large networks. In order to cope more effectively with the parameter uncertainty problem, we impose an entirely new paradigm replacing thinking about single instances with thinking about orders of magnitude. Our computational methods are diverse and involve various branches of mathematics such as tropical geometry, real algebraic geometry, theories of singular perturbations, invariant manifolds and symmetries of differential systems. The foundations and validity of our methods will be carefully secured by mathematical investigation. Corresponding computer algebra problems are NP-hard, but experiments point at their feasibility for biological networks. We have already shown that complexity parameters such as tree-width or number of distinct metastable regimes grow only slowly with size for models available in existing biological databases. We will exploit this observation to solve challenging problems in network analysis including determination of parameter regions for the existence and stability of attractors, model reduction, and characterization of qualitative dynamics of nonlinear networks. The methods developed in this project will be benchmarked against existing biological models and also against more challenging models, closer to the needs of systems and precision medicine that will be generated using biological pathways databases.

Completed Projects

Publications

 
Qaiser Riaz, Muhammad Zeeshan Ul Hasnain Hashmi, Muhammad Arslan Hashmi, Muhammad Shahzad, Hassan Errami, and Andreas Weber
In: IEEE Access (Mar. 2019), 7:1(28510-28524)
 
Russell Bradford, James Davenport, Matthew England, Hassan Errami, Vladimir P. Gerdt, Dima Grigoriev, Charles Hoyt, Marek Kosta, Ovidiu Radulescu, Thomas Sturm, and Andreas Weber
In: Journal of Symbolic Computation, Elsevier (Jan. 2019)
 
Masa Dukarić, Hassan Errami, Roman Jerala, Tina Lebar, Valery G. Romanovski, János Tóth, and Andreas Weber
In: Reaction Kinetics, Mechanisms and Catalysis (Dec. 2018):11144(1-28)
 
Matthew England, Hassan Errami, Dima Grigoriev, Ovidiu Radulescu, and Andreas Weber
In proceedings of Computer Algebra in Scientific Computing - 19th International Workshop (CASC 2017), Beijing, China, Springer, Sept. 2017
 
Russell Bradford, James Davenport, Matthew England, Hassan Errami, Vladimir P. Gerdt, Dima Grigoriev, Charles Hoyt, Marek Kosta, Ovidiu Radulescu, Thomas Sturm, and Andreas Weber
In proceedings of Proceedings of the 42nd International Symposium on Symbolic and Algebraic Computation (ISSAC '17), Kaiserslautern, Germany, pages 45-52, ACM, July 2017
 
Hassan Errami, Markus Eiswirth, Dima Grigoriev, Werner M. Seiler, Thomas Sturm, and Andreas Weber
In: Journal of Computational Physics (2015), 291(279-302)
 
Suedwestdeutscher Verlag fuer Hochschulschriften, Oct. 2014
 
Dissertation, University of Kassel, Dec. 2013
 
Hassan Errami, Markus Eiswirth, Dima Grigoriev, W. M. Seiler, Thomas Sturm, and Andreas Weber
In proceedings of Computer Algebra in Scientific Computing - 15th International Workshop (CASC 2013), Berlin, Germany, Springer, Sept. 2013
 
 
In proceedings of Dagstuhl Reports, Dagstuhl, Germany, pages 72, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, Mar. 2013
 
Hassan Errami, W. M. Seiler, Markus Eiswirth, and Andreas Weber
In proceedings of Computer Algebra in Scientific Computing - 14th International Workshop (CASC 2012), Maribor, Slovenia, Springer, Sept. 2012
 
Satya Samal, Hassan Errami, and Andreas Weber
In proceedings of Computer Algebra in Scientific Computing - 14th International Workshop (CASC 2012), Maribor, Slovenia, Springer, Sept. 2012
 
Hassan Errami, W. M. Seiler, Thomas Sturm, and Andreas Weber
In proceedings of Computer Algebra in Scientific Computing - 13th International Workshop (CASC 2011), Kassel, Germany, pages 135-143, Springer, Sept. 2011
 
 
N. N. Vassiliev (Editors)
Hassan Errami, Thomas Sturm, and Andreas Weber
In proceedings of Polynomial Computer Algebra, Saint Petersburg, pages 25-28, The Euler International Mathematical Institute, Apr. 2011