Konferenzen zum Thema Angewandte Mathematik (allgem.) in Singapur

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1
Computational Approaches to the Analysis of Biomolecular Sequences, Structures and Their Functions and Applications to Biotechnology and Clinical Data Studies
23. Mär 2020 - 27. Mär 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
Any biological function is a result of the evolutionary trade-off, where sequences provide a foundation for evolutionary variability and natural selection on the basis of the fitness and efficacy of corresponding structures and functions. In-depth understanding of biomolecules would ultimately allow one to aim at engineering and design of desired biological activities. The ease and speed at which sequence and structure data are obtained nowadays do not only prompt researches to integrate experimental and computational tools, but also force them to challenge existing concepts, driving experimental biology towards more quantitative realms. Omics technologies, in turn, deliver a wealth of exponentially growing high-throughput data, which becomes a must in medical practice. Therefore, there is a strong need for development of theoretical models and computational frameworks for the analysis and crosslinking the omics outputs with clinical data, and for further use it in biomedical applications. The goal of this workshop is to cover some of the important topics on theoretical modelling and simulations of biomolecular evolution, protein sequence and 3D structure, and the dynamical relationship with biomolecular function and how to use them to bridge the gap to phenotype and clinical application.
Eintrags-ID:
1240624
2
Combinatorial Problems for String and Graph and Their Applications in Bioinformatics
30. Mär 2020 - 24. Apr 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
Combinatorics is a branch of mathematics concerning the study of finite or countable discrete structures. It finds applications in various domains. In particular, due to advances in biotechnology, applications in biology and medical research have increased, many of which arose from the study of bio-molecular sequences and their interaction. This program aims to investigate the combinatorial problems in strings and graphs and their applications in biological science, hoping to explore new ideas and techniques in analyzing these big datasets.
Eintrags-ID:
1240612
3
Causal Inference with Big Data
29. Jun 2020 - 10. Jul 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
Causal inference is the study of quantifying whether a treatment, policy, or an intervention, denoted as A, has a causal effect on an outcome interest, denoted as Y. What distinguishes a causal effect of A on Y from an associative effect of A on Y, say by computing the correlation between A and Y, is that under a causal effect, intervening on the treatment A leads to changes in the outcome Y. Hence, a causal effect is a stronger notion of a relationship between A and Y than an associative effect.
Eintrags-ID:
1240664
4
Data Stream Algorithms
13. Jul 2020 - 21. Jul 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
The more data we have, the more data we need to process. Whether it is internet traffic or biological data, the hardware is never fast enough. The aim of this workshop is to focus on analysing data under new models: when the data cannot be stored (e.g., identifying viruses in the Internet traffic), when we use multiple cores to analyse the data, and when we are generating short sketches of the data to be sent and analysed by someone else. We believe a new set of algorithmic techniques (which rely mostly on statistics and on data structures) can be used in these models, and wish to find such techniques and employ them. An important focus of this workshop is to find algorithms which are elegant, and thus can also be used in practice. To develop these algorithms, it is critical to connect the key subareas of algorithmic research on big data. These key subareas include streaming, sketching, and sampling. The goal of the workshop is to bring researchers together from these different sub-areas and to establish strong collaborations among the attendees.
Eintrags-ID:
1240729
5
Optimization in the Big Data Era
03. Aug 2020 - 28. Aug 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
The field of optimization has undergone tremendous growth in its applications in science, engineering, business and finance in the past few decades. The growth has accelerated in recent years with the advent of big data analytics where optimization forms the core engine for solving and analyzing the underlying models and problems of extracting meaningful information from available data for the purpose of better decision making or getting better insights into the data sources. Spurred by the application needs and motivated by new emerging models in machine learning and data analytics, optimization research (in theory and algorithms) has also undergone rapid transformation and progress in recent years. In particular, demands for fast algorithms to solve extremely large-scale optimization problems arising from big data analytics have spurred numerous exciting new research directions in optimization theory and algorithms. The latter in turn helps to shape the development of optimization models and techniques in machine and statistical learning.
Eintrags-ID:
1240651
6
22nd International Conference on Formal Engineering Methods
02. Nov 2020 - 06. Nov 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Eintrags-ID:
1240681
7
International Workshop on Reduced Order Methods
17. Mai 2021 - 21. Mai 2021 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
This is a one-week program gathering mathematicians, engineers, and scientists interested in reduced order models and methods (ROMs) for systems of partial differential equations. The general idea behind ROMs is to derive a low-dimensional model from a high-dimensional model, by integrating techniques from data science, modeling, and simulation, in order to obtain accurate and reliable results at greatly reduced computational costs.
Eintrags-ID:
1240829


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Stand vom 18. Juni 2019