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California Institute of Technology (Caltech)

This annual workshop welcomes academics and industry practitioners at the interface of theoretical physics, mathematics, and computer science to discuss research directions centred on the application of machine learning and data science to open problems in fundamental theory, and equivalently the application of techniques from theory to describe the successes of machine learning.

Open Data Science Conference

The ODSC East in-person conference will feature 200+ speakers, instructors, and practitioners, 3,000 of your fellow data scientists, and expert-led, hands-on instruction in in-demand topics and tools, previous included:

NLP | Python | Responsible AI | TensorFlow | PyTorch | Conversational AI | OpenAI | Cybersecurity | Data Visualization | scikit-learn | MLOps | Data Engineering | Machine Learning | and much more

Email: iryna@odsc.com

Data Science, Artificial Intelligence

Institute for Mathematical and Statistical Innovation

Materials informatics is an emerging field defined by the use of simulation tools combined with methods from data sciences and machine learning to better understand materials properties and design innovative materials. The models which are considered cover an extremely wide range, from Schrödinger’s equation, which describes matter at the (sub)atomistic scale, to the equations of continuum mechanics. Mathematical sciences play a key role in materials informatics, both to construct the databases used to train machine learning algorithms (since these databases are made of reference simulation results), and to harness them in order to extract the most relevant information. The aim of this program is bring together a diverse scientific audience, both between scientific fields (physical sciences, materials sciences, biophysics, etc) and within mathematics (mathematical modeling, numerical analysis, statistics and data analysis, etc), to make progress on key questions of materials informatics.

Condensed Matter Physics and Materials,    Metallurgy and Materials Science

Society for Industrial and Applied Mathematics (SIAM)

This conference is co-located with the SIAM Conference on Mathematics of Planet Earth (MPE24). This is the conference of the SIAM Activity Group on Life Sciences. The life sciences have become increasingly quantitative as new technologies facilitate collection and analysis of vast amounts of data ranging from complete genomic sequences of organisms to satellite imagery of forest landscapes on continental scales. As a consequence, mathematics and computational science have become crucial technologies for the study of complex models of biological processes.

Society for Industrial and Applied Mathematics (SIAM)

Simons Laufer Mathematical Sciences Institute (SLMath)

In a growing number of applications, one needs to analyze and interpret data coming from massive networks. The statistical problems arising from such applications lead to important mathematical challenges: building novel probabilistic models, understanding the possibilities and limitations for statistical detection and inference, designing efficient algorithms, and understanding the inherent limitations of fast algorithms. The workshop will bring together leading researchers in combinatorial statistics, machine learning, and random graphs in the hope of cross-fertilization of ideas.

combinatorial statistics, random graphs, network inference, network reconstruction, detection, estimation

Complex Networks,    Graph Theory and Combinatorics