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| COSINE Summer School | |
|---|---|
| Name | COSINE Summer School |
| Established | 2010s |
| Type | International summer school |
| Location | Various (Asia, Europe) |
COSINE Summer School COSINE Summer School is an international intensive program focusing on computational science, numerical methods, and interdisciplinary applications, convening annually for graduate students, postdoctoral researchers, and junior faculty. The program combines lectures, hands-on workshops, and collaborative projects to bridge theory and practice across numerical analysis, high-performance computing, and applied mathematics. Hosted at rotating venues, the school attracts participants and faculty from universities, national laboratories, and research institutes worldwide.
The school offers concentrated modules on algorithms, software engineering, and scientific workflows, integrating topics such as Finite element method, Spectral method, Parallel computing, High Performance Computing, Machine learning, Data assimilation, Computational fluid dynamics, Computational chemistry, and Computational biology. Its format includes plenary lectures, problem sessions, tutorials, and hackathons modeled after programs like Les Houches Summer School, Kellogg School of Management workshops, and SIAM conferences. Lecturers often include faculty from Massachusetts Institute of Technology, Stanford University, University of Cambridge, Princeton University, University of Oxford, and researchers from Lawrence Berkeley National Laboratory, Argonne National Laboratory, Los Alamos National Laboratory, and European Organization for Nuclear Research. Partnerships have linked the school to initiatives at National Science Foundation, Horizon Europe, Japan Society for the Promotion of Science, and industry partners such as NVIDIA, Intel, and IBM.
Founded in the 2010s by a coalition of computational scientists inspired by summer schools like École Polytechnique, CERN Summer Student Programme, and Newton Institute workshops, the program grew from regional meetings in Seoul, Singapore, and Zurich to an international circuit. Early organizers included faculty affiliated with KAIST, The University of Tokyo, ETH Zurich, and University of California, Berkeley, and cooperating laboratories such as Riken and Max Planck Society. Milestones include expansion of curriculum to encompass tensor decomposition methods, incorporation of GPU computing modules following collaborations with NVIDIA Corporation, and formal recognition through grants from European Research Council and foundations associated with Gordon and Betty Moore Foundation.
Curricula are structured around core sequences in numerical linear algebra, time-stepping schemes, and discretization techniques, supplemented by electives on topics such as Monte Carlo method, Markov chain Monte Carlo, Bayesian inference, Inverse problems, Optimization, and Uncertainty quantification. Practical instruction covers software ecosystems like PETSc, Trilinos, TensorFlow, PyTorch, MPI, and OpenMP, with sessions on reproducible research referencing standards promulgated by FAIR data principles advocates and repositories such as GitHub and Zenodo. Course leaders have included scholars with affiliations to Courant Institute of Mathematical Sciences, Imperial College London, University of Toronto, Columbia University, and University of Michigan.
Admissions target doctoral students, postdoctoral fellows, and early-career researchers nominated by supervisors or institutions including Indian Institute of Science, Tsinghua University, Peking University, Seoul National University, University of Melbourne, and University of Sydney. Selection emphasizes research potential, letters of recommendation from faculty at institutions such as Harvard University, Yale University, Duke University, and University of Chicago, and demonstrated interest in computational projects tied to national laboratories like Oak Ridge National Laboratory and Sandia National Laboratories. The cohort size typically ranges from 40 to 120 participants to maintain low student-to-instructor ratios akin to Mathematical Sciences Research Institute programs.
Organization is typically led by a steering committee composed of academics from institutions including École Normale Supérieure, Sorbonne University, University of Edinburgh, and Technical University of Munich, with logistical support from host universities and research centers such as KTH Royal Institute of Technology and Seoul National University. Funding sources have included competitive grants from National Institutes of Health grants for computational biology modules, awards from National Science Foundation, corporate sponsorship from AMD, Google, and travel fellowships funded by Fulbright Program and national scholarship agencies like DAAD and A*STAR.
The summer school fosters collaborative research projects that often continue as joint publications in venues such as Journal of Computational Physics, SIAM Journal on Scientific Computing, Nature Computational Science, and proceedings of conferences like International Conference on Machine Learning, NeurIPS, and SC (Supercomputing) Conference. Collaborative nodes have linked participants to long-term efforts at European Centre for Medium-Range Weather Forecasts, NASA Jet Propulsion Laboratory, European Space Agency, and multinational consortia addressing problems in climate modeling, drug discovery, and materials science. Cross-institutional mentorship sometimes leads to joint grant proposals submitted to Horizon 2020 and US Department of Energy programs.
Alumni have progressed to faculty positions and leadership roles at institutions and organizations such as Massachusetts Institute of Technology, Stanford University, University of Cambridge, Princeton University, Goldman Sachs quantitative research groups, Google DeepMind, OpenAI, and national labs including Lawrence Livermore National Laboratory. Graduates have contributed to high-impact work cited in collaborations with Intergovernmental Panel on Climate Change, open-source projects like SciPy, and initiatives recognized by awards such as the Turing Award and Fields Medal-adjacent computational prizes. The program's network has catalyzed startups and spin-offs in computational platforms, mirroring trajectories seen among alumni of Y Combinator-affiliated incubators and research-focused accelerators.
Category:Summer schools