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table of proposed coding projects
This year contributors will have to choose between a ~175 hours medium-sized project or ~350 hours large project. For all the changes that GSoC 2022 brings refer to the official website.
Mentors, please edit this wiki page, and add your ideas to the table below.
Contributors, please look for a project that interests you in the table below. Before emailing project mentors, please do at least one project test and post a link to your solution on the proposal's wiki page.
Proposal | Mentors | Languages | Hours |
---|---|---|---|
MENTORS-COPY-THIS-TEMPLATE | |||
Simulated Annealing for high dimensional log-concave sampling | V Fisikopoulos, M Papachristou, E Tsigaridas | C++ | 350 |
Randomized SDP solver | E Tsigaridas, V Fisikopoulos, A Chalkis | C++/R | 350 |
Sampling with Riemannian Hamiltonian Monte Carlo | A Chalkis, V Fisikopoulos, M Papachristou | C++/Matlab | 350 |
Exclude Lpsolve from R and C++ interfaces of volesti | Z Zafeirakopoulos, M Christoforou, A Chalkis | C++/R | 350 |
Counting linear extensions with volume computation | V Fisikopoulos, E Tsigaridas, M Bender | C++ | 350 |
A comparative study of uniform high-dimensional samplers | A Chalkis, M Papachristou, E Tsigaridas | C++/R | 175 |
Sampling correlation matrices | V Arakelian, A Chalkis | C++ | 175 |
Automatic differentiation support in volesti | M Papachristou, E Tsigaridas | C++ | 175 |
Building an R interface to use volesti for financial applications | C Bachelard, A Chalkis, V Fisikopoulos, E Tsigaridas | R | 175 |
Memory allocation in facet redundancy removal in dingo | A Chalkis, V Fisikopoulos, E Tsigaridas | Python | 175 |
Expose random walk C++ implementations in dingo | A Chalkis, V Fisikopoulos, E Tsigaridas | C++/Python | 175 |
All contributor applications will be discussed by the GeomScale mentor community, and proposals will be ranked considering factors such as quality, contributor's ability to successfully finish the project, and impact for the GeomScale project. A finite number of slots will be granted to GeomScale by Google, thus, only the best proposals will get chosen. This implies that it is possible that some ideas will not become GSoC projects even if they are supported by a good contributor application.
Contributors, if you are interested in a coding project related to GeomScale that is not listed above, please try to find mentors by posting a description of your project idea on the gitter. If you find mentors, feel free to add your project idea to this wiki and write an application.
The application process has several steps. Before contacting anybody verifies that you are eligible. The next step is to contact the mentor of the project you are interested in. You have to convince him that you are the right person to get the job done. The next step is to work out more details and to contact the mentors or the GeomScale org by providing the following information by email or by gitter.
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Project:
- Select a project in the list and provide your personal and detailed description. If you wish to work on another idea of your own, we are pretty open as long as this serves the goal of consolidating GeomScale as a whole.
- Provide a proposal of a technical solution with your envisioned methodology. The more detailed the better.
- Explain how the solution will be available to the user, in which form. Do not forget the documentation, unitary tests, and cross-platform aspects.
- Provide a realistic schedule with objectives (one every two weeks for example) and deadlines. Focus on mid-term objectives as well as on the final evaluation.
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Personal data:
- First name, last name, affiliation, and geographical location.
- A brief list of the main studies and programming courses attended, with ranking.
- List of the most important software projects contributed and success.
- Which are your best skills in terms of programming and scientific computing?
- In general what is your taste in terms of programming? language, methodology, teamwork, etc.
- Is there anything that prevents you from working full time on the project during the program period?
- How do you see your involvement after the program ends? Do you see yourself pushing the project further, or do you see yourself contributing to other GeomScale projects?
- Are you more interested in the theory/scientific aspect of GeomScale, or do you feel more like a hacker?
STUDENT 1 AGILAN S, https://github.com/Agi7an, https://github.com/Agi7an/VolEsti/blob/main/setup.r
STUDENT 2 Ioannis Iakovidis, https://github.com/iakoviid/, https://github.com/iakoviid/volesti/tree/gsoc2022
STUDENT 3 HUSSAIN LOHAWALA, https://github.com/H9660/Volesti-/blob/main/setup.r
STUDENT 4 Huu Phuoc Le, https://github.com/huuphuocle, https://github.com/huuphuocle/sampling_correlation_matrices