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Department of Information Technology

'Project in Computational Science'

Fall, 2017: Schedule

Course room: 1246

Please note, that occasions marked by '(*)' are compulsory for the participants of the particular project
and occasions marked by '(**)' are compulsory for all course participants.

Date Time Place Contents Lecturer/Coordinator
27.10 14:45-16:00 1406 Meeting, Project 8-1,8-2 Supervisors, students, course coordinator
30.10 9:00-11:00 1406 Meeting, Project 1-1,1-2 Supervisors, students, course coordinator
30.10 13:15-14:15 1406 Meeting, Project 3 Supervisors, students, course coordinator
30.10 15:00-16:00 1406 Meeting, Project 5 Supervisors, students, course coordinator
31.10 13:15-14:15 1406 Meeting, Project 13 Supervisors, students, course coordinator
31.10 14:30-15:30 1406 Meeting, Project 15 Supervisors, students, course coordinator
1.11 10:15-11:15 2414b Meeting, Project 11 Supervisors, students, course coordinator
1.11 15:15-16:15 2414b Meeting, Project 18 Supervisors, students, course coordinator
2.11 10:15-11:15 2414b Meeting, Project 16 Supervisors, students, course coordinator
30.11 14:15-16:00 1211 Poster presentation techniques(**) Elisabeth Långström
1.12 10:15-12:00 1211 Oral presentation techniques(**) Kristina Lund
11.12 8:30- 9:55 2414b Project 3, Oral presentation training (*) Kristina Lund, Course coordinator
11.12 10:15-11:20 2414b Project 1-1, Oral presentation training (*) Kristina Lund, Course coordinator
11.12 11:20-12:25 2414b Project 1-2, Oral presentation training (*) Kristina Lund, Course coordinator
11.12 13:20-14:25 2414b Project 8-1, Oral presentation training (*) Kristina Lund, Course coordinator
11.12 14:30-15:35 2414b Project 8-2, Oral presentation training (*) Kristina Lund, Course coordinator
12.12 8:30- 9:55 2414b Project 15, Oral presentation training (*) Kristina Lund, Course coordinator
12.12 10:15-11:20 2414b Project 16, Oral presentation training (*) Kristina Lund, Course coordinator
12.12 11:20-12:25 2414b Project 13, Oral presentation training (*) Kristina Lund, Course coordinator
13.12 9:15-10:30 2347 Results of computations: communication and responsibility (some ethical aspects) Stefan Engblom
13.12 10:45-12:00 2347 On the use of English language. Writing a scientific report, some requirements Maya Neytcheva
15.12 8:30- 9:55 2414b Project 5, Oral presentation training (*) Kristina Lund, Course coordinator
15.12 10:30-11:55 2414b Project 11, Oral presentation training (*) Kristina Lund, Course coordinator
15.12 13:15-14:20 2414b Project 18, Oral presentation training (*) Kristina Lund, Course coordinator

January, Final presentations(**)

Date Time Place Contents Participants
8.01 14:15-14:45 4308 Mounting of the posters (**) All course participants
8.01 14:50-15:30 4308 Poster presentation session and 'Best poster' award (**) All course participants
9/01 08:55-09:00 2446 Opening (**) All students and supervisors
9/01 09:00-09:20 2446 Project 1-1 Pattern matching with neural networks for the PANDA experiment (Part 1)(**) All students and supervisors
9/01 09:20-09:40 2446 Project 1-2 Pattern matching with neural networks for the PANDA experiment (Part 2) (**) All students and supervisors
9/01 09:40-10:10 2446 Project 3 Network sampling in epidemiological simulations(**) All students and supervisors
10:10-10:25 Break
9/01 10:25-10:55 2446 Project 11 Microsoft Azure machine learning for data based modeling (**) All students and supervisors
9/01 10:55-11:15 2446 Project 8-1 Function-based Algebraic Multigrid method (Part 1) [**] All students and supervisors
9/01 11:15-11:35 2446 Project 8-2 Function-based Algebraic Multigrid method (Part 2) (**) All students and supervisors
9/01 11:35-11:55 2446 Project 13 Black Box Time Series Modeling (**) All students and supervisors
11:55-13:15 Lunch
9/01 13:15-13:45 2446 Project 5 Numerical studies of singularities in the vortex patch problem (**) All students and supervisors
9/01 13:45-14:15 2446 Project 15 Visualization of spatiotemporal data in immersive Virtual Reality (**) All students and supervisors
9/01 13:45-14:30 2446 Project 16 Black box variational inference as a solution for the smoothing problem via machine learning methods (**) All students and supervisors
9/01 14:35-14:55 2446 Project 18 Solving the heat equation in a rolling mill (**) All students and supervisors

31.01, Finalizing the project reports(**)

Updated  2018-01-02 17:39:58 by Maya Neytcheva.