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732A64 Master's Thesis

Course information

Welcome!

This is the web site for the thesis course in the master's programme Statistics and Machine Learning.
We have posted some useful information and material below. This is the only course webpage to keep track of during this course.


Timetable for the Spring 2025 course

Date Activity Material
October 9, 2024
Preparatory meeting at 10.15 in KY23, Key-house

December 20, 2024
Deadline for sending in project descriptions to Oleg.
January 9, 2025
Approval of the thesis topic

January 16 Appointment of the supervisor
January 17 Introductory meeting. At 15.15 in Alan Turing, E-house

January 31 Submitting thesis proposal presentation to LISAM
February 5-6
Thesis proposal seminar in Alan Turing (group A) and John von Neumann (group B).

March 13 Submitting the midterm presentation plus progress report plus thesis text sample to LISAM
March 20-21
Mid-term seminar in Alan Turing (group A) and John von Neumann (group B).

April 24 Sending a thesis draft to the supervisor by email unless the supervisor states otherwise.
April 30 Decision is made by the supervisor regarding whether the thesis has
good chances to be passed within the course time frames or
the thesis work needs to be stopped and grade F given.

May 4 Sending a thesis draft to the opponent, examiner and supervisor by email
May 12 or 13 or 14
Revision meeting. Mandatory, but date and place are set bilaterally selected pairs of students.
May 25 Submission of the close-to-final thesis to LISAM. This version will be controlled for the plagiarism. Send it also to the supervisor, examiner and opponent by email

June 2 Submission of the presentation for the oral defense to LISAM
June 3 - June 5
Oral defense seminar in Alan Turing (group A) and John von Neumann (group B).
June 9
Last day to submit final version of the thesis for it to be reported within this semester

June 17 Examiner's meeting where the grades are decided and then reported
August, 4 Last attempt for submitting the final version of the thesis
(for students who passed all obligatory moments except of June 9 submission; the maximum possible grade is C)

January, 2026 Second opportunity for the oral defense seminar (for students who passed all obligatory moments except of  defense)

Bold means that the entire meeting is mandatory. If a group is indicated, the entire meeting is mandatory for students from this group.
Note that LiU makes use of academic quarters.
All deadlines specified refer to the latest time point 23:59.



Timetable for the Autumn 2024 course

Date Activity Material
August 9
Deadline for sending in project descriptions to Frank.
August 14
Approval of thesis topic.

August 20 or earlier Appointment of supervisor.
August 21 Introductory meeting at 10.15 in John von Neumann, B building.
Slides
September 9 Submitting the thesis proposal presentation to LISAM.
September 13
Thesis proposal seminar. In John von Neumann, B building. Schedule
October 18 Submitting the midterm presentation and supporting report to LISAM.
October 24
Mid-term seminar.  In John von Neumann, B building.
Schedule
November 22 Sending a thesis draft to the supervisor unless the supervisor states otherwise.
November 29 Decision is made by the supervisor regarding whether the thesis has
good chances to be passed within the course time frames or
the thesis work needs to be stopped and grade F given.

December 4 Sending a thesis draft to the opponent, examiner and supervisor.
December 11, 12 or 13 Revision meeting. Mandatory, but date and place are decided in agreement between the student, opponent, supervisor and examiner. Opponents for theses
January 5, 2025
Submission of the close-to-final thesis to LISAM. This version will be controlled for the plagiarism.
Send it also to the supervisor, examiner and opponent by email.

January 12, 2025 Submission of the presentation for the oral defense to LISAM.
January 13, 2025 Oral defense seminar. In John von Neumann, B building.
January 20, 2025
Last day to submit final version of the thesis for it to be reported within this semester.
January 27, 2025 Examiner's meeting where the grades are decided and then reported.
March 21, 2025 Last attempt for submitting the final version of the thesis
(for students who become delayed; the maximum possible grade is C).

June, 2025 Second opportunity for the oral defense seminar (for students who become delayed).

Bold means that the meeting is mandatory.
Note that LiU makes use of academic quarters.
All deadlines specified refer to the latest time point 23:59.


Letter to company collaborators

- Letter


Proposed projects start Spring 2025

Internal, at IDA:

Link for projects in Spring 2025


Templates and instructions for the report

For the templates, and the publication rules, see here


Examples of theses from previous years (grade A or B)

2020-2022

Can be found here

Older theses:

2017

Caroline Svahn, Automated Bug Report Routing

Andrea Bruzzone,P-SGLD: Stochastic Gradient Langevin Dynamics with control variates

Aleksey Shipitsyn, Statistical Learning with Imbalanced Data

2016

Alessandro Olivi, Survival analysis of gas turbine components

Malte Nalenz, Horseshoe RuleFit - Learning Rule Ensembles via Bayesian Regularization

Konstantinos Poulakis, Alzheimer's disease heterogeneity assessment using high dimensional clustering techniques

Claudia Adok, Retrieval of Cloud Top Pressure

Miriam Hurtado Bodell, Bayesian poll of polls for multi-party systems

2015

Patrik Pavlov, Optimal Experimental Design and Parameter Estimation of a Stacked Bed Hydrotreating Process

Martin Arvidsson, Dynamic Call Drop Analysis

Andreea Bocancea, Supervised Classification Leveraging Refined Unlabeled Data

2014

Aiswaryaa Viswanathan, Data driven analysis of usage and driving parameters that affect fuel consumption of heavy vehicles

Munezero Parfait, Mobile network traffic analysis based on IP log data

Uriel Chareca, Inferring user demographics from reading habits

Paolo Elena, Anomaly detection and analysis on dropped phone call data

2013

Lotta J rvstr t, Functionality Classification Filter for Websites

2012

Ankita Garg, Forecasting exchage rates using machine learning models with time-varying volatility


Page responsible: Oleg Sysoev
Last updated: 2024-12-03