Welcome!

This is the web site for the thesis course 732A67 in the master's programme Statistics and Machine Learning (which previously hade the code 732A64).
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 Fall 2026 course

Date	Activity	Material
August 11	Deadline for sending in project descriptions to Frank.
August 18	Approval of thesis topic.
August 21 or earlier	Appointment of supervisor.	Project List
August 25	Introductory meeting at 13:15-15:00 in John von Neumann, B building.	Slides
September 10	Submitting the thesis proposal presentation to LISAM.
September 14	Thesis proposal seminar. In Alan Turing, E building.	Schedule
October 14	Submitting the midterm presentation and supporting report to LISAM.
October 20	Mid-term seminar.  In John von Neumann, B building.	Schedule
November 20	Sending a thesis draft to the supervisor unless the supervisor states otherwise.
November 27	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 2	Sending a thesis draft to the opponent, examiner and supervisor.
December 9, 10 or 11	Revision meeting. Mandatory, but date and place are decided in agreement between the student, opponent, supervisor and examiner.
January 4, 2027	Submission of the close-to-final thesis to LISAM. This version will be controlled for plagiarism. Send it also to the supervisor, examiner and opponent by email.
January 11, 2027	Submission of the presentation for the oral defense to LISAM.
January 12, 2027	Oral defense seminar. In John von Neumann, B building.
January 18, 2027	Last day to submit final version of the thesis for it to be reported within this semester.
January 25, 2027	Examiner's meeting where the grades are decided and then reported.
March 19, 2027	Last attempt for submitting the final version of the thesis (for students who become delayed; the maximum possible grade is C).
June, 2027	Second opportunity for the oral defense seminar (for students who become delayed).

Timetable for the Spring 2026 course

Date	Activity	Material
October 20, 2025	Preparatory meeting at 10.15 in Alan Turing, Key-house
December 21, 2025	Deadline for sending in project descriptions to Oleg.
January 9, 2026	Approval of the thesis topic
January 16	Appointment of the supervisor	Project List
January 20	Introductory meeting. At 10.15 in Alan Turing, E-house	Slides
February 2	Submitting thesis proposal presentation to LISAM
February 6 and 9	Thesis proposal seminar: February 6: Group A in Alan Turing, E-house; Group B in John von Neumann, B-house February 9: Group A in Donald Knuth, B-house, Group B has no sessions that day	Schedule for group A Schedule for group B
March 15	Submitting the midterm presentation plus progress report plus thesis text sample to LISAM
March 23-24	Mid-term seminar: March 23: Group B in John von Neumann, B-house; March 24: Group A in John von Neumann, B-house, Group B in Alan Turing, E-house	Schedule for group A Schedule for 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 complete thesis draft (it may not contain any missing part) to the opponent, examiner and supervisor by email
May 11 or 12 or 13	Revision meeting. Mandatory, but the concrete date and place is to be negotiated between the student, opponent, examiner and supervisor
May 24	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: June 3: Group A in John von Neumann, B-house; Group B in Alan Turing, E-house June 4: Group A in John von Neumann, B-house, Group B in Charles Babbage, B-house June 5: Group B in Alan Turing, E-house	Schedule for group A Schedule for group B
June 9	Last day to submit final version of the thesis for it to be reported within this semester
June 18	Examiner's meeting where the grades are decided and then reported
August, 2	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, 2027	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.

Letter to company collaborators

- Letter

Proposed projects start Spring 2027

Internal, at IDA:

Link for projects in Spring 2027

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