Defenses in 2022/2023
Defended theses
Submission of Master's Thesis: 1 electronic copy named firstname_lastname.pdf to ltms_kantselei@ut.ee
Submission deadlines:
For defense on January 26 2023: January 16 2023
For defense in June 2023 (7-13): May 16 2023
Additional defenses in the spring semester 2022/2023
June 20 2023, submission June 6 2023
August 30 2023, submission August 20 2023
Theses that reach the recipient's mailbox no later than 11:59 p.m. on the day of submission are considered submitted by the deadline. NB! All theses submitted will receive a reply within the next working day; if there is no answer, write to ltms_kantselei@ut.ee.
The presentation materials must be checked and uploaded to the computer in the defense room before the beginning of the defense session. The students whose defense is after the break, can use the break time for these preparations.
The time limit for master's defense presentation is 15 minutes. The defenses will be held publicly if not declared private. The thesis is defended in the form of an open academic debate which includes:
- presentation of the defender (up to 15 minutes)
- questions about the presentation
- reviewer's opinion
- general discussion, starting with the supervisor's assessment
- author's closing remarks (1 min)
The defended thesis is assessed in the closed part of the meeting where the supervisor(s) and reviewer(s) are allowed to participate. The chair of the committee announces the results of the defense within one working day after the defense. If a master's student has successfully defended their graduation thesis, they are considered to have graduated from the university with a master's degree.
Read more about the procedure for defense in the Faculty of Science and Technology here.
Committee: chair: Raul Kangro, members: Jüri Lember, Kalev Pärna, Meelis Käärik, Toomas Raus
| beginning approximately (curriculum) | Student | Supervisor(s) | Topic |
Reviewer |
|
| 10.00 (AFE) | Narmin | Mammadli | Stefania Tomasiello, Toomas Raus | Interpretable approaches for financial time series forecasting | Märt Möls |
| 10.50 (AFE) | Nicholas | Lupul | Meelis Käärik | Claims Severity Modelling on the Basis of Publicly Available Vehicle Insurance Data | Tõnu Kollo |
| 11.30 (AFE) | Kaari | Kuus | Meelis Käärik | Claims frequency modelling with usage-based insurance data | Anastassia Kolde |
| 12.10 (MS) | Liis | Hiie | Jaanika Kronberg, Krista Fischer | Human Metabolic Pathways as Predictors for Hypertension Based on Estonian Biobank Data | Märt Möls |
| BREAK | |||||
| 13.30 (AFE) | Kelly | Tilga | Anastassia Kolde | Pseudovaatlused elukestusanalüüsis depressiooni ja kardiometaboolsete haiguste vaheliste seoste hindamiseks TÜ Eesti Geenivaramu andmete põhjal | Meelis Käärik |
| 14.10 (MS) | Mihkel | Lepson | Raivo Kolde | Epikriisi tekstide genereerimine GPT-2 mudeliga | Raul Kangro |
| 14.50 (AFE) | Artur | Tuttar | Meelis Käärik, Julius Pau | Extending generalized linear models in insurance with machine learning techniques | Raul Kangro |
| 15.30 (AFE) | Hardi | Roosi | Raul Kangro | K-lähinaabri meetodi ja selle modifikatsioonide rakendamise tehnilistest detailidest ja nende võimalikust mõjust tulemuste täpsusele | Kalev Pärna |
| Student | Supervisor(s) | Topic |
Reviewer |
||
| Kaari | Kuus | Meelis Käärik | Claims frequency modelling with usage-based insurance data | Anastassia Kolde | |
| Nicholas | Lupul | Meelis Käärik | Claims Severity Modelling on the Basis of Publicly Available Vehicle Insurance Data | Tõnu Kollo | |
| Narmin | Mammadli | Stefania Tomasiello, Toomas Raus | Interpretable approaches for financial time series forecasting | Märt Möls | |
| Hardi | Roosi | Raul Kangro | K-lähinaabri meetodi ja selle modifikatsioonide rakendamise tehnilistest detailidest ja nende võimalikust mõjust tulemuste täpsusele | Kalev Pärna | |
| Kelly | Tilga | Anastassia Kolde | Pseudovaatlused elukestusanalüüsis depressiooni ja kardiometaboolsete haiguste vaheliste seoste hindamiseks TÜ Eesti Geenivaramu andmete põhjal | Meelis Käärik | |
| Artur | Tuttar | Meelis Käärik, Julius Pau | Extending generalized linear models in insurance with machine learning techniques | Raul Kangro |
| Student | Supervisor(s) | Topic |
Reviewer |
||
| Suleyman | Ahmadov | Kalev Pärna | Weight of Evidence Methodology in Logistic Regression with Application in Credit Scoring | Kristi Kuljus | |
| Dhruba Raj | Gnawali | Märt Möls | GLARMA time series modeling of counts | ||
| Ali | Hasanov | Toomas Raus | Analysis of the Links among FDI, GDP, Oil and Gas Prices in Developed, Developing and Resource-Dependent Countries | ||
| Abdullateef Akorede | Ibrahim | Toomas Raus | Weak Efficiency of Foreign Exchange Rates |
