{"id":702,"date":"2024-01-17T10:50:46","date_gmt":"2024-01-17T10:50:46","guid":{"rendered":"https:\/\/mat.ub.edu\/sciencedata\/?page_id=702"},"modified":"2025-07-01T09:22:34","modified_gmt":"2025-07-01T09:22:34","slug":"masters-project","status":"publish","type":"page","link":"https:\/\/mat.ub.edu\/sciencedata\/masters-project\/","title":{"rendered":"Final Master Project"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>In most cases, the Master&#8217;s Project is carried out individually by a single student. However, group projects may also be considered. In such cases, the expected workload should be proportional to the number of participants, with each student contributing approximately 300 hours. Students can either select a project from the list of suggested topics or propose their own project idea.<\/p>\n<p style=\"text-align: justify;\"><b>More information<\/b>: <u><\/u><\/p>\n<ul>\n<li style=\"text-align: justify;\"><u><a href=\"https:\/\/github.com\/DataScienceUB\/PFM\">https:\/\/github.com\/DataScienceUB\/PFM<\/a><\/u><\/li>\n<li>Regulations for the\u00a0<a href=\"https:\/\/mat.ub.edu\/wp-content\/uploads\/2024\/09\/2024-06-11_NormativaTFM2024_Final.pdf\" target=\"_blank\" rel=\"noopener\">Master\u2019s Final Project.<\/a><\/li>\n<\/ul>\n<p><b>Calendar (Jan 2025)<\/b>:<\/p>\n<p>[vc_row][vc_column][vc_column_text css=&#8221;&#8221;]<\/p>\n<table class=\" aligncenter\" style=\"width: 100.63%; height: 1680px;\" width=\"1440\">\n<tbody>\n<tr style=\"height: 24px;\">\n<td style=\"width: 4.87593%; height: 24px;\" width=\"89\"><strong>Tribunal<\/strong><\/td>\n<td style=\"width: 3.8203%; height: 24px;\" width=\"67\"><strong>Room<\/strong><\/td>\n<td style=\"width: 9.11433%; height: 24px;\" width=\"160\"><strong>Date<br \/>\n<\/strong><\/td>\n<td style=\"width: 6.83522%; height: 24px;\" width=\"141\"><strong>President<\/strong><\/td>\n<td style=\"width: 7.84657%; height: 24px;\" width=\"125\"><strong>Secretari<\/strong><\/td>\n<td style=\"width: 9.71076%; height: 24px;\" width=\"128\"><strong>Vocal<\/strong><\/td>\n<td style=\"width: 9.09651%; height: 24px;\" width=\"160\"><strong>Suplent<\/strong><\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"123\"><strong>Student<\/strong><\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"69\"><strong>Supervisor 1<\/strong><\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"41\"><strong>Supervisor 2<\/strong><\/td>\n<td style=\"width: 17.1677%; height: 24px;\" width=\"556\"><strong>Definitive Master&#8217;s Project title<br \/>\n<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 48px;\">\n<td style=\"width: 4.87593%; height: 48px;\" width=\"89\">1<\/td>\n<td style=\"width: 3.8203%; height: 48px;\" width=\"67\">T2<\/td>\n<td style=\"width: 9.11433%; height: 48px;\" width=\"160\">25\/06\/2025 &#8211; 15:30<\/td>\n<td style=\"width: 6.83522%; height: 48px;\" width=\"141\">Jordi Vitri\u00e0<\/td>\n<td style=\"width: 7.84657%; height: 48px;\" width=\"125\">Laura Igual<\/td>\n<td style=\"width: 9.71076%; height: 48px;\" width=\"128\">Eloi Puertas<\/td>\n<td style=\"width: 9.09651%;\" valign=\"bottom\" nowrap=\"nowrap\" data-ogsb=\"rgb(255, 242, 204)\">Mireia Ribera<\/td>\n<td style=\"width: 9%;\" valign=\"bottom\" nowrap=\"nowrap\" data-ogsb=\"rgb(255, 242, 204)\">Marc Ballestero Rib\u00f3<\/td>\n<td style=\"width: 9%; height: 48px;\" width=\"69\">Daniel Ortiz Mart\u00ednez<\/td>\n<td style=\"width: 9%; height: 48px;\" width=\"41\"><\/td>\n<td style=\"width: 17.1677%; height: 48px;\" width=\"556\">Explaining Word Interactions using Integrated Directional Gradients<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\" width=\"89\">2<\/td>\n<td style=\"width: 3.8203%;\" width=\"67\">T2<\/td>\n<td style=\"width: 9.11433%;\" width=\"160\">15\/7\/2025 &#8211; 15:00<\/td>\n<td style=\"width: 6.83522%;\" width=\"141\">Petia Radeva<\/td>\n<td style=\"width: 7.84657%;\" width=\"125\">Julio Cezar Silveira Jacques-Junior<\/td>\n<td style=\"width: 9.71076%;\" width=\"128\">Mireia Ribera<\/td>\n<td style=\"width: 9.09651%;\" width=\"160\">Laura Igual<\/td>\n<td style=\"width: 9%;\" width=\"123\">Ana Rey Davila<\/td>\n<td style=\"width: 9%;\" width=\"69\">Oriol Pujol Vila<\/td>\n<td style=\"width: 9%;\" width=\"41\"><\/td>\n<td style=\"width: 17.1677%;\" width=\"556\">Application of One-Class Models for Financial Risk Classification<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\" width=\"89\">2<\/td>\n<td style=\"width: 3.8203%;\" width=\"67\">T2<\/td>\n<td style=\"width: 9.11433%;\" width=\"160\">15\/7\/2025 &#8211; 15:40<\/td>\n<td style=\"width: 6.83522%;\" width=\"141\">Petia Radeva<\/td>\n<td style=\"width: 7.84657%;\" width=\"125\">Julio Cezar Silveira Jacques-Junior<\/td>\n<td style=\"width: 9.71076%;\" width=\"128\">Mireia Ribera<\/td>\n<td style=\"width: 9.09651%;\" width=\"160\">Laura Igual<\/td>\n<td style=\"width: 9%;\" width=\"123\">Jokin Eguzkitza Zalakain<\/td>\n<td style=\"width: 9%;\" width=\"69\">Laura Igual<\/td>\n<td style=\"width: 9%;\" width=\"41\"><\/td>\n<td style=\"width: 17.1677%;\" width=\"556\">Evaluating Tool-Augmented ReAct Language Agents<\/td>\n<\/tr>\n<tr style=\"height: 24px;\">\n<td style=\"width: 4.87593%; height: 24px;\" width=\"89\">2<\/td>\n<td style=\"width: 3.8203%; height: 24px;\" width=\"67\">T2<\/td>\n<td style=\"width: 9.11433%; height: 24px;\" width=\"160\">15\/7\/2025 &#8211; 16:20<\/td>\n<td style=\"width: 6.83522%; height: 24px;\" width=\"141\">Petia Radeva<\/td>\n<td style=\"width: 7.84657%; height: 24px;\" width=\"125\">Julio Cezar Silveira Jacques-Junior<\/td>\n<td style=\"width: 9.71076%; height: 24px;\" width=\"128\">Mireia Ribera<\/td>\n<td style=\"width: 9.09651%; height: 24px;\" width=\"160\">Laura Igual<\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"123\">Ilaria Curzi<\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"69\">Javier Solana Sanchez<\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"41\">Laura Igual<\/td>\n<td style=\"width: 17.1677%; height: 24px;\" width=\"556\">Patient Profiling and Task Assignment in Neuropsychological Rehabilitation: A Data-Driven Analysis of GNPT\u2019s Decision Support System<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">2<\/td>\n<td style=\"width: 3.8203%;\">T2<\/td>\n<td style=\"width: 9.11433%;\">15\/7\/2025 &#8211; 17:00<\/td>\n<td style=\"width: 6.83522%;\">Petia Radeva<\/td>\n<td style=\"width: 7.84657%;\">Julio Cezar Silveira Jacques-Junior<\/td>\n<td style=\"width: 9.71076%;\">Mireia Ribera<\/td>\n<td style=\"width: 9.09651%;\">Laura Igual<\/td>\n<td style=\"width: 9%;\">Cl\u00e0udia Valverde Sanchez<\/td>\n<td style=\"width: 9%;\">Laura Igual<\/td>\n<td style=\"width: 9%;\">Alexis Molina<\/td>\n<td style=\"width: 17.1677%;\">Pocket-Aware Molecular Generation Through Learned Protein Representations<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">3<\/td>\n<td style=\"width: 3.8203%;\">T2<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 10:30h<\/td>\n<td style=\"width: 6.83522%;\">Laura Igual<\/td>\n<td style=\"width: 7.84657%;\">Oliver D\u00edaz<\/td>\n<td style=\"width: 9.71076%;\">Sergio Escalera<\/td>\n<td style=\"width: 9.09651%;\">Enrique Mora<\/td>\n<td style=\"width: 9%;\">Theodoros Lambrou<\/td>\n<td style=\"width: 9%;\">Jordi Vitria<\/td>\n<td style=\"width: 9%;\"><\/td>\n<td style=\"width: 17.1677%;\">Forecasting Urban Traffic Patterns in London Using Hybrid AI Techniques<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">3<\/td>\n<td style=\"width: 3.8203%;\">T2<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 11:10h<\/td>\n<td style=\"width: 6.83522%;\">Laura Igual<\/td>\n<td style=\"width: 7.84657%;\">Oliver D\u00edaz<\/td>\n<td style=\"width: 9.71076%;\">Sergio Escalera<\/td>\n<td style=\"width: 9.09651%;\">Enrique Mora<\/td>\n<td style=\"width: 9%;\">Joel Di\u00e9guez Vil\u00e0<\/td>\n<td style=\"width: 9%;\">Petia Radeva<\/td>\n<td style=\"width: 9%;\">Javier Rodenas Cumplido<\/td>\n<td style=\"width: 17.1677%;\">Enhancing Few-Shot Learning with Large Language Models<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">3<\/td>\n<td style=\"width: 3.8203%;\">T2<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 -11:50h<\/td>\n<td style=\"width: 6.83522%;\">Laura Igual<\/td>\n<td style=\"width: 7.84657%;\">Oliver D\u00edaz<\/td>\n<td style=\"width: 9.71076%;\">Sergio Escalera<\/td>\n<td style=\"width: 9.09651%;\">Enrique Mora<\/td>\n<td style=\"width: 9%;\">Hug Camps i Reg\u00e0s<\/td>\n<td style=\"width: 9%;\">Ana Blanco Lara<\/td>\n<td style=\"width: 9%;\">Eloi Puertas i Prats<\/td>\n<td style=\"width: 17.1677%;\">Honeypot data classifications into the MITRE framework<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">3<\/td>\n<td style=\"width: 3.8203%;\">T2<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 12:30h<\/td>\n<td style=\"width: 6.83522%;\">Laura Igual<\/td>\n<td style=\"width: 7.84657%;\">Oliver D\u00edaz<\/td>\n<td style=\"width: 9.71076%;\">Sergio Escalera<\/td>\n<td style=\"width: 9.09651%;\">Enrique Mora<\/td>\n<td style=\"width: 9%;\">Georgia Zavou<\/td>\n<td style=\"width: 9%;\">Jordi Abante Llenas<\/td>\n<td style=\"width: 9%;\">Jordi Vitri\u00e0<\/td>\n<td style=\"width: 17.1677%;\">Augmenting phenotype prediction models leveraging a genomic Large Language Model<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">4<\/td>\n<td style=\"width: 3.8203%;\">B3<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 10h<\/td>\n<td style=\"width: 6.83522%;\">Jordi Vitri\u00e0<\/td>\n<td style=\"width: 7.84657%;\">Eloi Puertas<\/td>\n<td style=\"width: 9.71076%;\">Daniel Ortiz<\/td>\n<td style=\"width: 9.09651%;\">Ignasi Cos<\/td>\n<td style=\"width: 9%;\">Alexandru Ioan Oarga Hategan<\/td>\n<td style=\"width: 9%;\">Yilun Du<\/td>\n<td style=\"width: 9%;\">Sergio Escalera Guerrero<\/td>\n<td style=\"width: 17.1677%;\">Generalization beyond Training: Reasoning as Energy-Based Optimization<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">4<\/td>\n<td style=\"width: 3.8203%;\">B3<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 10:40h<\/td>\n<td style=\"width: 6.83522%;\">Jordi Vitri\u00e0<\/td>\n<td style=\"width: 7.84657%;\">Eloi Puertas<\/td>\n<td style=\"width: 9.71076%;\">Daniel Ortiz<\/td>\n<td style=\"width: 9.09651%;\">Ignasi Cos<\/td>\n<td style=\"width: 9%;\">Marcel Canals Codina<\/td>\n<td style=\"width: 9%;\">Enrique Mora Ayala<\/td>\n<td style=\"width: 9%;\"><\/td>\n<td style=\"width: 17.1677%;\">Machine Learning Interpretability: A Study of Local Agnostic Methods and Causal Insights<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">4<\/td>\n<td style=\"width: 3.8203%;\">B3<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 11:20h<\/td>\n<td style=\"width: 6.83522%;\">Jordi Vitri\u00e0<\/td>\n<td style=\"width: 7.84657%;\">Eloi Puertas<\/td>\n<td style=\"width: 9.71076%;\">Daniel Ortiz<\/td>\n<td style=\"width: 9.09651%;\">Ignasi Cos<\/td>\n<td style=\"width: 9%;\">Alba Garcia Romo<\/td>\n<td style=\"width: 9%;\">Dimitri Marinelli<\/td>\n<td style=\"width: 9%;\">Albert Diaz Guilera<\/td>\n<td style=\"width: 17.1677%;\">Exploring Academic Relationships with UMAP: Dimensionality Reduction and Visualization of Topics and Authors in OpenAlex<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">4<\/td>\n<td style=\"width: 3.8203%;\">B3<\/td>\n<td style=\"width: 9.11433%;\">4\/7\/2025 &#8211; 12h<\/td>\n<td style=\"width: 6.83522%;\">Jordi Vitri\u00e0<\/td>\n<td style=\"width: 7.84657%;\">Eloi Puertas<\/td>\n<td style=\"width: 9.71076%;\">Daniel Ortiz<\/td>\n<td style=\"width: 9.09651%;\">Ignasi Cos<\/td>\n<td style=\"width: 9%;\">Alana Zoloeva<\/td>\n<td style=\"width: 9%;\">Santiago Segu\u00ed Mesquida<\/td>\n<td style=\"width: 9%;\"><\/td>\n<td style=\"width: 17.1677%;\">Evaluating and Refining Recommendation Quality: A Case Study of the RecSys Challenge 2024 Winner<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">5<\/td>\n<td style=\"width: 3.8203%;\">T1<\/td>\n<td style=\"width: 9.11433%;\">8\/7\/2025 &#8211; 10:00<\/td>\n<td style=\"width: 6.83522%;\">Oriol Pujol<\/td>\n<td style=\"width: 7.84657%;\">Santi Segu\u00ed<\/td>\n<td style=\"width: 9.71076%;\">Xavier Bar\u00f3<\/td>\n<td style=\"width: 9.09651%;\">Eloi Puertas<\/td>\n<td style=\"width: 9%;\">Lukas Tornow<\/td>\n<td style=\"width: 9%;\">Nahuel Statuto Perez<\/td>\n<td style=\"width: 9%;\"><\/td>\n<td style=\"width: 17.1677%;\">Quantum Machine Learning for Probabilistic Modeling of Chaotic Time Series: A Quantum Bayesian Network Approach to Stock Market Forecasting<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">5<\/td>\n<td style=\"width: 3.8203%;\">T1<\/td>\n<td style=\"width: 9.11433%;\">8\/7\/2025 &#8211; 10:40<\/td>\n<td style=\"width: 6.83522%;\">Oriol Pujol<\/td>\n<td style=\"width: 7.84657%;\">Santi Segu\u00ed<\/td>\n<td style=\"width: 9.71076%;\">Xavier Bar\u00f3<\/td>\n<td style=\"width: 9.09651%;\">Eloi Puertas<\/td>\n<td style=\"width: 9%;\">Arnau Jutglar Puig<\/td>\n<td style=\"width: 9%;\">Nahuel Statuto Perez<\/td>\n<td style=\"width: 9%;\">Julio Cezar Silveira Jacques-Junior<\/td>\n<td style=\"width: 17.1677%;\">Regularization-based machine unlearning<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 4.87593%;\">5<\/td>\n<td style=\"width: 3.8203%;\">T1<\/td>\n<td style=\"width: 9.11433%;\">8\/7\/2025 &#8211; 11:20<\/td>\n<td style=\"width: 6.83522%;\">Oriol Pujol<\/td>\n<td style=\"width: 7.84657%;\">Santi Segu\u00ed<\/td>\n<td style=\"width: 9.71076%;\">Xavier Bar\u00f3<\/td>\n<td style=\"width: 9.09651%;\">Eloi Puertas<\/td>\n<td style=\"width: 9%;\">Joshua Tapper<\/td>\n<td style=\"width: 9%;\">Ignasi Cos Aguilera<\/td>\n<td style=\"width: 9%;\"><\/td>\n<td style=\"width: 17.1677%;\">Semantic Decoding of Neural Data Series<\/td>\n<\/tr>\n<tr style=\"height: 24px;\">\n<td style=\"width: 4.87593%; height: 24px;\" width=\"89\">5<\/td>\n<td style=\"width: 3.8203%; height: 24px;\" width=\"67\">T1<\/td>\n<td style=\"width: 9.11433%; height: 24px;\" width=\"160\">8\/7\/2025 &#8211; 12:00<\/td>\n<td style=\"width: 6.83522%; height: 24px;\" width=\"141\">Oriol Pujol<\/td>\n<td style=\"width: 7.84657%; height: 24px;\" width=\"125\">Santi Segu\u00ed<\/td>\n<td style=\"width: 9.71076%; height: 24px;\" width=\"128\">Xavier Bar\u00f3<\/td>\n<td style=\"width: 9.09651%; height: 24px;\" width=\"160\">Eloi Puertas<\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"123\">Luca Eric Di Croce<\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"69\">Ignasi Cos Aguilera<\/td>\n<td style=\"width: 9%; height: 24px;\" width=\"41\"><\/td>\n<td style=\"width: 17.1677%; height: 24px;\" width=\"556\">How the brain moves: Understanding motion-based brain states using deep learning techniques<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>In most cases, the Master&#8217;s Project is carried out individually by a single student. However, group projects may also be considered. In such cases, the expected workload should be proportional to the number of participants, with each student contributing approximately 300 hours. Students can either select a project from the list of suggested topics or [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-void.php","meta":{"footnotes":""},"class_list":["post-702","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/pages\/702","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/comments?post=702"}],"version-history":[{"count":63,"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/pages\/702\/revisions"}],"predecessor-version":[{"id":868,"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/pages\/702\/revisions\/868"}],"wp:attachment":[{"href":"https:\/\/mat.ub.edu\/sciencedata\/wp-json\/wp\/v2\/media?parent=702"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}