Links to the project reports
Project #2:
- Description: Big data in GUI lists
- Team: Sotirios Chatzigeorgiou, Shuyi Qin Report
Project #3:
- Description: Finding new two dimensional magnets by evolutionary structure search algorithms and ab initio theory
- Team: Leo Zdansky Cottle, Patric Beas Petersson Report
Project #4:
- Description: Deep learning with added landmarks for improved object segmentation
- Team: Nima Akbarian, Edvin Arvidsson, Henrik Sparr, Magnus Sahlin, Imane Momayiz Report
Project #5:
- Description: (Un)certain asset price direction prediction using Bayesian Neural Networks
- Team: Gustav Lind, Andreas Lindgren, Aliaksandra Kupreyeva Report
Project #6:
- Description: Can we compute the eigenvalues without the matrix?
- Team: David Meadon, Melker Claesson, John Danielsson Report
Project #7:
- Description: Efficient detection of data quality flaws in social interactions of dairy cows
- Team 7a: Li Ju, Gustaf Andersson, Linus Kanestad Report
- Team 7b: Torsten Malmgård, Björn Sparresäter Report
Project #8:
- Description: Dairy Farmers Dashboard
- Team: Axel Jonnarth, Björn Seifert, Muhammad Ishfaq, Yuting Wang Report
Project #9:
- Description: Evaluating locally measured weather and weathers services
- Team: Rebecka Homman, Karolina Hedberg, Johan Rideg Report
Project #10:
- Description: Computational techniques for two-phase flow
- Team: Charitini Stavropoulou, Erik Blom, Gunnar Dufwa Report
Project #11:
- Description: Time-step analysis of methods for the advection equation
- Team: Mohammed Mosa, Andrea Lindgren, Zackeus Zetterberg Report
Project #12:
- Description: Stochastic blockmodeling methods for bipartite graphs
- Team: Deepthi Hulithala Venkataramana, Naeim Rashidfarokhi Report
Project #13:
- Description: Multigraph clustering via graph embedding
- Team: Niclas Samuelsson, Daniel Strandberg, Yegor Piven Report
Project #15:
- Description: Enhancing Blockchain Based Federated Learning
- Team: Jacob Tiensuu, Maja Linderholm, Fredrik Örn, Jialun Song Report
Project #16:
- Description: Mapping IR absorbance in wheat seeds to crucial properties using machine learning
- Team: Ruiyun Wang, Ellen Lindgren, Oskar Lundberg, Johannes Bohlin Report
Project #18:
- Description: Machine learning for outcome prediction from magnetic resonance imaging in colorectal cancer
- Team 18a: Maja Arvola, Emil Åberg Report
- Team 18b: Dong Wang, Yu Zhu Report
Project #20:
- Description: Computational modeling of avascular tumors: towards multiscale hybrid models
- Team: Alice Graf Brolund, Rebecca Persson, Johannes Dufva, Mary Jayaweera Report