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Matematikcentrum

Lunds universitet

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Artificial Inteligence & Machine Learning Projects

Masters and Bachelors Students Directed

Thesis Directed

  • Bachelor - Oisin Clancy, Dec. 2021
    Title: Classification of EEG recorded Meditative States using Machine Learning
    Examiner: TBA
  • Master - Victor Mårtensson, June 2021. With Janne Sakerson Mashie FoodTech Solutions.
    Title: AI-Driven Meal Planning in the FoodTech IndustryA Reinforcement Learning Approach
    Examiner: Karl Åstrom.
  • Master - Maximilian Schön, June 2021.
    Title: Identifying obstacles and key measurements of roof surfaces using a digital surface model and an orthomosaic
    Examiner: Karl Åstrom.
  • Master - Rasmus Helander, June 2021. With Jonas Söderberg at RaySearch.
    Title: Evaluating the efficiency of augmentation by learned transformations for segmentation of magnetic resonance images
    Examiner: Niels Christian Overgaard
  • Master - Niklas Hummer, Nov. 2020. With SGU and Dept. of Geology.
    Title: Machine learning methods on Swedish geological data.
    Examiner: Magnus Wiktorsson.
  • Bachelors - Dennis Hein, Oct. 2020.
    Title: Super-resolution and object detection from low resolution images - social distancing AI
    Examiner: Magnus Wiktorsson.
  • Master - Robin Veziroglu.
    Title: Machine learning methods for self-driving vehicles.
    Examiner: Magnus Wiktorsson.
  • Master - Karl Tengelin. Co-advisor Hugo Lungeen and Jimmy Karlsson, Century AI, May 2020.
    Title: Algorithms for identifying and classifying tick clustering in the currency exchange market. Examiner: TBA.
  • Bachelors - Yichen Liu. June 2020.
    Title: Resolving hybrid system dynamics with Neural ODEs.
    Examiner: Claus Fuhrer, Math. LTH.
  • Master - Thomas Hamfelt internship Nordea - Denmark, May 2020.
    Title: Multivariate Timeseries Forecasting and Data Augmentation for Heavy Industries.
    Examiner: TBA.
  • Master - Simon Sjögren. Sept 2019.
    Title: Designing a deep neural network for time-series prediction featuring traffic data.
    Examiner: Claus Fuhrer, Math. LTH.
  • Bachelors - Christoffer Svenningsson. Sept. 2019.
    Title: Modelling driver behavior with artificial neural networks.
    Examiner: Mattias Ohlsson, Physics, LTH.
  • Master - Joel Andersson. Co-advisor Davide Gamba, CERN. Dec. 2019.
    Title: A Linear Framework for Orbit Correction in the High-Luminosity Large Hadron Collider.
    Examiner: Eskil Hansen, Math, LTH.
  • Master - Frej Berglind. Co-advisor Jianhua Chen, Luissiana State Univ. Dec. 2019.
    Title: Adaptive Distributional Temporal Difference Learning for Game Playing using Deep Neural Networks.
    Examiner: Johan Lindstrom, Statistics, LTH.
  • Master - Erik Norlander. Co-advisor Richard Henricsson, Handelsbank, June 2019.
    Title: Clustering and Anomaly Detection in Financial Trading Data Using the Conditional Latent Space Variational Autoencoder.
    Examiner: Johan Lindstrom, Statistics LTH.
  • Bachelors - Thomas Hamfelt. Aug. 2019.
    Title: Forecasting the USD/SEK exchange rate using deep neural networks.
    Examiner: Magnus Wiktorsson, Statistics LTH.
  • Bachelors - Oskar Stigland. Co-advisors Morten Arngren and Vlad Sandulescu, Adform. Sept. 2018.
    Title: Deep Reinforcement Learning in Real-Time Bidding
    Examiner: Johan Lindstrom, Statistics LTH.
  • Masters - Gustav Lundberg. Sept. 2018.
    Title: Transfer Learning in Autonomous Vehicles Using Convolutional Networks.
    Examiner: Mattias Ohlsson, Physics LTH.
  • Masters - Erik Ackzell. Aug. 2018.
    Title: Modeling rush hour vehicular traffic using a machine learning approach.
    Examiner: Claus Fuhrer, Math-NA, LTH.
  • Bachelors - Johan Peter Moler. June 2018.
    Title: Description: Studying and forecasting trends for crypto-currencies via a machine learning approach.
    Examiner: Claus Fuhrer, Math-NA, LTH.
  • Masters -Arwin Sohrabi. May 2018
    Title: A machine learning model for stock market trading predictions, Examiner: Claus Fuhrer, Math-NA, LTH.
  • Masters - Anders Hansson. May 2018.
    Title: An improved deep learning network for racing with a self-driving vehicle,
    Examiner: Kalle Astrom, Math-Visualization, LTH.
  • Bachelors -Nora Ibrahim, June 2017
    Title: Designing a deep learning network for self-driving vehicles,
    Examiner: Claus Fuhrer, Math-NA LTH.

Examiner for Thesis

  • Masters - Simon Sjogren, June 2021
    Title: TBA
    Advisor - Tony Stylfjord
  • Bachelors - Isabela Vinterbladh, December 2019
    Title: Parameter estimation with the non-linear Levenberg-Marquardt method on hydrogeological models.
  • Masters - Magnus Hansson and Christoffer Olsson, August 2017
    Title: Feedforward neural networks with ReLU activation functions and linear splines.