Advanced Data Analysis Techniques (TAAD) - Project presentations

Europe/Lisbon
D.14 (Dep. of Physics, FCTUC)

D.14

Dep. of Physics, FCTUC

Description

Research project presentations should describe the problem, the techniques used to address it, and the conclusions reached.

Each presentation will be 15 mins (maximum) and will be followed by up to 5 minutes of questions/discussion. Both students in each group should participate in making and showing the presentation. The  presence of all students is welcome during all presentations, but not mandatory.

Evaluation criteria will be: 1) presentation clarity, 2) description of problem, 3) use of machine learning techniques, 4) conclusions and critical thinking. Project supervisors are welcome to attend the presentations and will be asked to take part in the evaluation.

Course: Advanced Data Analysis Techniques (TAAD)

Degree/university: MEF/MF - UC, 1st semester 2023/2024

Profs: R. Gonçalo, F. Veloso, M. Ferreira, P. Brás, T.Cerqueira, T. Malik, T. Pereira

    • 10:00 10:15
      Learning Models to Classify PPG Waveforms 15m
      Speakers: Duarte Rodrigues, Henrique Gaspar
    • 10:20 10:35
      Deciphering the Dark: A Machine Learning Approach to Detecting Dark Matter Influence in Neutron Star Observables 15m
      Speakers: Mariana Encarnação, Patrícia Encarnação
    • 10:40 10:55
      Audio analysis: Speech recognition 15m
      Speakers: Gabriel Maynard, Michelle Colantoni
    • 11:00 11:15
      Classification of pulses in the LUX-ZEPLIN dark matter detector 15m
      Speakers: Adeniyi Adebayo, Ronald Soares
    • 11:20 11:35
      Earth Observation Mission of a 6U CubeSat with a 5-Meter Resolution for Wildfire Image Classification Using Convolution Neural Network Approach 15m
      Speaker: Plínio Borges