Selpi Selpi

Forskare, Data Science och AI avdelningen, Institution av Data-och informationsteknik

  • Python för data scientists (2021-)
  • Tillämpad maskininlärning (2019-)
  • Introduktion till data science och AI (2020-2021)
  • Databas (2015-2019)
Recent Master's thesis projects that I supervised:
  • Resource Optimal Neural Networks for Safety-Critical Real-Time Systems
  • Detecting and predicting automation expectation mismatch
  • Safety evaluation of heterogeneous traffic: using modified models in SUMO
  • Using pre-trained language models for extractive text summarisation of academic papers
  • AI-based road friction estimation using road weather information
  • Predicting pedestrian movement for street segments in urban environments
  • Exploring semi-supervised learning for deciding the order of vehicles in rear-end crashes
  • Lane-level map matching using hidden Markov models
  • Influence area of speed cameras
  • Highway tollgates traffic prediction using a stacked autoencoder neural network
  • Highway tollgates travel time & volume predictions using Support Vector Regression with scaling methods
  • Topic modelling and clustering for analysis of road traffic accidents
  • Automating text categorization with Machine Learning: Error responsibility routing in a multi-layer hierarchy

Sidansvarig Publicerad: må 07 nov 2022.