Selpi Selpi

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

  • Python for data scientists (DIT374) (2021-)
  • Introduktion till data science och AI (DAT405/DIT405) (2020-)
  • Tillämpad maskininlärning (DAT340/DIT866) (2019-)
  • Databas (TDA357/DIT621) (2015-2019)
  • Doktorand kurs Maskin- och fordonssystem Seminarie Kurs, Del A(FTME115) (2015-2020)
  • Doktorand kurs Maskin- och fordonssystem Seminarie Kurs, Del B (FTME120) (2015-2020)
  • Engineering of Automotive Systems (2011-2013)
  • Active Safety (guest lecture, 2010-2014)
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: on 06 apr 2022.