Selpi Selpi

Forskare at Chalmers, Mechanics and Maritime Sciences, Vehicle Safety

Selpi is a project leader at the department of Applied Mechanics, division of Vehicle Safety. Within this division, she belongs to the research group Accident Prevention. For most days, she can be visited at SAFER. (Lindholmspiren 3, Lindholmen Science Park, Göteborg).Her research interests include understanding how drivers behave differently from one another in different situations (e.g., driving styles) and exploring the application of machine learning and data mining for analysis of large-scale naturalistic driving data.

Source: chalmers.se

Projects

2015–2016

Driver modelling and cross-cultural analysis of driving styles based on large-scale driving data

Selpi Selpi Accident Prevention
The Swedish Foundation for International Cooperation in Research and Higher Education (STINT)

2015–2016

Att bättre förstå körstil från naturalistisk kördata

Selpi Selpi Accident Prevention
Swedish Transport Administration

There might be more projects where Selpi Selpi participates, but you have to be logged in as a Chalmers employee to see them.

Publications

2017

Economics of Road Safety – What does it imply under the 2030 Agenda for Sustainable Development?

Marie Thynell, Gunnar Lindberg, Selpi Selpi et al
10th Regional Environmentally Sustainable Transport (EST) Forum in Asia, 14-16 March 2017 in Vientiane, Lao PDR, p. 1-58
Conference contribution
2015

A Review of Research on Driving Styles and Road Safety

Giulio Bianchi Piccinini, Selpi Selpi, Johan A Skifs Engström et al
Human Factors. Vol. 57 (No. 7, November 2015), p. 1248- 1275
Journal article
2015

Driving Signature Extraction

Kazuya Takeda, Ekim Yurtsever, Chiyomi Miyajima et al
Paper in proceedings
2015

The effect of curve geometry on driver behaviour in curves by using naturalistic driving data

Selpi Selpi, Robert Thomson, Jakob Imberg et al
Paper in proceedings
2015

Mutual Recognition Methodology Development

Miriam A. Manary, Selpi Selpi, Christian Howard et al
Report
2012

Deliverable D3.3: Data management in euroFOT

Jonas Bärgman, Barbara Metz, Samuel Borgen et al
Report
2012

Investigating visually distracted driver reactions in rear-end crashes and near crashes based on 100-car study data

Henrik Lind, Selpi Selpi, Marco Dozza
In D. de Waard, N. Merat, A.H. Jamson, Y. Barnard, and O.M.J. Carsten (Eds.) (2012). Human Factors of Systems and Technology, p. 201-211
Paper in proceedings
2012

Deliverable D11.3: Final Report

Mohamed Benmimoun, Giancarlo Alessandretti, Aria Etemad et al
Report
2012

Deliverable D5.3: Final delivery of data and answers to questionnaires

Roberto Tadei, Gianfranco Burzio, Walter Hagleitner et al
Report
2011

Automatic real-time FACS-coder to anonymise drivers in eye tracker videos

Li Hagström, Marcus N E Jansson, Selpi Selpi et al
Proceedings of the IEEE International Conference on Computer Vision. 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011, Barcelona, 6-13 November 2011, p. 1986-1993
Paper in proceedings
2011

On data security and analysis platforms for analysis of naturalistic driving data

Jonas Bärgman, Erik M Steinmetz, Selpi Selpi et al
Paper in proceedings
2009

Predicting functional upstream open reading frames in Saccharomyces cerevisiae

Selpi Selpi, Christopher H. Bryant, Janeli Sarv et al
BMC Bioinformatics. Vol. 10, p. 451-
Journal article
2008

Using mRNA Secondary Structure Predictions Improves Recognition of Known Yeast Functional uORFs

C. H. Bryant, Graham Kemp, Selpi Selpi
Wehenkel, L., d'Alché-Buc, F., Moreau, Y. and Geurts, P. (eds.) MLSB08, The Second International Workshop on Machine Learning in Systems Biology, Brussels, 13-14 September 2008., p. 85-93
Paper in proceedings
2007

Using Inductive Logic Programming to Predict Functional Upstream Open Reading Frames in Yeast

C. H. Bryant, M. Cvijovic, Graham Kemp et al
Conference poster
2006

A First Step towards Learning which uORFs Regulate Gene Expression

Graham Kemp, Selpi Selpi, M. Cvijovic et al
Journal of integrative bioinformatics. Vol. 3 (2), p. 31-
Journal article
2005

Using the Functional Data Model to Store and Query Recursive Biological Data

Merja Karjalainen, Selpi Selpi, Graham Kemp
Workshop on Database Issues in Biological Databases (DBiBD),8-9 January 2005, Edinburgh, UK, p. 24-28
Conference contribution
2004

Pathway and Protein Interaction Data: from XML to FDM Database

Graham Kemp, Selpi Selpi
Lecture Notes in Computer Science. Vol. 2994, p. 212-219
Journal article