Christian Fischer Pedersen

PhD, Lektor

Institut for Elektro- og Computerteknologi - Signal Processing and Machine learning - Edison
Finlandsgade 22
bygning 5125, 314
8200 Aarhus N
Danmark
cfp@ece.au.dk
Fastnet: +4541893318

Visit my research group page - Signal Processing and Distributed Computing

Profil

Christian received a MSc degree (Electrical and Computer Engineering), a MSc degree (Mathematics and Computer Science), and a PhD degree (Speech Signal Processing) from Aalborg University, Denmark. Currently, he is with the Section of Signal Processing and Machine Learning, Department of Electrical and Computer Engineering, Aarhus University. At this department he has founded the Signal Processing and Distributed Computing Group. Christian teaches and supervises at BSc, MSc, and PhD levels, he has co-organized conferences, workshops and summer schools, he has authored more than 70 scientific publications including a patent with Fraunhofer, and he has participated in 14 national and international research projects. Christian has been a visiting scholar at: i) Aalto University Helsinki, ii) Imperial College London, iii) Shanghai Jiao Tong University, and iv) University of Erlangen-Nuremberg. He is an IEEE Senior Member and vice-chairing the External Engineering Examiners in Denmark at BSc/MSc levels in accordance with the Danish Ministry of Higher Education and Science. Christian’s research interests include biomedical signal/image/data processing and statistical learning for clinical decision support systems.

Seneste publikationer

Accepteret/In press
Predicting Survival Time of Ball Bearings in the Presence of Censoring
Publikation: Bidrag til bog/antologi/rapport/proceeding › Konferencebidrag i proceedings › Forskning › peer review
Udgivet
Computationally Efficient Labeling of Cancer-Related Forum Posts by Non-Clinical Text Information Retrieval
Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review
Accepteret/In press
Uncertainty Estimation in Deep Bayesian Survival Models
Publikation: Bidrag til bog/antologi/rapport/proceeding › Konferencebidrag i proceedings › Forskning › peer review