Andrea Dunbar

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andrea.dunbar@epfl.ch +41 21 693 23 87

Citizenship: British / Swiss

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EPFL CDM MTEI-GE
ODY 2 01.2 (Odyssea)
Station 5
1015 Lausanne

+41 21 693 23 87
Office: ODY 2 01.2
EPFL > CDM > MTEI > MTEI-GE

+41 21 693 23 87
EPFL > CDM > CDM-MTE > MTE-ENS

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Administrative data

Professional course

Focus Activity Manager

Data & AI

CSEM

2023- now

Group Leader

Edge AI & Vision

CSEM

2018-2023

Publications

Selected publications

S Narduzzi, SA Bigdeli, SC Liu, LA Dunbar ICASSP, 2022	Optimizing the consumption of spiking neural networks with activity regularization
D Honzátko, E Türetken, P Fua, L.A. Dunbar IC3DV, 2021	Leveraging spatial and photometric context for calibrated non-lambertian photometric stereo
Pedram Pad, Simon Narduzzi, Clement Kundig, Engin Turetken, Siavash A. Bigdeli, L. Andrea Dunbar CVPR, 2020	Efficient Neural Vision Systems Based on Convolutional Image Acquisition
Duncan Luguern, Simon Perche, Yannick Benezeth, Virginie Moser, L Andrea Dunbar, Fabian Braun, Alia Lemkaddem, Keisuke Nakamura, Randy Gomez, Julien Dubois CVPR, 2020	An assessment of algorithms to estimate respiratory rate from the remote photoplethysmogram

Teaching & PhD

Teaching

Management of Technology

Past EPFL PhD Students

Sepehri Yamin ,

Courses

Data science for business

Students will learn how data science can be used to make better business decisions. In doing this we examine the basic data science techniques used in business and how to evaluate them within a business framework. We demonstrate key transversal business concepts through use-cases implementation.