Ben Wolf

PhD Candidate Artificial Intelligence

Groningen, Netherlands
University of Groningen
benbenwolf.nl
Ben Wolf - PhD candidate at University of Groningen

H2020 Lakhsmi project

The lakhsmi consortium aims to develop novel bioinspired flow sensors for near-field sensing.

Ben is modelling, prototyping and testing sensors to work towards artificial lateral line hydrodynamic imaging: the ability to detect and track nearby underwater objects and obstacles.


Robocup@home Team Borg

The team works with Alice, a domestic service robot capable of autonomous navigation, SLAM, object recognition and manipulion.

Ben lead the team, designed the coorporate style, maintains the behavior architecture and developed the speech system.


Study Association Cover

Besides being the chair of the association board in '11-'12, Ben has contributed in organizing two study trips and was active for several years in the academic broadening committee organizing lectures and company visits. Currently, he holds a position in the advisory board

His creative side is highlighted by designing several yearbooks, layouting several magazines, committee logo's and posters.


Buzzwords, skills and interests

Artificial Intelligence, Speech Recognition, Machine Learning, Deep Learning, Robotics, Layout Design, Numbers, Python, Matlab, LaTeX, Adobe Indesign, Adobe Illustrator, Neuroscience, Image Recognition, Sound Processing, Explanations, ...

Patent application

S.M. van Netten, B.J. Wolf, W.N. MacPherson, (2017). Sensor element and method for measuring of near-field, large-scale hydrodynamic characteristics. EP3399320 (A1). [Espacenet]


Journal articles

B.J. Wolf, S. Warmelink, S.M. van Netten, (2019). Recurrent neural networks for hydrodynamic imaging using a 2D-sensitive artificial lateral line. Bioinspiration & Biomimetics 14(5) 055001. [DOI] [Publisher PDF] Special issue on Active Perception and Bioinspired Sensing

B.J. Wolf, J.A.S. Morton, W.M. macPherson, S.M. van Netten, (2018). Bio-inspired all-optical artificial neuromast for 2D flow sensing. Bioinspiration & Biomimetics 13(2) 026013. [DOI] [Publisher PDF] [bib]

L.H. Boulogne, B.J. Wolf, M.A. Wiering, S.M. van Netten, (2017). Performance of neural networks for localizing moving objects with an artificial lateral line. Bioinspiration & Biomimetics 12(5) 056009. [DOI] [PDF] [bib]


Presented conference articles

B.J. Wolf, S.M. van Netten, (2019). Hydrodynamic Imaging using an all-optical 2D Artificial Lateral Line. 2019 IEEE Sensors Applications Symposium (SAS) 1-6. [DOI] [PDF] Awarded student travel grant award

B.J. Wolf, S.M. van Netten, (2019). Training Submerged Source Detection for a 2D Fluid Flow Sensor Array with Extreme Learning Machines. Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018) 1104126. [DOI] [PDF] Awarded best oral presentation


Conference poster

P. van der Meulen, B.J. Wolf, P. Pirih, S.M. van Netten, (2018). Performance of Neural Networks in Source Localization using Artificial Lateral Line Sensor Configurations. ICT.OPEN2018 [DOI]