Tim Bakker

Tim Bakker

PhD researcher in Machine Learning

University of Amsterdam

Biography

I’m a PhD student at the Amsterdam Machine Learning lab with Herke van Hoof and Max Welling. My research focuses on active learning and active sensing through reinforcement learning.

Other interests include AI4Science, everything Bayesian, effective altruism, and musical theater.

Download my resume.

Interests
  • Machine Learning
  • Reinforcement learning
  • AI4Science
  • Bayesian probability theory
Education

  • MSc in Theoretical Physics, 2016

    University of Amsterdam

  • BSc in Physics and Astronomy, 2014

    University of Amsterdam

Recent posts

From Bayesian inference to modern machine learning
A tour from prescriptive Bayesianism to modern statistical machine learning.
Tim Bakker
Last updated on Mon, Apr 19, 2021 14 min read
From Bayesian inference to modern machine learning
Everything but commentary
A look at the objective Bayesian prescription for reasoning under uncertainty.
Tim Bakker
Last updated on Wed, Apr 7, 2021 12 min read
Everything but commentary

Publications

Tim Bakker, Matthew Muckley, Adriana Romero-Soriano, Michal Drozdzal, Luis Pineda (2022). On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction. MIDL 2022.

PDF Code

Sierk Kanis, Laurens Samson, Daan Bloembergen, Tim Bakker (2021). Back to Basics: Deep Reinforcement Learning in Traffic Signal Control. UrbComp 2021, Best Paper Award runner-up.

PDF Code Video

Tim Bakker, Herke van Hoof, Max Welling (2020). Experimental design for MRI by greedy policy search. NeurIPS 2020, Spotlight.

PDF Cite Code Slides Video

Recent talks

Active sensing for magnetic resonance imaging
Qualcomm academic lecture on our NeurIPS 2020 Spotlight paper and applications to active sensing.
Wed, Dec 2, 2020 17:30 — 18:30 Online
Experimental design for MRI by greedy policy search
Amsterdam Machine Learning lab seminar on our NeurIPS 2020 Spotlight paper.
Thu, Nov 5, 2020 16:00 — 17:00 Online

Supervision

Master AI projects

  • 2020-2021: Uncertainty and Diversity Based Methods in Batch-Mode Active Learning, András Csirik.
  • 2020-2021: Back to Basics: Deep Reinforcement Learning in Traffic Signal Control, Sierk Kanis. UrbComp'21 Best Paper Award runner-up.
  • 2019-2020: Contrastively-shaped reward signals for curiosity-based exploration tasks, Nil Stolt Anso.

Bachelor AI projects

  • 2019-2020: Forecasting shipped orders with long short-term memory recurrent neural networks, Roel van der Burght.

External projects

  • 2019-2020: Bayesian Convolutional Neural Networks for Learning Ground State Energies from a Simple Harmonic Potential Well, Chase van de Geijn.

Teaching

Reinforcement Learning 2019, 2020

I was teaching assistant for the Master AI Reinforcement Learning 2019 and 2020 course at the University of Amsterdam. This involved leading lab and theoretical homework sessions, as well as supervising group projects. Additionally, I taught a substitute lecture on Deep Q-Learning.

Leren 2019, 2021 (Introduction Machine Learning)

I was teaching assistant for the Bachelor AI Leren 2019 and 2021 course at the University of Amsterdam. This involved leading theoretical homework sessions, and assisting students in their lab work.

Experience

 
 
 
 
 
Research intern
Facebook AI Research
Jun 2021 – Oct 2021 Montreal (remote)
Research internship on machine learning for active acquisition methods in Magnetic Resonance Imaging.
 
 
 
 
 
PhD researcher
AMLab, University of Amsterdam
Mar 2019 – Present Amsterdam
Researching reinforcement learning methods for active learning and active sensing.
 
 
 
 
 
Machine Learning Engineer
BrainCreators
Sep 2017 – Feb 2019 Amsterdam
Engineer and consultant on a variety to topics from object detection to NLP.

Organiser

 
 
 
 
 
Guide and organiser
Effective Altruism Meditation
Oct 2020 – May 2021 Online
EA Meditation tries to connect effective altruists with an interest in meditation, and gives them a place to practice together. My primary role was to guide weekly 20-minute breath meditations.
 
 
 
 
 
Mentor
Inclusive AI
May 2019 – Present Amsterdam
As an IAI mentor, I help members navigate the academic and non-academic world during and after their Master AI programme.
 
 
 
 
 
Board member
Inclusive AI
May 2019 – Oct 2021 Amsterdam
The IAI is an inclusive space for members to receive non-academic help from senior peers in the field and connect with people of various backgrounds. As a board member I thought about ways to make IAI more effective at combating the ‘leaky-pipeline’ problem of AI industry and academia, and organised events to give our mentees a head-start.
 
 
 
 
 
Interim board member
Amsterdams Studentenprojectkoor (ASPK)
Nov 2018 – Feb 2019 Amsterdam
The ASPK is an Amsterdam-based, student-lead amateur choir and association that performs yearly operettas in Dutch. As interim board member I updated our statutes, wrote summaries for PR material, and performed a general assisting role.
 
 
 
 
 
Chair and organiser
Amsterdams Studentenprojectkoor (ASPK) activities committee
Oct 2018 – Present Amsterdam
The activities committee is responsible for organising regular events for ASPK members with the aim of fostering group cohesion and fun. Events we’ve organised include Christmas carolling, pub quizzes, and oper(ett)a viewings.
 
 
 
 
 
Co-founder and organiser
LessWrong Netherlands meetup
Jul 2016 – Jul 2018 Amsterdam and Utrecht
We met every few weeks to philosophise, discuss cognitive biases, and learn techniques for dealing with the latter.
 
 
 
 
 
Organiser
Effective Altruism Netherlands
May 2016 – Jul 2017 Netherlands
I volunteered for and helped organise national projects with the goal of movement building.
 
 
 
 
 
Founder and organiser
Effective Altruism Amsterdam meetup
Mar 2016 – Present Amsterdam
We meet every month to philosophise, discuss current events, and talk about the best ways to have an actual impact in the world.

Contact