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 primarily focuses on active learning and active sensing for high-tech applications, such as MRI and molecular simulations. Currently on research internship at Qualcomm AI, previously at Facebook AI Research (FAIR).

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

I have recently spoken about the (existential) risks of AI at Pakhuis de Zwijger and the Dutch Ministry of Defence. Please reach out if you’re interested in a similar talk.

Download my resume.

Interests
  • Active learning / sensing
  • AI alignment
  • Bayesian probability theory
  • Musical theater
Education

  • MSc in Theoretical Physics, 2016

    University of Amsterdam

  • BSc in Physics and Astronomy, 2014

    University of Amsterdam

Recent talks

Existential Risks of Artificial Intelligence
Presentation on the existential risks of artificial intelligence for the Cyber Innovation Hub of the Dutch Ministry of Defence.
Thu, May 4, 2023 13:00 Dutch Ministry of Defence, Den Haag
Existential Risks of Artificial Intelligence
Panel on the existential risks of artificial intelligence, with Stuart Russell, Maxim Februari, Queeny-Aimee Rajkowski, Tim Bakker, and others.
Wed, Apr 12, 2023 20:00 Pakhuis de Zwijger, Amsterdam
Video
Existential Risks of Artificial Intelligence
On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction
MIDL presentation on the paper “On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction” from the Facebook AI Research internship.
Thu, Jul 7, 2022 15:30 — 16:30 ETH Zurich
On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction
See all events

Publications

Tim Bakker, Herke van Hoof, Max Welling (2022). Learning objective-specific active learning strategies with Attentive Neural Processes. Under submission at ECML 2023.

PDF

Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forre (2022). E-Valuating Classifier Two-Sample Tests. Preprint.

PDF

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 Cite 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 posts

AI alignment
My views on the importance and difficulty of the AI alignment problem.
Tim Bakker
Last updated on Mon, May 29, 2023 32 min read
AI alignment
Priors and generalisation
A look at the role of priors in deep learning methods.
Tim Bakker
Last updated on Mon, May 15, 2023 9 min read
Priors and generalisation
From Bayesian inference to modern machine learning
A tour from prescriptive Bayesianism to modern statistical machine learning.
Tim Bakker
Last updated on Sun, May 14, 2023 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 Sun, May 14, 2023 12 min read
Everything but commentary

Supervision

Master AI projects

  • 2021-2023: Active learning for imbalanced image classification, Philip Goto.
  • 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
Qualcomm AI
May 2023 – Present Amsterdam
Research internship on machine learning for physics simulators.
 
 
 
 
 
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 worked 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
Mar 2016 – Present Amsterdam
We meet throughout the month to discuss current events, talk about the best ways to have an actual impact in the world, and then do that.

Contact