Service

Memberships and Committees

• ELLIS Scholar (2021–)
  Theory, Algorithms and Computations of Modern Learning Systems
  European Laboratory for Learning and Intelligent Systems (ELLIS)

• Coordinating Professor (2020–)
  Next-generation Data-efficient Deep Learning Research Program
  Finnish Center for Artificial Intelligence (FCAI)

• Member (for the term 2021–2025)
  Young Academy Finland

• Aalto/FCAI Representative (2020–)
  NVAITC Technical Committee
  NVIDIA AI Technology Center Finland

• AML Track Co-Chair (2021–)
  HICT Steering Group
  The Helsinki Doctoral Education Network in Information and Communications Technology

In addition to internal committee work at Aalto.

Workshop/Conference Co-Organization

• Organizer (2022)
  ECCV Workshop on Uncertainty Quantification for Computer Vision (UNCV)

• Publicity Chair (2020)
  The 30th IEEE International Workshop on Machine Learning for Signal Processing (MLSP)

Seminar Series

• Seminar on Advances in Probabilistic Machine Learning (2021–) Aalto University and ELLIS unit Helsinki Seminar on Advances in Probabilistic Machine Learning

Session Chair

• 2022: AISTATS

Area Chair

• 2023: AISTATS, ICML, NeurIPS
• 2022: AISTATS, NeurIPS
• 2021: NeurIPS

Program Committee Member

• 2021: AAAI, UAI
• 2020: AAAI
• 2019: AAAI

Reviewing

• 2023: WACV, CVPR, ICLR
• 2022: ICML, WACV, JASA, JUQ
• 2021: AISTATS, ICLR, ICML, IFAC SYSID, NeurIPS
• 2020: AISTATS, ICML, ICML Workshop selection, Nature Communications, NeurIPS, NeurIPS Workshop selection, SPL, STCO
• 2019: AISTATS, ICML, ECC, IEEE Access, IEEE Sensors, NeurIPS,
• 2018: AISTATS, FUSION, IROS, JMLR, NeurIPS
• 2017: AISTATS, Automatica, JMLR, Sensors
• 2016: AISTATS, IEEE TKDE
• 2015: AISTATS, NIPS, IEEE SPL
• 2014: AISTATS, Automatica, NIPS
• 2013: IEEE SMC-C, IEEE TAC, IEEE Signal Processing
• 2012: IEEE ACC

I also review grant proposals (for, e.g., national funding agencies).

Mentoring

• 2022: ICLR Reviewer Mentorship Program

Opponent/Examiner/Dissertation Committee Member

• Martin Jørgensen (2020). “Stochastic Representations with Gaussian Processes and Geometry”. PhD thesis at Technical University of Denmark. Supervised by Prof. Søren Hauberg.
• Jarrad Courts (2021). “State and Parameter Estimation for Nonlinear State-Space Models using Variational Inference”. PhD thesis at University of Newcastle, Australia. Supervised by Prof. Adrian Wills and Dr. Christopher Renton.
• Anton Kullberg (2021). “On Joint State Estimation and Model Learning using Gaussian Process Approximations”. Licentiate Thesis at University of Linköping, Sweden. Supervised by Prof. Gustaf Hendeby and Prof. Isaac Skog.
• Théo Galy-Fajou (2022). “Latent Variable Augmentation for Approximate Bayesian Inference – Applications for Gaussian Processes”. PhD thesis at Technical University of Berlin, Germany. Supervised by Prof. Manfred Opper.