Risto Vuorio

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I am a Ph.D. student at Whiteson Research Lab at University of Oxford. My research is focused on Meta-Reinforcement Learning (Meta-RL). I'm excited about developing Deep RL into a practical technology and I believe Meta-RL is a good framework for making progress on that.

Before joining WhiRL, I worked with Satinder Singh at the University of Michigan on meta-gradient reinforcement learning. And before that, I worked at SK-Telecom AI Research Lab in Seoul. I got my Master's in Computer Science at Aalto University, Finland.


A Survey of Meta-Reinforcement Learning

Jacob Beck (equal contribution), Risto Vuorio (equal contribution), Evan Zheran Liu, Zheng Xiong, Luisa Zintgraf, Chelsea Finn, and Shimon Whiteson. arxiv. 2023. paper

Deconfounded Imitation Learning

Risto Vuorio, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen, and Pim de Haan. NeurIPS Deep RL Workshop. 2022. paper

Hypernetworks in Meta-Reinforcement Learning

Jacob Beck, Matthew Thomas Jackson, Risto Vuorio, and Shimon Whiteson. Conference on Robot Learning (CoRL). 2022. paper

Pairwise Weights for Temporal Credit Assignment

Zeyu Zheng (equal contribution), Risto Vuorio (equal contribution), Richard Lewis, and Satinder Singh. AAAI. 2022. paper

An Investigation of the Bias-Variance Tradeoff in Meta-Gradients

Risto Vuorio, Jacob Beck, Gregory Farquhar, Jakob Foerster, Shimon Whiteson. NeurIPS Deep RL Workshop. 2021. paper

Learning State Representations from Random Deep Action-conditional Predictions

Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard Lewis, Satinder Singh. NeurIPS. 2021. paper

On the Practical Consistency of Meta-Reinforcement Learning Algorithms

Zheng Xiong, Luisa Zintgraf, Jacob Beck, Risto Vuorio, Shimon Whiteson. NeurIPS Meta-Learning Workshop. 2021.

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation

Risto Vuorio (equal contribution), Shao-Hua Sun (equal contribution), Hexiang Hu, and Joseph J. Lim. NeurIPS (Spotlight). 2019. paper

Deep Reinforcement Learning for Dynamic Multi-Driver Dispatching and Repositioning Problem

John Holler (equal contribution), Risto Vuorio (equal contribution), Tiancheng Jin, Satinder Singh, Zhiwei Qin, Jieping Ye, Xiaocheng Tang, Yan Jiao, and Chenxi Wang. ICDM Short Paper. 2019. paper

Toward Multimodal Model-Agnostic Meta-Learning

Risto Vuorio, Shao-Hua Sun, Hexiang Hu and Joseph J. Lim. NeurIPS Meta-Learning Workshop. 2018. paper

Meta Continual Learning

Risto Vuorio, Subin Yi, Dong-Yeon Cho, Daejoong Kim and Jiwon Kim. NeurIPS Continual Learning Workshop. 2018. paper


Ph.D. Computer Science

University of Oxford

M.Sc. Computer Science (with distinction)

Aalto University
Helsinki, Finland

Minor: Mathematics

Thesis: Stream Processing on a Multi-core DSP with Open Event Machine

B.Sc. Industrial Management

Aalto University
Helsinki, Finland

Minor: Software Technology

Research Experience

Research Intern

Qualcomm Research, Amsterdam

Advised by Taco Cohen, Daniel Dijkman

Visiting Scholar

University of Michigan, Ann Arbor

Advised by Satinder Singh

Research Engineer

SK Telecom, T-Brain

Advised by Jiwon Kim, Joseph J. Lim

Research Assistant

Machine Learning for Big Data Group, Aalto University

Advised by Alexander Jung

Research Assistant

Embedded Systems Group, Aalto University

Advised by Vesa Hirvisalo, Heikki Saikkonen

Industry Experience

Data Scientist/Software Engineer

Wolt Enterprises Oy

Software Engineer

Apportable Inc

Service and Activities

Junior Organizer:

NeurIPS Deep RL Workshop 2022.

Program Committee:

ICML 2022.

AAAI 2021, 2022.

NeurIPS Deep Reinforcement Learning Workshop 2019, 2020, 2021.

ICML Pre-Training Workshop 2022.