Kristian Hartikainen

London
United Kingdom

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I am a Ph.D. student at Whiteson Research Lab (WhiRL) at University of Oxford, advised by Shimon Whiteson. My research interests are in machine learning and robotics, and recently I've focused on model-free deep reinforcement learning for real-world robotic control. I also spend my time working on open-source projects like Ray and Softlearning.

Prior to joining WhiRL, I did research at Robotic AI and Learning Lab (RAIL) at the University of California, Berkeley, where I worked with Sergey Levine and Tuomas Haarnoja. I also spent a couple years as a software engineer in the industry, building statistical analysis and machine learning products at Statwing and Qualtrics.

Most recently, I did a research internship at DeepMind.

Publications and Preprints

  • Matthew Fellows, Kristian Hartikainen, and Shimon Whiteson. Bayesian Bellman Operators. Neural Information Processing Systems (NeurIPS). 2021.

    paper

  • Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, and Shimon Whiteson. Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. International Conference on Machine Learning (ICML). 2021.

    paper | code

  • Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja*, and Sergey Levine*. Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery. 8th International Conference on Learning Representations (ICLR). 2020.

    paper | videos

  • Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, and Sergey Levine. The Ingredients of Real-World Robotic Reinforcement Learning. 8th International Conference on Learning Representations (ICLR). 2020.

    paper | videos

  • Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar. ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. 3rd Conference on Robot Learning (CoRL). 2019.

    paper | videos | code

  • Avi Singh, Larry Yang, Kristian Hartikainen, Chelsea Finn, and Sergey Levine. End-to-End Robotic Reinforcement Learning without Reward Engineering. Robotics: Science and Systems (RSS). 2019.

    paper | videos | code

  • Tuomas Haarnoja*, Aurick Zhou*, Kristian Hartikainen*, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, and Sergey Levine. Soft Actor-Critic Algorithms and Applications. arXiv preprint arXiv:1812.05905. 2018.

    paper | videos | code

  • Tuomas Haarnoja*, Kristian Hartikainen*, Pieter Abbeel, and Sergey Levine. Latent Space Policies for Hierarchical Reinforcement Learning. International Conference on Machine Learning (ICML). 2018.

    paper | videos | code

Research Experience

Research Intern

DeepMind. With Nicolas Heess, Tuomas Haarnoja.

Research Staff

Robotics and AI Lab, University of California, Berkeley. With Sergey Levine, Tuomas Haarnoja.

Research Assistant

Machine Learning for Big Data Group, Aalto University. With Alexander Jung.

Research Assistant

Embedded Systems Group, Aalto University. With Vesa Hirvisalo, Heikki Saikkonen.

Industry Experience

Software Engineer 2

Qualtrics, LLC.

Software Engineer

Statwing, Inc.

Data Scientist/Software Engineer

Wolt Enterprises Oy

Software Engineer

Statwing, Inc.

Education

Ph.D. in Computer Science

University of Oxford
United Kingdom

Reinforcement learning, robotics

M.Sc. in Computer Science (5.0/5.0)

Aalto University
Finland

Software technology, machine learning

Thesis: Performance Analysis of Packet Processing Systems (with distinction)

B.Sc. in Computer Science

Aalto University
Finland

Software technology, industrial management

Thesis: Methods for Adaptive User Interfaces (with distinction)

Open-Source