Aleksei Petrenko

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	All	Since 2020
Citations	375	374
h-index	8	8
i10-index	8	8

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20192020202120222023202420251 4 17 45 107 193 8

Co-authors

Arthur AllshireUC BerkeleyVerified email at berkeley.edu
Ankur HandaPrincipal Research Scientist, NVIDIAVerified email at doc.ic.ac.uk
Gaurav SukhatmeProfessor, Departments of CS and ECE, USCVerified email at usc.edu
Viktor MakoviychukChief Scientist, CloneVerified email at clonerobotics.com
Zhehui HuangPh.D. student of computer science, University of Southern CaliforniaVerified email at usc.edu
Tushar KumarSoftware Engineer, Nimble RoboticsVerified email at usc.edu
Vladlen KoltunDistinguished Scientist, AppleVerified email at apple.com
Sumeet BatraUniversity of Southern CaliforniaVerified email at usc.edu
Denys MakoviichukMachine Learning Engineering ManagerVerified email at snap.com
Artem MolchanovApplied Research Scientist, NVidiaVerified email at nvidia.com
Erik WijmansAppleVerified email at apple.com
Kayvon FatahalianAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Dhruv BatraPrev: FAIR (Meta AI), Georgia TechVerified email at dhruvbatra.com
Manolis SavvaSimon Fraser UniversityVerified email at sfu.ca
Shashank HegdeUniversity of Southern CaliforniaVerified email at usc.edu
Anssi KanervistoResearcher, Meta FAIRVerified email at meta.com
Dieter FoxUniversity of Washington and NVIDIAVerified email at cs.washington.edu

Aleksei Petrenko

Research Scientist at Apple, Computer Science PhD from the University of Southern California

Verified email at apple.com - Homepage

reinforcement learning deep reinforcement learning deep learning systems robotics


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Dextreme: Transfer of agile in-hand manipulation from simulation to reality A Handa, A Allshire, V Makoviychuk, A Petrenko, R Singh, J Liu, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 5977-5984, 2023	131*	2023
Sample factory: Egocentric 3d control from pixels at 100000 fps with asynchronous reinforcement learning A Petrenko, Z Huang, T Kumar, G Sukhatme, V Koltun International Conference on Machine Learning, 7652-7662, 2020	102	2020
Decentralized control of quadrotor swarms with end-to-end deep reinforcement learning S Batra, Z Huang, A Petrenko, T Kumar, A Molchanov, GS Sukhatme Conference on Robot Learning, 576-586, 2022	52	2022
Large batch simulation for deep reinforcement learning B Shacklett, E Wijmans, A Petrenko, M Savva, D Batra, V Koltun, ... International Conference on Learning Representations, 2021, 2021	27	2021
Megaverse: Simulating embodied agents at one million experiences per second A Petrenko, E Wijmans, B Shacklett, V Koltun International Conference on Machine Learning, 8556-8566, 2021	22	2021
Dexpbt: Scaling up dexterous manipulation for hand-arm systems with population based training A Petrenko, A Allshire, G State, A Handa, V Makoviychuk arXiv preprint arXiv:2305.12127, 2023	14	2023
Proximal policy gradient arborescence for quality diversity reinforcement learning S Batra, B Tjanaka, MC Fontaine, A Petrenko, S Nikolaidis, G Sukhatme arXiv preprint arXiv:2305.13795, 2023	10	2023
Agents that listen: High-throughput reinforcement learning with multiple sensory systems S Hegde, A Kanervisto, A Petrenko 2021 IEEE Conference on Games (CoG), 1-5, 2021	10	2021
Quadswarm: A modular multi-quadrotor simulator for deep reinforcement learning with direct thrust control Z Huang, S Batra, T Chen, R Krupani, T Kumar, A Molchanov, A Petrenko, ... arXiv preprint arXiv:2306.09537, 2023	7	2023
Ai-based control for robotics systems and applications A Handa, AD Allshire, V Makoviichuk, AV Petrenko US Patent App. 18/330,905, 2024		2024
Training machine learning models using simulation for robotics systems and applications A Handa, AD Allshire, D Fox, JFV Lafleche, LIU Jingzhou, V Makoviichuk, ... US Patent App. 18/448,049, 2024		2024

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