Ademi Adeniji

Email: ademi_adeniji [at] berkeley [dot] edu

I am a Computer Science PhD student at UC Berkeley, advised by Pieter Abbeel. My research focuses on developing generalist agents capable of intelligent decision-making in complex environments. I specialize in leveraging reinforcement learning algorithms to enable agents to autonomously collect diverse data and learn general-purpose behaviors with minimal human supervision. I am supported by the Berkeley Chancellor's Fellowship.

I previously interned at NVIDIA, focusing on reinforcement learning and robotics research, and at Google, where I worked with the SmartHome Automation team. I earned my BS and MS degrees from Stanford University, conducting research in the Stanford Vision and Learning Lab under the guidance of Fei-Fei Li.

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	Language Reward Modulation for Pretraining Reinforcement Learning Ademi Adeniji, Amber Xie, Carmelo Sferrazza, Younggyo Seo, Stephen James, Pieter Abbeel RLC Reinforcement Learning Beyond Rewards Workshop 2024 RLC Training Agents with Foundation Models Workshop 2024 PDF \| Code \| Twitter
	Video Prediction Models as Rewards for Reinforcement Learning Alejandro Escontrela, Ademi Adeniji, Wilson Yan*, Ajay Jain, Xue Bin Peng, Ken Goldberg, Youngwoon Lee, Danijar Hafner, Pieter Abbeel NeurIPS 2023 PDF \| Code \| Blog \| Twitter
	Skill-Based Reinforcement Learning with Intrinsic Reward Matching Ademi Adeniji, Amber Xie, Pieter Abbeel RLC Reinforcement Learning Beyond Rewards Workshop 2024 (Spotlight) RLC Training Agents with Foundation Models Workshop 2024 NeurIPS Intrinsically Motivated Open-ended Learning Workshop 2023 PDF \| Code \| Twitter
	Learning Representations for Unsupervised Skill Discovery Undergraduate Honors Thesis Ademi Adeniji Advisors: L Fei-Fei, Kuan Fang, Animesh Garg, Yuke Zhu 2021 PDF
	Recurrent Control Nets as Central Pattern Generators for Deep Reinforcement Learning Vincent Liu, Ademi Adeniji, Nathaniel Lee, Jason Zhao SURJ 2019 PDF \| BibTex \| Code \| Press
	Latent Actor-Critic with Intrisnic Motivation and Skill Hierarchy Ademi Adeniji, Eva Zhang 2020 PDF
	Latent Skill Transfer for Simulated Agents Ademi Adeniji 2019 PDF
	Volumetric Semantic Segmentation of Glioblastoma Tumors from MRI Studies Ademi Adeniji, Vincent Liu 2019 PDF \| Code
	Sequence-to-Sequence Generative Argumentative Dialogue Systems with Self-Attention Ademi Adeniji, Nate Lee, Vincent Liu 2019 PDF \| Code

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	Language Reward Modulation for Pretraining Reinforcement Learning Ademi Adeniji, Amber Xie, Carmelo Sferrazza, Younggyo Seo, Stephen James, Pieter Abbeel RLC Reinforcement Learning Beyond Rewards Workshop 2024 RLC Training Agents with Foundation Models Workshop 2024 PDF \| Code \| Twitter
	Video Prediction Models as Rewards for Reinforcement Learning Alejandro Escontrela, Ademi Adeniji, Wilson Yan*, Ajay Jain, Xue Bin Peng, Ken Goldberg, Youngwoon Lee, Danijar Hafner, Pieter Abbeel NeurIPS 2023 PDF \| Code \| Blog \| Twitter
	Skill-Based Reinforcement Learning with Intrinsic Reward Matching Ademi Adeniji, Amber Xie, Pieter Abbeel RLC Reinforcement Learning Beyond Rewards Workshop 2024 (Spotlight) RLC Training Agents with Foundation Models Workshop 2024 NeurIPS Intrinsically Motivated Open-ended Learning Workshop 2023 PDF \| Code \| Twitter
	Learning Representations for Unsupervised Skill Discovery Undergraduate Honors Thesis Ademi Adeniji Advisors: L Fei-Fei, Kuan Fang, Animesh Garg, Yuke Zhu 2021 PDF
	Recurrent Control Nets as Central Pattern Generators for Deep Reinforcement Learning Vincent Liu, Ademi Adeniji, Nathaniel Lee, Jason Zhao SURJ 2019 PDF \| BibTex \| Code \| Press
	Latent Actor-Critic with Intrisnic Motivation and Skill Hierarchy Ademi Adeniji, Eva Zhang 2020 PDF
	Latent Skill Transfer for Simulated Agents Ademi Adeniji 2019 PDF
	Volumetric Semantic Segmentation of Glioblastoma Tumors from MRI Studies Ademi Adeniji, Vincent Liu 2019 PDF \| Code
	Sequence-to-Sequence Generative Argumentative Dialogue Systems with Self-Attention Ademi Adeniji, Nate Lee, Vincent Liu 2019 PDF \| Code