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.


I offer strategic and technical consulting services to businesses seeking to integrate AI solutions into their core operations. Leveraging my extensive experience at McKinsey & Company and Stanford Consulting, I have successfully served clients in the technology, financial services, real estate, and food and beverage industries. For inquiries, please reach out via email.

Language Reward Modulation for Pretraining Reinforcement Learning
Ademi Adeniji, Amber Xie, Carmelo Sferrazza, Younggyo Seo, Stephen James, Pieter Abbeel
RLC Training Agents with Foundation Models Workshop 2024
RLC Reinforcement Learning Beyond Rewards 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 Training Agents with Foundation Models Workshop 2024
RLC Reinforcement Learning Beyond Rewards 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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