My current research focus is on how to make RL agents learn effectively using knowledge leveraged from humans or other agents. I am interested in various kinds of advice modalities from humans with varying degrees of expertise and want to build systems that can seamlessly integrate such knowledge into a decision making framework. I am also interested in data efficient learning paradigms like active learning and cost-sensitive learning.
I am broadly interested in the theory and applications of Reinforcement Learning in Multi-agent systems (e.g. game and team theory). Specifically, I am working on safety, scalability, convergence and robustness of algorithms in Multi-agent Reinforcement learning.
Curious about the relation between AI and human intelligence. Interested in applying Reinforcement learning to human-intelligence tasks, especially language learning and understanding.
I believe that I am in a continuous and life long process of learning which drives my passion for trying out new technologies and learning new skills. My interest areas include Reinforcement Learning, Deep Learning, Machine Learning, and Natural Language Processing.
My research interests are representation learning, reinforcement learning and machine learning with a focus on building general-purpose AI agents. My previous research experience in computer vision and deep learning.
I have past experience in Computer Vision, Robotics, Data Mining and Natural Language Processing. Currently, my main interest is in the field of Reinforcement Learning
I have a background in electronic and telecommunication with 3 years experience working as a radio engineer. I'm in the AMMI (African Master in Machine Intelligence) and am interested in Reinforcement Learning, autonomous navigation and multiagent systems.
Interested in the intersection between AI and psychology and how to apply human learning methods to AI agents. My research interests includes reinforcement learning and deep learning.
My research interests are an intersection between human and AI, how human can help agents to improve, or agents can help human to learn. I am interested in Reinforcement Learning, Natural Language Processing and Deep learning.
Team Lead for Undergrad Cohort, lead developer of HIPPO Gym, and team member for Thunderblade project.
Currently working on the SoundHunters to personalize learning of Cree Sounds with User Modelling and Machine Learning.
Currently working on the Human-AI interaction system for latent fingerprint
Thesis: The Impact of Different Summaries as Reinforcement Learning Explanations on Human Performance And Perception,
Thesis: Transfer in Deep Reinforcement Learning: How an Agent Can Leverage Knowledge From Another Agent, A Human, or Itself, Spring 2021
Thesis: Knowledge Transfer in Reinforcement Learning: How Agents Should Benefit from Prior Knowledge, Fall 2019
Thesis: Teaching Effectiveness of Intelligent Tutoring Systems, Spring 2019
Thesis: Learning from Human Teachers — Supporting How People Want to Teach in Interactive Machine Learning, Summer 2018
Thesis: TINGLE — Topic-Independent Gamification Learning Environment, Summer 2018
Thesis: Policy Advice, Non-convex and Distributed Optimization in Reinforcement Learning, Fall 2016
Thesis: Regret Minimization with Function Approximation in Extensive-Form Games, Summer 2020
Thesis: Useful Policy Invariant Shaping from Arbitrary Advice, Winter 2020
Thesis: Accelerate the Learning Speed of Deep Reinforcement Learning by Pre- training with Non-Expert Human Demonstrations, Spring 2019
Thesis: Engineering a Smart Scarecrow: Bird Deterrence with Drones, Spring 2017
Thesis: Development of the Baton: A Novel Precision Delivery Drone, Summer 2017
Thesis: Modifying Smart Home to Smart Phone Notifications using Reinforcement Learning Algorithms, Spring 2017