Papers
2
Total Citations
114
H-Index
2
About
Marie desJardins is a leading researcher in artificial intelligence, with a primary focus on human-robot interaction, natural language grounding, and planning under uncertainty. Her groundbreaking work bridges the gap between how humans communicate and how robots understand and execute tasks. In her highly cited 2015 paper (65 citations), she pioneered methods for grounding English commands directly into reward functions, enabling robots to learn from natural language and demonstration—a critical step toward making intelligent robots more accessible to non-experts. Her 2017 work on planning with Abstract Markov Decision Processes (49 citations) introduced hierarchical abstraction techniques that allow robots to efficiently plan under uncertainty in large, dynamic state-action spaces, even as reward functions shift with changing goals. Beyond these contributions, desJardins has been a tireless advocate for broadening participation in AI and computing, serving as a mentor and leader in diversity initiatives. Her research has profoundly impacted the development of robots that can operate fluidly in human environments, making her a pivotal figure in creating more intuitive, adaptable, and intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Grounding English Commands to Reward Functions65 citations · 2015
- 2Planning with Abstract Markov Decision Processes49 citations · 2017