ΑΙhub.org
 

Maria Gini wins the 2022 ACM/SIGAI Autonomous Agents Research Award


by
17 January 2022



share this:
trophy

Congratulations to Professor Maria Gini on winning the ACM/SIGAI Autonomous Agents Research Award for 2022! This prestigious prize recognises years of research and leadership in the field of robotics and multi-agent systems.

Maria Gini is Professor of Computer Science and Engineering at the University of Minnesota, and has been at the forefront of the field of robotics and multi-agent systems for many years, consistently bringing AI into robotics.

Her work includes the development of:

  • novel algorithms to connect the logical and geometric aspects of robot motion and learning,
  • novel robot programming languages to bridge the gap between high-level programming languages and programming by guidance,
  • pioneering novel economic-based multi-agent task planning and execution algorithms.

Her work has spanned both the design of novel algorithms and practical applications. These applications have been utilized in settings as varied as warehouses and hospitals, with uses such as surveillance, exploration, and search and rescue.

Maria has been an active member and leader of the agents community since its inception. She has been a consistent mentor and role model, deeply committed to bringing diversity to the fields of AI, robotics, and computing. She is also the former President of International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Maria will be giving an invited talk at AAMAS 2022. More details on this will be available soon on the conference website.




AIhub is dedicated to free high-quality information about AI.
AIhub is dedicated to free high-quality information about AI.

            AIhub is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Relational neurosymbolic Markov models

and   19 Feb 2026
Relational neurosymbolic Markov models make deep sequential models logically consistent, intervenable and generalisable

AI enables a Who’s Who of brown bears in Alaska

  18 Feb 2026
A team of scientists from EPFL and Alaska Pacific University has developed an AI program that can recognize individual bears in the wild, despite the substantial changes that occur in their appearance over the summer season.

Learning to see the physical world: an interview with Jiajun Wu

and   17 Feb 2026
Winner of the 2019 AAAI / ACM SIGAI dissertation award tells us about his current research.

3 Questions: Using AI to help Olympic skaters land a quint

  16 Feb 2026
Researchers are applying AI technologies to help figure skaters improve. They also have thoughts on whether five-rotation jumps are humanly possible.

AAAI presidential panel – AI and sustainability

  13 Feb 2026
Watch the next discussion based on sustainability, one of the topics covered in the AAAI Future of AI Research report.

How can robots acquire skills through interactions with the physical world? An interview with Jiaheng Hu

  12 Feb 2026
Find out more about work published at the Conference on Robot Learning (CoRL).

From Visual Question Answering to multimodal learning: an interview with Aishwarya Agrawal

and   11 Feb 2026
We hear from Aishwarya about research that received a 2019 AAAI / ACM SIGAI Doctoral Dissertation Award honourable mention.

Governing the rise of interactive AI will require behavioral insights

  10 Feb 2026
Yulu Pi writes about her work that was presented at the conference on AI, ethics and society (AIES 2025).



AIhub is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence