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.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

coffee corner

AIhub coffee corner: World models

  22 May 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.

Why the world’s banks are so worried about Anthropic’s latest AI model

  21 May 2026
The finance world’s concern rests on the impressive cyber capabilities of a product called Mythos.

Embracing empiricism – from the lottery hypothesis to creating real-world impact: an interview with Jonathan Frankle

  20 May 2026
Jonathan Frankle discusses empiricism, making an impact, and the legacy of his lottery ticket hypothesis for which he was awarded the 2023 AAAI/ACM Doctoral Dissertation Award.

A faster way to estimate AI power consumption

  19 May 2026
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

Introducing ARFBench: A time series question-answering benchmark based on real incidents

  18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.

Does ‘federated unlearning’ in AI improve data privacy, or create a new cybersecurity risk?

  15 May 2026
As the capacity of AI systems increases apace, so do concerns about the privacy of user data.

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence