ΑΙhub.org
 

Congratulations to the #IJCAI2021 award winners


by
01 July 2021



share this:
winners' medal

The winners of three IJCAI awards have been announced. These three distinctions are: the Award for Research Excellence, the John McCarthy Award and the Computers and Thought Award.

IJCAI-21 Award for Research Excellence

The Research Excellence award is given to a scientist who has carried out a program of research of consistently high quality throughout an entire career yielding several substantial results.

The winner of the 2021 Award for Research Excellence is Richard Sutton (University of Alberta). Richard is recognized for his fundamental contributions to the foundation of reinforcement learning.

IJCAI-21 Computers and Thought Award

This award is presented to outstanding young scientists in artificial intelligence.

The winner of the 2021 IJCAI Computers and Thought Award is Fei Fang (Carnegie Mellon University). Fei is recognized for her contributions to integrating machine learning with game theory and the use of these novel techniques to tackle societal challenges, such as more effective deployment of security resources, enhancing environmental sustainability, and reducing food insecurity.

IJCAI-21 John McCarthy Award

This award is intended to recognize established mid-career researchers, typically between fifteen to twenty-five years after obtaining their PhD, that have built up a major track record of research excellence in artificial intelligence.

The winner of the 2021 John McCarthy Award is Tuomas Sandholm (Carnegie Mellon University). Thomas is recognized for his significant research contributions to multiagent systems, computational economics, optimization and game playing, and their application in real-world settings.


The recipients were selected on the recommendation of the IJCAI-21 Awards Selection Committee:
Thomas Eiter, Vienna University of Technology, Austria
Maria Gini, University of Minnesota Twin Cities, USA
Luc De Raedt, KU Leuven, Belgium
Dan Roth, University of Pennsylvania, USA
Chengqi Zhang, University of Technology Sydney, Australia
Qiang Yang, Hong Kong University of Science and Technology, Hong Kong, China (Chair)



tags:


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.

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