Erdal Arikan Receives Kanellakis Award
Erdal Arikan, Professor, Bilkent University, receives the ACM Paris Kanellakis Theory and Practice Award for the discovery of channel polarization and the construction of polar codes – the first explicit, capacity-achieving codes with efficient encoding and decoding adopted in global wireless standards.
The transition of polar codes from a profound theoretical milestone to a cornerstone of modern communication infrastructure represents an extraordinary achievement in the field of computing.
The ACM Paris Kanellakis Theory and Practice Award honors specific theoretical accomplishments that have had a significant and demonstrable effect on the practice of computing. This award is accompanied by a prize of $10,000 and is endowed by contributions from the Kanellakis family, with additional financial support provided by ACM’s Special Interest Groups on Algorithms and Computation Theory (SIGACT), Design Automation (SIGDA), Management of Data (SIGMOD) and Programming Languages (SIGPLAN), the ACM SIG Projects Fund and individual contributions.
ACM – AAAI Recognises Kevin Leyton-Brown for Contributions to AI
Kevin Leyton-Brown, Professor, University of British Columbia, receives the ACM – AAAI Allen Newell Award for fundamental contributions to artificial intelligence and machine learning, focusing on applications to multiagent systems, heuristic algorithms, social impact and market design. Leyton-Brown has made numerous significant contributions to artificial intelligence, specifically in the areas of computational economics and game theory and automatedconfiguration/design of algorithms using machine learning.
The ACM – AAAI Allen Newell Award is presented to an individual selected for career contributions that have breadth within computer science, or that bridge computer science and other disciplines. The Newell award is accompanied by a prize of $10,000, provided by ACM and the Association for the Advancement of Artificial Intelligence (AAAI), and by individual contributions.
Ben Mildenhall and Pratul Srinivasan Receive ACM Grace Murray Hopper Award
Ben Mildenhall, co-founder, World Labs, and Pratul Srinivasan, Research Scientist, Google DeepMind, are the recipients of the ACM Grace Murray Hopper Award.
They are cited for contributions to radiance field representations, 3D scene capture and rendering and for pioneering neural implicit representations and 3D generative AI.
Their contributions underpin widely deployed systems in major products including immersive mapping, 3D commerce and large-scale scene visualisation, and have been adopted across leading technology companies.
The ACM Grace Murray Hopper Award is given to the outstanding young computer professional of the year, selected on the basis of a single recent major technical or service contribution. This award is accompanied by a prize of $35,000. The candidate must have been 35 years of age or less at the time the qualifying contribution was made. Financial support for this award is provided by Microsoft. Read the ACM news release.
University of Washington Grad Earns ACM Doctoral Dissertation Award
Allen Liu is the recipient of the ACM Doctoral Dissertation Award for his dissertation “Learning Theoretic Foundations for Understanding Quantum Systems” toward a PhD earned at MIT.
Liu’s thesis reshapes our understanding of quantum systems through perspectives in learning theory. The quantum computing community is still trying to unravel the far-reaching implications of his work.
Honourable Mentions go to Gal Arnon for his dissertation “New Advancements in Interactive Oracle Proofs: Theory, Practice, and Limitations” toward a PhD earned at the Weizmann Institute of Science; and to Rachit Nigam for his dissertation “Modular Abstractions for Efficient Hardware Design” toward a PhD earned at Cornell University. Read the news release.
Featured ACM Member: Sheelagh Carpendale
Sheelagh Carpendale is a Canada Research Chair and Professor at Simon Fraser University (SFU). At SFU, she directs the InnoVis (Innovations in Visualization) Research Group, and she co-founded and co-directs Interactive Experiences (ixLab).
She combines information visualization and human-computer interaction with innovative new interaction techniques to better support the everyday practices of people who are viewing, representing, and interacting with information.
Carpendale has authored two books, 200+ research articles and presented at more than 20 exhibits and installations. Among her numerous honours, she is a Fellow of the Royal Society of Canada (RSC), an IEEE Fellow and was inducted into the ACM CHI Academy and the IEEE Visualization Academy. Carpendale was recently named an ACM Fellow for contributions to expanding the diversity of data comprehension through innovative interactive visualisations.
In her interview, she discusses her artistic background and data visualization, how sounds from Antarctica can inspire musical composition, why many people feel uncomfortable with data these days, and more. Read Carpendale’s interview here.
ACM TechTalk: Val Andrei Fajardo
View the recent ACM Techtalk “Inside an LLM Agent: A From-Scratch Walkthrough” with Val Andrei Fajardo, Principal AI Engineer and Researcher on the AI and Data Leadership Team at The Carlyle Group.
Everybody’s talking about AI agents. But what’s actually inside one when you strip away the framework? In this talk,
Fajardo walks through the internals of an LLM agent from scratch. No CrewAI, no LangGraph, no black boxes. Just the raw building blocks: tool abstraction, the agent processing loop, MCP integration and the Agent Skills open standard (plus a sneak peek at the upcoming memory chapter). Through live examples, you’ll see exactly what’s happening under the hood of the agent clients you use every day and how to build them yourself.
ACM TechTalk: Bertrand Meyer
View the recent ACM Techtalk “Software Verification in the Age of Artificial Intelligence” with Bertrand Meyer, Professor of Software Engineering and Provost at the Schaffhausen Institute of Technology in Switzerland and CTO of Eiffel Software
The AI tsunami is transforming every aspect of software engineering. What does it hold in store for the world’s software and for the profession itself? Beyond the buzz, can “vibe coding” scale up to the production of the high-quality systems the world increasingly requires? How do these evolutions affect testing and software verification?
The talk will address these questions and, more generally, analyse what software development will look like in the new, AI-rich world, focusing on the need for a modern form of software verification, supported by advanced tools and combining the best of dynamic techniques (tests) and static ones (proofs), all supported by AI agents.
ACM ByteCast: Cynthia Rudin
In this episode of ACM ByteCast, Rashmi Mohan hosts ACM Fellow Cynthia Rudin, the Gilbert, Louis and Edward Lehrman Distinguished Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics and Biostatistics and Bioinformatics at Duke University, where she leads the Interpretable Machine Learning Lab.
Her lab, which seeks to design predictive ML models that people can understand, focuses on areas including healthcare, criminal justice and energy reliability. Rudin was recently named an ACM Fellow for contributions to and leadership in interpretable machine learning and societal applications.
Here Rudin clarifies the crucial distinction between “interpretable” and “explainable” AI and makes the argument that true interpretability is foundational to trustworthy, ethical AI. She shares her extensive field experience collaborating with Con Edison engineers on power grid maintenance, neurologists on medical diagnostics and the Cambridge Police Department on crime series detection, and more.