University of Wisconsin Professor Recognized for Breakthrough Techniques in Algorithm Design
Ilias Diakonikolas Transformed Robust Statistics through Efficient Algorithms
New York, NY, May 21, 2025 – ACM, the Association for Computing Machinery, today announced that Ilias Diakonikolas, a Professor at the University of Wisconsin, Madison, is the recipient of the 2024 ACM Grace Murray Hopper Award. He is cited for making contributions to the field of algorithmic robust statistics by introducing new techniques to robustly estimate high-dimensional distributions along with a surprising variety of algorithmic applications.
Diakonikolas will formally receive the Grace Murray Hopper Award at ACM’s annual awards banquet on June 14, 2025 in San Francisco.
The primary focus of Diakonikolas' work is the mathematical foundations of data analysis, machine learning and algorithmic statistics. He is most well-known for his work on robust statistical algorithms for high-dimensional data. “Robust algorithms” are algorithms that perform well even when the data significantly deviates. The new paradigms that Diakonikolas developed changed the way we think about what is possible for efficient algorithms that process high-dimensional data—overcoming problems that have stymied researchers since the 1960s.
In 2016, Diakonikolas and collaborators gave the first efficient algorithms for learning the parameters of a high-dimensional distribution. These breakthrough algorithms are robust to arbitrary corruption in a constant fraction of data, with the constant being independent of the dimension. Subsequent work by Diakonikolas showed these new methods are not only of theoretical interest but can be made practical. In turn, these new methods can also be used to tackle more complex robust high-dimensional statistical problems. In mixtures of distributions, for example, there are cases where Diakonikolas’ algorithms are more efficient than even the prior state-of-the-art non-robust methods. Among other applications, robust algorithms are critical in order to develop reliable machine learning systems.
In addition to his breakthrough research contributions, Diakonikolas has also played a leading role in establishing a vibrant community around this work. He has organized workshops, given tutorials, and co-authored (with Daniel Kane) Algorithmic High-Dimensional Robust Statistics, a new textbook which has become an essential resource for this emerging field.
About ACM
ACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting educators, researchers, and professionals to inspire dialogue, share resources, and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.
About ACM Grace Murray Hopper Award
Awarded 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 of the Grace Murray Hopper Award is provided by Microsoft.
Contact:
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