Éva Tardos

Éva Tardos
Name	Éva Tardos
Birth date	1 August 1963
Birth place	Budapest, Hungary
Nationality	Hungarian-American
Fields	Computer science, Algorithms, Combinatorial optimization
Workplaces	Cornell University, Microsoft Research, IBM Research
Alma mater	Eötvös Loránd University, Eötvös Loránd University (M.Sc.), Eötvös Loránd University (Ph.D.)
Doctoral advisor	Jacob T. Schwartz
Known for	Approximation algorithms, Network flows, Algorithmic game theory
Awards	Knuth Prize, Gödel Prize, EATCS Award

Éva Tardos is a Hungarian-American computer scientist noted for foundational work in algorithms, combinatorial optimization, and algorithmic game theory. She has held a professorship at Cornell University and collaborated with institutions such as Microsoft Research and IBM Research. Tardos's research combines techniques from linear programming, graph theory, game theory, and economics to address network design, routing, and mechanism design problems.

Early life and education

Born in Budapest, Tardos completed early studies at institutions in Hungary before pursuing advanced degrees. She earned degrees from Eötvös Loránd University and undertook doctoral research under the supervision of Jacob T. Schwartz, connecting her work to traditions in computer science and mathematics emanating from Central European schools. During this period she interacted with researchers affiliated with Bell Labs, AT&T, and other research centers that influenced algorithmic research directions in the late 20th century.

Academic career

Tardos joined the faculty of Cornell University, becoming a prominent member of its Department of Computer Science and affiliating with Cornell Tech and related centers. Her career includes visiting and collaborative positions at Microsoft Research, IBM Research, and sabbaticals at universities such as Stanford University and Massachusetts Institute of Technology. She has participated in programs and workshops organized by societies including the Association for Computing Machinery, the Society for Industrial and Applied Mathematics, and the European Association for Theoretical Computer Science.

Research and contributions

Tardos made major contributions to approximation algorithms and network optimization, building on earlier work by researchers like Jack Edmonds, Richard Karp, Vladimir Vazirani, and David Johnson. Her results on approximation schemes, flow algorithms, and performance guarantees advanced understanding of problems studied in venues such as the ACM Symposium on Theory of Computing, the IEEE Symposium on Foundations of Computer Science, and the Journal of the ACM. She introduced techniques combining combinatorial arguments from graph theory with relaxations from linear programming and duality concepts associated with John von Neumann and Kurt Gödel's contemporaries. In algorithmic game theory, her analyses of equilibria and price of anarchy connected to work by Tim Roughgarden, Éva Tardos's contemporaries, and researchers in microeconomics and mechanism design influenced studies in online platforms and networked systems by groups at Google Research, Amazon, and Facebook.

Awards and honors

Tardos's awards include prestigious recognitions from major professional bodies. She received the Gödel Prize and the Knuth Prize and was honored by the European Association for Theoretical Computer Science (EATCS) with the EATCS Award. Her election to academies such as the National Academy of Engineering and affiliations with the Association for Computing Machinery and the American Academy of Arts and Sciences reflect her impact. She has been a keynote or plenary speaker at events including the International Congress of Mathematicians, the Symposium on Discrete Algorithms, and meetings of the Institute of Electrical and Electronics Engineers.

Teaching and mentorship

At Cornell University, Tardos has taught undergraduate and graduate courses in algorithms, optimization, and algorithmic game theory, mentoring doctoral students who have gone on to positions at institutions such as Princeton University, Harvard University, University of California, Berkeley, University of Oxford, ETH Zurich, and industry labs including Microsoft Research and Google Research. Her pedagogical approach builds on traditions from educators linked to Donald Knuth, Robert Tarjan, and Michael Garey, emphasizing rigorous proof techniques and practical applications for systems developed at companies like Cisco Systems and Juniper Networks.

Selected publications and impact

Tardos authored influential papers on approximation algorithms, network flows, and equilibria that appeared in proceedings of the ACM Symposium on Theory of Computing, the IEEE Symposium on Foundations of Computer Science, and journals such as the Journal of the ACM and SIAM Journal on Computing. Her work has been cited in textbooks and monographs by authors like Jon Kleinberg, Éva Tardos's collaborators, and has influenced research programs at centers including INRIA, DIMACS, and CWI. Selected topics include combinatorial optimization foundations, approximation bounds for NP-hard problems related to Cook's theorem and Karp's 21 NP-complete problems, and analyses of strategic behavior in routing and congestion games with connections to Wardrop's principle and classical results in economics.

Category:Computer scientists Category:Hungarian–American scientists