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Computer Science

D-Index
58
Citations
10901
World Ranking
3693
National Ranking
1761

Overview

Mohammad Mahdian is a researcher affiliated with Google in the United States, with a primary focus on computer science. Their scholarly work spans 31 publications, contributing extensively to various subfields including artificial intelligence, management science and operations research, signal processing, marketing, and computer networks and communications.

Their research topics encompass a wide range of areas, notably data management and algorithms, auction theory and applications, privacy-preserving technologies in data, consumer market behavior and pricing, complexity and algorithms in graphs, advanced clustering algorithms, and advanced bandit algorithms.

Mahdian's recent publications illustrate the thematic breadth and interdisciplinary nature of their work:

  • Budget-Management Strategies in Repeated Auctions, 2021, Operations Research
  • Fair Hierarchical Clustering, 2020, arXiv (Cornell University)
  • Auto-Bidding and Auctions in Online Advertising: A Survey, 2024, ACM SIGecom Exchanges
  • Fair Correlation Clustering, 2020, arXiv (Cornell University)
  • Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering, 2021, arXiv (Cornell University)

Throughout their career, Mahdian has regularly published in venues such as arXiv (Cornell University), ACM SIGecom Exchanges, Operations Research, and Mathematics of Operations Research. Their body of work includes 13 publications in arXiv, reflecting an active engagement with open-access scholarly dissemination.

In collaborative research, Mahdian frequently coauthors with several scholars, including:

  • Vahab Mirrokni (12 joint publications)
  • Alessandro Epasto (8 joint publications)
  • Jieming Mao (5 joint publications)
  • Santiago Balseiro (4 joint publications)
  • Yuan Deng (3 joint publications)

This extensive collaboration network supports research spanning multiple dimensions of computer science and operations research. Mahdian's work addresses theoretical and applied aspects in areas such as auctions, clustering algorithms, and privacy technologies, contributing to an understanding of consumer markets and algorithmic complexity.

Best Publications

  • Influence and correlation in social networks

    Aris Anagnostopoulos;Ravi Kumar;Mohammad Mahdian

  • Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP

    Kamal Jain;Mohammad Mahdian;Evangelos Markakis;Amin Saberi

  • A new greedy approach for facility location problems

    Kamal Jain;Mohammad Mahdian;Amin Saberi

  • Limitations of cross-monotonic cost-sharing schemes

    Nicole Immorlica;Mohammad Mahdian;Vahab S. Mirrokni

  • Marriage, honesty, and stability

    Nicole Immorlica;Mohammad Mahdian

  • Comparing and aggregating rankings with ties

    Ronald Fagin;Ravi Kumar;Mohammad Mahdian;D. Sivakumar

  • Dynamics of bid optimization in online advertisement auctions

    Christian Borgs;Jennifer Chayes;Nicole Immorlica;Kamal Jain

  • Improved Approximation Algorithms for Metric Facility Location Problems

    Mohammad Mahdian;Yinyu Ye;Jiawei Zhang

  • Online bipartite matching with random arrivals: an approach based on strongly factor-revealing LPs

    Mohammad Mahdian;Qiqi Yan

  • Tolls for heterogeneous selfish users in multicommodity networks and generalized congestion games

    L. Fleischer;K. Jain;M. Mahdian

  • Packing Steiner trees

    Kamal Jain;Mohammad Mahdian;Mohammad R. Salavatipour

  • Multi-unit auctions with budget-constrained bidders

    Christian Borgs;Jennifer Chayes;Nicole Immorlica;Mohammad Mahdian

  • Approximation Algorithms for Metric Facility Location Problems

    Mohammad Mahdian;Yinyu Ye;Jiawei Zhang

  • Suggesting contacts for social networks

    Malcolm Slaney;Alex Jaffe;Shanmugasundaram Ravikumar;Aris Anagnostopoulos

  • A Cascade Model for Externalities in Sponsored Search

    David Kempe;Mohammad Mahdian

  • Comparing Partial Rankings

    Ronald Fagin;Ravi Kumar;Mohammad Mahdian;D. Sivakumar

  • Allocating online advertisement space with unreliable estimates

    Mohammad Mahdian;Hamid Nazerzadeh;Amin Saberi

  • Online auctions with re-usable goods

    Mohammad T. Hajiaghayi

  • Optimizing the placement of Internet TAPs in wireless neighborhood networks

    R. Chandra;Lili Qiu;K. Jain;M. Mahdian

  • Click fraud resistant methods for learning click-through rates

    Nicole Immorlica;Kamal Jain;Mohammad Mahdian;Kunal Talwar

  • Dynamics of conversations

    Ravi Kumar;Mohammad Mahdian;Mary McGlohon

Frequent Co-Authors

Nicole Immorlica
Nicole Immorlica Microsoft (United States)
Kamal Jain
Kamal Jain Microsoft (United States)
Jennifer Chayes
Jennifer Chayes University of California, Berkeley
Christian Borgs
Christian Borgs University of California, Berkeley
Ravi Kumar
Ravi Kumar Google (United States)
Amin Saberi
Amin Saberi Stanford University
Vahab Mirrokni
Vahab Mirrokni Google (United States)
Uriel Feige
Uriel Feige Weizmann Institute of Science
Sergei Vassilvitskii
Sergei Vassilvitskii Google (United States)
Ranveer Chandra
Ranveer Chandra Microsoft (United States)

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