I am a fourth-year Ph.D. student in the Algorithm and Complexity department at the Max Planck Institute for Informatics, under the supervision of Kurt Mehlhorn. Prior to joining MPI, I earned my B.Sc. in Computer Engineering with a minor in Mathematics from Sharif University of Technology. Following two internships at MPI, I officially joined the institute in 2019 and obtained my M.Sc. in Computer Science.
My research interests lie in theoretical computer science, with a focus on algorithmic game theory (including fair division and mechanism design). I am specifically interested in exploring algorithms that leverage machine learning predictions to enhance their performance.

• Randomized and Deterministic Maximin-share Approximations for Fractionally Subadditive Valuations
Hannaneh Akrami, Masoud Seddighin, Kurt Mehlhorn, Golnoosh Shahkarami.
Proc. of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

• Learning-Augmented Online TSP on Rings, Trees, Flowers and (almost) Everywhere Else
Evripidis Bampis, Bruno Escoffier, Themis Gouleakis, Niklas Hahn, Kostas Lakis, Golnoosh Shahkarami, Michalis Xefteris.
Proc. of the 31st European Symposium on Algorithms (ESA 2023).

• Learning-Augmented Algorithms for Online TSP on the Line
Themis Gouleakis, Konstantinos Lakis, Golnoosh Shahkarami.
Proc. of the 37th AAAI Conference on Artificial Intelligence (AAAI 2023).

• Maximizing Nash Social Welfare in 2-Value Instances: Delineating Tractability
Hannaneh Akrami, Bhaskar Ray Chaudhury, Martin Hoefer, Kurt Mehlhorn, Marco Schmalhofer, Golnoosh Shahkarami, Giovanna Varricchio, Quentin Vermande, Ernest van Wijland.

• A Novel Prediction Setup for Online Speed-Scaling
Antonios Antoniadis, Peyman Jabbarzade Ganje, Golnoosh Shahkarami.
Proc. of the 18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022).

• Maximizing Nash Social Welfare in 2-Value Instances
Hannaneh Akrami, Bhaskar Ray Chaudhury, Martin Hoefer, Kurt Mehlhorn, Marco Schmalhofer, Golnoosh Shahkarami, Giovanna Varricchio, Quentin Vermande, Ernest van Wijland.
Proc. of the 36th AAAI Conference on Artificial Intelligence (AAAI 2022).

• Nash Social Welfare for 2-value Instances
Hannaneh Akrami, Bhaskar Ray Chaudhury, Kurt Mehlhorn, Golnoosh Shahkarami, Quentin Vermande.

• Physarum-inspired multi-commodity flow dynamics
Vincenzo Bonifaci, Enrico Facca, Frederic Folz, Andreas Karrenbauer, Pavel Kolev, Kurt Mehlhorn, Giovanna Morigi, Golnoosh Shahkarami, Quentin Vermande.
Journal of Theoretical Computer Science (TCS 2022).

• Complexity of Computing the Anti-Ramsey Numbers for Paths
Saeed Akhoondian Amiri, Alexandru Popa, Mohammad Roghani, Golnoosh Shahkarami, Reza Soltani, Hossein Vahidi.
Proc. of the 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020).

• Organizer
  24th Max Planck Advanced Course on the Foundations of Computer Science (ADFOCS'24)


• Program Committee
  ACM Conference on Economics and Computation (EC 2024)


• Reviewer
  ACM-SIAM Symposium on Discrete Algorithms (SODA), European Symposia on Algorithms (ESA), Autonomous Agents and Multiagent Systems (AAMAS), Web and Internet Economics (WINE), Stabilization, Safety, and Security of Distributed Systems (SSS)

• Workshop Instructor
  Forschungstage Informatik 2024
  


• Tutor
  Summer 2021: Core course Optimization
  Winter 2020/21: Advanced course Topics in Algorithmic Game Theory and Economics
  Spring 2019: Bachelor course Game Theory
  Fall 2018: Bachelor course VLSI Design
  Spring 2018: Bachelor course Design of Algorithms
  Spring 2018: Bachelor course Logical Circuits
  Fall 2017: Bachelor course Design of Algorithms
  Fall 2017: Bachelor course Data Structures and Algorithms
  Fall 2016: Bachelor course Data Structures and Algorithms
  Spring 2016: Bachelor course Discrete Structures


• Olympiad Teacher
  2014-2019: Teaching in top high schools; preparing students for Mathematical Olympiad and Olympiad in Informatics.

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