About me

I am a second-year Ph.D. student in the multidisciplinary program Algorithms, Combinatorics and Optimization / Computer Science (ACO/CS) at Georgia Tech. I am fortunate to be advised by Santosh Vempala. I have completed my M.Sc. in Computer Science at the University of British Columbia, under supervision of Bruce Shepherd and Mark Schmidt. Previously, I received my B.Sc. in Computer Engineering Department from Sharif University of Technology.
My research is in optimization and areas related to optimization, including machine learning and algorithms.

Research Interests

• Combinatorial and Convex Optimization
• Design and Analysis of Algorithms, Approximation and Randomized Algorithms
• Theoretical Machine Learning, Theoretical Aspects of Deep Learning, Tensor Decomposition
• Machine Learning, Fairness, Diffrerential Privacy, Data Mining

Education

• Ph.D. in ACO/CS 2019 - present
  Algorithms, Combinatorics, and Optimization / Computer Science, Georgia Institute of Technology
  Advisor: Santosh Vempala
  Minor: Algebraic and Enumerative Combinatorics.
• M.Sc. in Computer Science 2017 - 2019
  Department of Computer Science, University of British Columbia
  Advisors: Bruce Shepherd and Mark Schmidt
  Thesis title: "Beyond Submodular Maximization: One-Sided Smoothness and Meta-Submodularity"
• B.Sc. in Computer Engineering 2011 - 2016
  Department of Computer Engineering, Sharif University of Technology
  Advisor: Hamid Zarrabi-Zadeh
  Thesis title: "Discrete Voronoi Game"

Work Experience

• Research intern in Algorithms and Optimization Team at Google. May 2021 - present
  Hosts: Matthew Fahrbach and Thomas Fu.
  Working on tensor decomposition methods for deep neural network applications.

Awards and Honors

• The Machine Learning Center at Georgia Tech (ML@GT) Fellowship. 2021
• Institute for Data Engineering and Science (IDEaS) and Transdisciplinary Research Institute for Advancing Data Science (TRIAD) Research Scholarship for Ph.D. Students and Postdocs. 2020
• Borealis AI Global Fellowship Award 2018
• Silver Medal at Iranian National Mathematical Olympiad 2010

Working Papers

• Fast Low-Rank Tensor Decomposition by Ridge Leverage Score Sampling 2021
  M. Fahrbach, M. Ghadiri, and T. Fu
  pdf
• A Parameterized Family of Meta-Submodular Functions 2020
  M. Ghadiri, R. Santiago, and B. Shepherd
  pdf

Publications

• Socially Fair k-Means Clustering FAccT 2021
  M. Ghadiri, S. Samadi, and S. Vempala
  pdf
• Beyond Submodular Maximization via One-Sided Smoothness SODA 2021
  M. Ghadiri, R. Santiago, and B. Shepherd
  pdf
• Distributed Maximization of Submodular Plus Diversity Functions for Multi-label Feature Selection on Huge Datasets AISTATS 2019
  M. Ghadiri and M. Schmidt
  pdf
• Scalable Feature Selection via Distributed Diversity Maximization AAAI 2017
  M. Ghadiri^*, S. Abbasi Zadeh^*, M. Zadimoghaddam and V. Mirrokni (* equal contribution)
  [Oral Presentation]
  pdf
• A Multiscale Agent-Based Framework Integrated with a Constraint-Based Metabolic Network Model of Cancer
  for Simulating Tumor Growth Molecular BioSystems Journal 2017
  M. Ghadiri^*, M. Heidari^*, S. H. Mousavi and S. A. Marashi (* equal contribution)
  
  Link
• Linear Relaxations for Finding Diverse Elements in Metric Spaces NIPS 2016
  A. Bhaskara, M. Ghadiri, V. Mirrokni and O. Svensson
  
  pdf
• Minimizing the Total Movement for Movement to Independence Problem on a Line CCCG 2016
  M. Ghadiri and S. Yazdanbod
  
  pdf
• Active Distance-Based Clustering using K-medoids PAKDD 2016
  M. Ghadiri^*, A. Aghaee^*, M. Soleymani Baghshah (* equal contribution)
  
  pdf

Workshops

• Amortized rejection sampling in universal probabilistic programming PROBPROG 2020
  S. Naderiparizi, A. Scibior, A. Munk, M. Ghadiri, A. G. Baydin, B. G. Hansen, C. S. de Witt, R. Zinkov, P. Torr, T. Rainforth, Y. W. Teh, F. Wood
  pdf
• Efficient Bayesian Inference for Nested Simulators AABI 2019
  B. G. Hansen, C. S. de Witt, R. Zinkov, S. Naderiparizi, A. Scibior, A. Munk, F. Wood, M. Ghadiri, P. Torr, Y. W. Teh, A. G. Baydin, T. Rainforth
  
  pdf

Presentations

• Socially Fair k-Means Clustering
  (Canadian Discrete and Algorithmic Mathematics Conference (CanaDAM)) May 2021
• Beyond Submodular Maximization via One-Sided Smoothness and Meta-Submodularity (Google Research) January 2021
• In Search of Tractable Supermodular Maximization Problems
  (Canadian Discrete and Algorithmic Mathematics Conference (CanaDAM)) May 2019
• Beyond Submodular Maximization (Bellairs Workshop on Discrete Optimization) April 2019
• Scalable Feature Selection via Distributed Submodular and Diversity Maximization (Element AI Research Workshop) August 2018