A short list of my experiences

Game Theory

  • Currently doing research on Online Stochastic Matching (Here is a post about it)
  • Read “Game Theory, alive” by Karlin and Peres: Chapters 1 to 8, 10, 14 and “Algorithmic Game Theory” book by Nisan et al. chapters 1,2,4,9.
  • Video lectures from prof. Tim Roughgarden’s Algorithmic Game Theory (10 first lectures); Lecture notes from prof. Aaron Roth’s Algorithmic Game Theory (9 first lectures, Online Learning Part)
  • Attended a short course on Information Design by prof. Nima Haghpanah

Statistical Machine Learning

  • Passed related courses with distinctive qualifications such as Stochastic Process, Data Mining and audited Statistical Machine Learning, and Probabilistic Graphical Models.
  • Teaching Assistant in probability and statistics
  • Related Academic Projects
  • A post about “When and Why we use Mean Squared Error”

Algorithm Design

  • Teaching assistant in algorithm design
  • Membership of problem designer team in AUT programming league
  • Passed advanced topics in algorithms course with the highest score among students of our class.



CV

Download my CV.pdf

HONORS AND AWARDS

RESEARCH EXPERIENCES

Implementation and Evaluation of “Genetic” and “Simulated Annealing” Algorithms for Extended Travelling Salesman Problem GitHub
(B.SC. Project)
Under the supervision of Dr. Razazi at Amirkabir University of Technology
In this project, we tested the performance of two different heuristic approaches to solve an NP-Complete Problem. This problem is an extended version of the Travelling Salesman Problem. Since our approach is heuristic, there is no guaranty to find a global optimum answer. So we needed some other exact approach for computing the global optimum. For this purpose, we reduced our problem to an Integer Linear Programming Instance. So in small graph samples, we could compare our results with the optimum solution and for the large graph samples, we just compared our two different methods with each other.

ACADEMIC PROJECTS

TALKS

TEACHING EXPERIENCE

LANGUAGE

  • TOEFL 99 (Reading: 23, Listening: 28, Speaking: 23, Writing: 25)
  • GRE General 317 (Quantitative: 167, Verbal: 150, Writing: 3.0)

FAMILIAR WITH

  • Statistical Machine Learning (Wasserman’s book: All of statistics)
  • Probabilistic Graphical Models (Kuller’s book)
  • Game Theory