Yasaman Malekiyourtchi

I graduated from the Department of Statistics at Amirkabir University of Technology (Tehran Polytechnic) and have over ten years of academic and research experience as an Assistant Professor of Statistics at the Department of Statistics, Alzahra University, Tehran, Iran.
My Ph.D. research focused on locally self-similar processes, a subclass of non-stationary stochastic processes, with an emphasis on time–frequency spectrum estimation. These processes arise in various real-world applications such as financial markets, internet traffic, and dynamic systems where statistical properties evolve over time.
My publication record includes articles in peer-reviewed journals in probability and statistics, as well as conference proceedings. In addition to my doctoral work, I have conducted research on probability density function (PDF) estimation for non-stationary processes, which is particularly relevant in signal processing and streaming data contexts (e.g., ATM transactions, internet data), where stochastic characteristics change over time.
I have extensive teaching experience across a wide range of courses, including Probability and Measure Theory (graduate level), Probability Theory, Stochastic Processes, Time Series Analysis, Mathematical Statistics, Statistical Methods, Computational Statistics with R, Design and Analysis of Experiments, and applied statistics courses for Engineering, Economics, Psychology, and other fields.
I have also supervised both graduate and undergraduate students in their research projects. Through my roles as an Orientation Leader and Academic Adviser, I have developed strong skills in communication, leadership, and problem-solving. Student evaluations consistently highlight my enthusiasm, subject knowledge, and ability to create an inclusive and engaging learning environment. I am highly motivated by research and creative problem solving.

Research and Professional Activities
Previous Work (Stock Assessment and Time Series Research)
* Worked with stock assessment models, including SAM (State-space Assessment Model) and Stock Synthesis (SS3), using R.
* Contributed to the analysis of Saithe, Cod, and Shrimp stocks.
* Applied expertise in Statistics to integrate statistical modeling with fisheries stock assessment.
* Authored one scientific paper focused on stock prediction using time series analysis combined with stock assessment models.

Current Research Focus
* Member of the AI and Analysis Group.
* Applying knowledge in Statistics, Probability Theory, and Stochastic Processes to Artificial Intelligence (AI), Machine Learning methods, and advanced data analysis.
* Focused on integrating statistical theory with modern AI approaches to enhance predictive modeling and analytical frameworks.

Core Competencies
* Statistical Modeling
* Time Series Analysis
* Stochastic Processes
* Stock Assessment Models (SAM, SS3)
* R Programming
* Machine Learning and AI (applied)
* Probability Theory