Azim

Ahmadzadeh

Research Assistant Professor

Data Mining Lab

Department of Computer Science

Georgia State University

E-mail: aahmadzadeh1..[at]..gsu..[dot]..edu

Office: 25 Park Place, Suite 752, Atlanta, GA

I am a Research Assistant Professor at Georgia State University, Department of Computer Science. I have a Ph.D. and a Master's degree in Computer Science from the same school. I also have a Bachelor of Science degree in Computer Science from Warsaw University of Technology, Poland, and an Associate degree in Mathematics from Guilan University in my hometown in Iran. I have worked as a Software Engineer for a short period of time before I decided to pursue higher education in the U.S. Since 2016, I have been working at the Data Mining Lab @ Georgia State University. My research primarily focuses on the effective use of Artificial Intelligence to advance interdisciplinary areas of science, specifically Space Weather research. High-dimensional data, integration and curation of data, novel similarity measures, and robust evaluation of models when data are imbalanced, are some of the key areas of my research. 

EDUCATION

Ph.D., Computer Science, 2021, Georgia State University, USA

B.Sc., Computer Science, 2016, Warsaw University of Technology, Poland

A.Sc., Pure Mathematics, 2008, Guilan University, Iran

AREAS OF INTEREST:

CS: Machine Learning, Deep Learning, Image Processing, Time Series Analysis, Performance Verification, High Dimensional Data, Imbalanced Data, Spatiotemporal Data

Physics: Solar Flare Forecasting, Detection and Segmentation of Solar Events, Cost-Effective Evaluation Metrics for Forecast Models

RESEARCH TOPICS:

• Model Evaluation:

  • Evaluation of Salient-Object Detection with Fine Structures

  • Evaluation of Categorical and Probabilistic Classification

  • Robust Sampling of Rare Events

• Spatiotemporal Analysis:

  • Prediction of Space-Weather Events

  • Detection and Segmentation of Scientific Events

  • Task-Specific Feature Extraction and Optimization

• Multivariate Time Series Data:

  • Statistical Feature Extraction 

  • Time Series Clustering