Strive for progress, not perfection

My general areas of interest span such areas of science and technology as Soft Computing and Artificial Intelligence. To have more close view, I could refer to Knowledge-based Systems and uncertainty analysis like defining uncertainty around real-world cases and evaluating the situations by using fuzzy logic theory, fuzzy mathematic, fuzzy optimization. Defining critical issues under uncertainty and trying to solve those by proposing the applicable algorithms. Decision-making under vagueness and considering hesitancy in solving problems is almost my fun in the research era. Also, I work on fuzzy inference systems and neuro-fuzzy systems are my most attractive fields of research.

Nowadays, I am working on data-based systems by using well-known data analytics methods and Machine Learning (ML) approaches. Because I do believe that neither knowledge-based nor data-based systems couldn't efficiently be enough alone, and to get a robust solution for well-known complicated problems it is required to consider both altogether. Beforehand, I also worked on model-based systems through different optimization methods, mostly on linear models but I am familiar with some Meta-Heuristic Algorithms in solving NP-hard optimization problems. To be referred some of those algorithms I could call Annealing simulated algorithm and Genetic algorithm. But as I mentioned nowadays I am focused on Machine Learning and Deep Learning algorithms. I also, are aware of time series analysis and applied some ARIMA-based methods in forecasting projects.

At the moment I do research on Graph Deep Learning (GDL) and some projects related to GDL. I introduced some of my interesting projects in this field and you could find those in the project section.