Calin-Adrian COMES | Digital Transformation | Best Academic Researcher Award

Published on by Cognitive Scientist Awards

Dr. Calin-Adrian COMES | Digital Transformation | Best Academic Researcher Award

George Emil Palade University of Medicine | Romania

Calin-Adrian Comes is an accomplished academic leader serving as the Institutional Director of the Centre for Studies in Law, Economics and Business at George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, where he contributes to advancing interdisciplinary research in economics, finance, migration studies and data-driven social analysis. He has built his educational foundation in economics and quantitative methods, strengthening it through advanced academic training that integrates econometrics, computational modelling and applied analytical techniques. His professional experience spans teaching, research supervision and collaborative engagement across national and international academic networks. His research interests encompass remittances, migration dynamics, financial flows, labour mobility, econometric modelling and data-mining approaches supporting evidence-based policy. He is skilled in quantitative analysis, stochastic modelling, statistical computing, data mining, natural language processing, SQL and NoSQL databases, as well as interdisciplinary methods that connect economic theory with real-world socio-economic challenges. His work includes contributions to books, journal articles and conference proceedings, supported by widespread citations that reflect his academic impact. He is affiliated with professional societies such as IEEE and the Econometric Society, and his achievements have positioned him for recognition through prestigious scientific award platforms. Overall, he stands out as a researcher committed to analytical rigor, collaborative scholarship and advancing knowledge that informs sustainable economic and social development.

Profile: Google scholar

Featured Publications

Comes, C. A., Bunduchi, E., Vasile, V., & Stefan, D. (2018). The impact of foreign direct investments and remittances on economic growth: A case study in Central and Eastern Europe. Sustainability, 10(1), 238.
Citations: 159

Bresfelean, V. P., Bresfelean, M., Ghisoiu, N., & Comes, C. A. (2008). Determining students’ academic failure profile founded on data mining methods. In ITI 2008: 30th International Conference on Information Technology Interfaces (pp. 1–6).
Citations: 102

Stefan, D., Vasile, V., Oltean, A., Comes, C. A., Stefan, A. B., & Ciucan-Rusu, L., et al. (2021). Women entrepreneurship and sustainable business development: Key findings from a SWOT–AHP analysis. Sustainability, 13(9), 5298.
Citations: 97

 

Mahmoud Alimoradi | Machine Learning | Best Researcher Award

Published on by Cognitive Scientist Awards

Mr. Mahmoud Alimoradi | Machine Learning | Best Researcher Award

Lahijan Azad ,Iran

He understands the growing need for Machine Learning and has a keen interest in the field, which he considers a blessing. Recognizing the importance of managing large and complex computations to control various aspects of the human environment has led him into this vast world. He is particularly fascinated by machine learning, especially reinforcement learning, supervised learning, semi-supervised learning, outliers, and basic data challenges. Furthermore, optimization, an area of artificial intelligence that requires fundamental studies and a change in approach, is another of his key research interests.

Profile

Education

He holds a Master’s degree in Artificial Intelligence Engineering from the University of Shafagh, completed in 2020. His thesis was titled “Trees Social Relations Optimization Algorithm: A New Swarm-Based Metaheuristic Technique to Solve Continuous and Discrete Optimization Problems.” He also earned a Bachelor’s degree in Software Engineering from Azad Lahijan University, which he attended from 2007 to 2011.

Research Interests

Theory: Reinforcement Learning (high-dimensional problems, regularized algorithms, model
learning,
representation learning and deep RL, learning from demonstration, inverse optimal control, deep
Reinforcement Learning); Machine Learning (statistical learning theory, nonparametric
algorithms, time series. processes, manifold learning, online learning); Large-scale Optimization;
Evolutionary Computation, Metaheuristic Algorithm, Deep Learning, Healthcare Machine
learning, Big Data, Data Problems (Imbalanced), Signal Analysis
Applications: Automated control, space affairs, robotic control, medicine and health, asymmetric
data, data science, scheduling, proposing systems, self-enhancing systems

Work Experience

He is a freelance programmer with expertise in various operating systems, including Microsoft Windows and Linux (Arch, Ubuntu, Fedora). He is proficient in software tools such as Microsoft Office, Anaconda, Jupyter, PyCharm, Visual Studio, Tableau, RapidMiner, MATLAB, and Visual Studio. His programming skills include Matlab, Python, C++, Scala, Java, and Julia, with a focus on data mining, data science, computer vision, and machine learning. He is experienced with Python libraries like Pandas, Numpy, Matplotlib, Seaborn, PyCV, TensorFlow, Time Series Analysis, Spark, Hadoop, and Cassandra. Additionally, he is skilled in using Github, Docker, and MySQL. His expertise spans machine learning, deep learning, imbalanced data, missing data, semi-supervised learning, healthcare machine learning, algorithm design, and metaheuristic algorithms. He is fluent in English and Persian.

Publications