Teodor Andrei Diaconescu

PhD Student in Artificial Intelligence

Bio

Teodor Andrei Diaconescu graduated in Computer Engineering from Universidad Rey Juan Carlos (URJC) and holds a Master’s in Artificial Intelligence Research from the Menéndez Pelayo International University (UIMP). He is currently pursuing his PhD in Artificial Intelligence, specializing in optimization and metaheuristics as a predoctoral researcher.

He brings a unique combination of academic expertise and practical industry experience to his research. His professional background includes working as a Full Stack Developer in the Corporate Applications area at Universidad Rey Juan Carlos, where he gained valuable experience in software development and system architecture.

In his academic role, he has served as a Visiting Lecturer in the Department of Computer Science and Statistics at URJC, where he taught subjects in various areas including Distributed Systems, Statistics, and Informatics and Digital Competence for Teaching. This teaching experience demonstrates his ability to bridge theoretical knowledge with practical application.

His research interests focus on the intersection of artificial intelligence, optimization algorithms, and metaheuristics, with a particular emphasis on developing efficient solutions for complex computational problems.

Research Focus

Optimization and Metaheuristics: His primary research specialization lies in optimization and metaheuristics, working within the framework of artificial intelligence to develop efficient algorithms for solving complex computational problems.

Artificial Intelligence Applications: He focuses on applying AI techniques to solve real-world optimization challenges, contributing to the advancement of computational intelligence methodologies.

Computational Problem Solving: His work involves developing and implementing algorithms that can effectively address hard optimization problems across various domains.

Academic Research: As a predoctoral researcher, he is actively engaged in advancing the theoretical and practical aspects of metaheuristic algorithms and optimization techniques.

Education

• PhD Student in Artificial Intelligence - Universidad Rey Juan Carlos (2024-present)
• Master’s Degree in Artificial Intelligence Research - Menéndez Pelayo International University (2022-2024)
• Computer Engineering - Universidad Rey Juan Carlos (2017-2022)

Professional Experience

Academic Teaching:

• Visiting Lecturer - Department of Computer Science and Statistics, URJC
  • Distributed Systems
  • Statistics
  • Informatics and Digital Competence for Teaching

Industry Experience:

• Full Stack Developer - Corporate Applications area, Universidad Rey Juan Carlos
  • Software development and system architecture
  • Corporate application development and maintenance

Teaching & Mentoring

Subject Areas:

• Distributed Systems - Teaching advanced concepts in distributed computing and system design
• Statistics - Instruction in statistical methods and data analysis
• Digital Competence - Training in informatics and digital skills for teaching applications

Educational Philosophy: His teaching approach combines theoretical foundations with practical applications, drawing from his industry experience to provide students with real-world perspectives on computational concepts.

Research Applications

• Algorithm Development - Creating efficient metaheuristic algorithms for optimization problems
• Computational Intelligence - Applying AI techniques to solve complex optimization challenges
• Software Systems - Leveraging full-stack development experience for research implementation
• Educational Technology - Integrating digital competence in academic instruction

Professional Development

Academic-Industry Bridge: His unique background combining industry experience as a full-stack developer with academic research provides valuable insights into practical implementation of theoretical concepts.

Multidisciplinary Approach: His teaching experience across distributed systems, statistics, and digital competence demonstrates versatility in computational sciences.

Research Collaboration: Active participation in the academic community through research and teaching activities at Universidad Rey Juan Carlos.

Current Research Areas

• Metaheuristic Algorithm Design - Developing new approaches to optimization problems
• Artificial Intelligence Applications - Implementing AI solutions for complex computational challenges
• Optimization Theory - Advancing theoretical understanding of optimization algorithms
• Practical Implementation - Bridging theory and practice in algorithm development

Interests

Artificial Intelligence | Metaheuristics | Optimization | Statistics | Distributed Systems | Software Development | Digital Education

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