جست‌وجوی استاد و پژوهشگر

Pablo Jesús Barniol-Duránمشاهده پروفایل

استادیار

• Physics Education
• Science Education
• Educational Assessment
• +۳ مورد دیگر

Pablo Jesús Barniol-Durán is an Assistant Professor at the School of Humanities and Education, Tecnológico de Monterrey, Campus Monterrey. His academic profile combines physics expertise with educational innovation, focusing on improving STEM pedagogy through rigorous assessment and instructional design. Education: Industrial Physicist Engineer, Tecnológico de Monterrey PhD in Educational Innovation, Programas en Línea Research Focus: Dr. Barniol-Durán specializes in physics education research , particularly students' conceptual understanding of electromagnetism, vector mathematics, and graphical interpretation. His work employs phenomenographic analysis and diagnostic tool development to identify learning obstacles in electricity/magnetism and kinematics. He investigates how surface features and contextual factors (calculus vs. kinematics) influence conceptual development, with significant contributions to Spanish-language assessment instruments. Publication Trends: His 2015-2025 publications reveal consistent focus on electromagnetism education (Gauss's/Ampere's laws, superposition principle) and assessment methodology. Increasing attention to adaptive learning (2023) and systematic reviews of educational innovation (2021) demonstrates evolving research scope while maintaining core physics education focus. Over 70% of his work addresses Spanish-speaking student populations. Scientific Recognition: National Researcher Level II (SNI, 2020) in Humanities & Behavioral Sciences Distinguished Professors Circle Award (Tecnológico de Monterrey, 2020) Best Titular Professor award by student vote (2020) Research Track Assistant Professor classification (2020) Mexican Researcher Certification Level 2 Teaching Practice: He leads Applied Research Projects I-III and Human Factors Research Methodologies courses, guiding students through problem identification, methodological design, and results analysis. His teaching directly applies his research on conceptual understanding to develop robust research competencies in education students. He actively contributes to UN Sustainable Development Goal 4 (Quality Education) through his pedagogical innovations.

Xin Zhangمشاهده پروفایل

استادیار

• Programming Languages
• Software Engineering
• Program Analysis
• +۶ مورد دیگر

Xin Zhang serves as an Assistant Professor in the Department of Computer Science and Technology within the School of Electronics Engineering and Computer Science at Peking University. His academic profile demonstrates deep engagement with programming languages and software engineering research communities through active participation in major conferences including ASE, SPLASH/OOPSLA, PLDI, and ICSE. Dr. Zhang's research focuses on the synergistic relationship between program analysis and machine learning. He investigates how ML/AI techniques can enhance traditional program analysis methods while simultaneously developing program analysis approaches to improve the interpretability, fairness, robustness, and safety of AI systems. His work spans probabilistic program analysis, abstraction refinement techniques, Bayesian modeling for program semantics, and applications of graph neural networks to static analysis problems. His publication record shows consistent contributions to top venues from 2016 through 2025, with recent work emphasizing Bayesian program analysis, abstraction refinement methods, and the intersection of formal methods with machine learning. The trajectory of his research demonstrates increasing sophistication in combining traditional program analysis techniques with modern AI approaches. Dr. Zhang actively contributes to the academic community as a program committee member for major conferences including ASE, SAS, PLDI, and SPLASH. His service includes reviewing, session chairing, and committee participation across multiple venues, reflecting his standing in the programming languages and software engineering communities.