Overview
These two peer-reviewed research papers, published in MDPI journals in 2023, demonstrate advanced mathematical analysis capabilities, rigorous research methodology, and contributions to the academic mathematics community. Both papers underwent rigorous peer review and represent high-quality academic scholarship.
Publication 1: Studying Harmonic Functions
Citation
Journal: Mathematics (MDPI)
Year: 2023
Volume/Issue: 11(10), 2220
DOI: 10.3390/math11102220
Abstract
This research investigates properties of harmonic functions within the framework of complex analysis and function theory. The study employs advanced mathematical techniques to analyze function behavior, proving theoretical results with applications in mathematical physics and engineering.
Key Contributions
- Theoretical Advancement: Novel results in harmonic function theory
- Analytical Methods: Application of complex analysis techniques
- Mathematical Rigor: Formal proofs and theoretical framework
- Research Innovation: Original contribution to mathematical literature
Significance
This work contributes to:
- Advanced function theory
- Complex analysis research
- Mathematical foundations for applied fields
- Theoretical mathematics community
Skills Demonstrated
- Advanced Mathematics: Complex analysis and function theory
- Analytical Thinking: Proof development and theoretical reasoning
- Academic Writing: Peer-reviewed publication standards
- Research Design: Original research questions and methodology
Publication 2: BiUnivalent Functions and q-Pascal Distribution
Citation
Journal: Symmetry (MDPI)
Year: 2023
Volume/Issue: 15(5), 1109
DOI: 10.3390/sym15051109
Abstract
This paper explores the intersection of geometric function theory and probability distributions, specifically examining bi-univalent functions through the lens of the q-Pascal distribution. The research establishes connections between seemingly disparate areas of mathematics, demonstrating the unifying power of mathematical analysis.
Key Contributions
- Interdisciplinary Mathematics: Bridges function theory and probability
- Novel Connections: Links bi-univalent functions to q-Pascal distributions
- Theoretical Results: New bounds and coefficient estimates
- Mathematical Innovation: Original approach to classical problems
Significance
This work demonstrates:
- Cross-disciplinary mathematical thinking
- Ability to connect abstract mathematical concepts
- Contribution to geometric function theory
- Application of probabilistic methods to function theory
Skills Demonstrated
- Advanced Probability: q-calculus and distribution theory
- Geometric Function Theory: Bi-univalent function analysis
- Mathematical Synthesis: Connecting multiple mathematical domains
- Publication Excellence: High-quality peer-reviewed research
Publication Impact
Academic Recognition
Both papers are published in MDPI journals, which are:
- Peer-reviewed: Rigorous academic quality standards
- Indexed: Included in major academic databases
- Open access: Freely available to global research community
- Cited: Contributing to ongoing mathematical research
Research Quality Indicators
- ✅ Peer Review: Passed rigorous academic review process
- ✅ Mathematical Rigor: Formal proofs and theoretical framework
- ✅ Original Research: Novel contributions to mathematics
- ✅ Publication Standards: Professional academic writing
- ✅ Open Access: Available to worldwide research community
Relevance to Data Science
While these publications focus on pure mathematics, they demonstrate critical skills for data science:
Analytical Capabilities
- Advanced quantitative reasoning: Complex mathematical analysis
- Pattern recognition: Identifying mathematical relationships
- Logical thinking: Proof development and validation
- Problem-solving: Tackling abstract, complex problems
Research Skills
- Methodology design: Structured research approaches
- Hypothesis testing: Mathematical proof as validation
- Literature synthesis: Building on existing research
- Communication: Explaining complex concepts clearly
Technical Writing
- Documentation: Precise mathematical writing
- Clarity: Communicating technical concepts
- Audience awareness: Writing for peer reviewers and readers
- Professional standards: Publication-quality work
View Publications
Related Work
Interested in more research and publications? View my other work:
- Survey Analysis: Upper Primary Mathematics Teaching
- Five-Country Mathematics Survey (RTI White Paper)
- Featured Data Science Projects
Research Philosophy
These publications reflect my commitment to:
- Intellectual rigor: High standards for analytical work
- Continuous learning: Engagement with cutting-edge research
- Knowledge contribution: Adding value to academic community
- Excellence: Meeting professional publication standards
These same principles guide my approach to data science and analytics work.
Contact
Interested in discussing mathematical applications in data science or collaborative research?
Email: carla.amoi@gmail.com
LinkedIn: linkedin.com/in/carudder