Evangelia C.
Postdoctoral Researcher & Data Steward
Experience
Jul 2023 - Present
2 years 5 monthsGermany
Postdoctoral Researcher & Data Steward
Technical University Darmstadt, Müller-Plathe group
- Developed and applied a symbolic regression scheme to explore and model complex relationships in liquid viscosities across their phase space, providing predictive insights into material properties.
- Contributed to the improvement of hybrid Particle-Field models through data-driven diagnostics and model enhancement strategies.
- Led interdisciplinary collaboration with experimental physicists for the investigation of the molecular mechanisms behind water-based inks.
- Managed research data workflows to ensure public accessibility and institutional archiving of simulation data, code scripts, and inputs, directly supporting research transparency and reproducibility.
Sep 2019 - Jul 2025
5 years 11 monthsTeaching Assistant
Technical University Darmstadt & Zhiyuan Institute, Shanghai Jiao Tong University
- Cultivated a supportive and inclusive learning environment, receiving positive feedback for student engagement.
- Developed curricula and assessment materials that maintained high academic standards and student engagement.
- Actively engaged in knowledge sharing and peer collaboration through teaching and direct mentorship on Bachelor thesis projects.
Sep 2018 - Jun 2023
4 years 10 monthsChina
Ph.D. Researcher & CSC (Grade A) Scholar
Shanghai Jiao Tong University, Huai Sun group
- Engineered a systematic, high-dimensional sampling framework for molecular configurations, generating robust datasets for predictive model training and integrated machine learning to optimize parameter fitting, significantly enhancing model generalization and predictive power for complex structures.
- Tailored and optimized force field parameters for the complex biomaterial cellulose-Iβ, achieving unprecedented accuracy in crystal lattice and thermodynamic property predictions, surpassing existing models.
- Engineered, benchmarked, and validated simulation-ready, physics-informed models that accurately predict system behavior across diverse thermodynamic regimes.
- Automated molecular structure transformation from fine-grained to coarse representations using a novel graph-theoretical algorithm, improving efficiency in multi-scale simulations.
Summary
Data-driven Computational Chemist with a Ph.D. in Physical Chemistry and expertise in machine learning, statistical modeling, molecular dynamics simulations, and high-performance computing.
Skilled in transforming complex datasets into actionable insights and scalable solutions.
My interests include photography and hiking.
Languages
Greek
AdvancedEnglish
AdvancedFrench
AdvancedGerman
ElementaryChinese
ElementaryEducation
Sep 2018 - Jun 2023
Shanghai Jiao Tong University
Ph.D. · Physical Chemistry · Shanghai, China
Sep 2016 - Jul 2018
University of Bordeaux
Master of Science · Bordeaux, France
Sep 2012 - Jul 2016
University of Bordeaux
Bachelor's Degree · Chemistry · Bordeaux, France
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