PhD Candidate at University of Vienna, Austria
Marco Corrias is a dedicated Computational Materials Physicist with a strong foundation in physics, data analysis, and machine learning. Currently pursuing his PhD at the University of Vienna, his research focuses on the automated analysis of microscopy images, combining advanced signal processing with computer vision and pattern recognition. Marco is the founding member and primary developer of AiSurf, a robust open-source software that leverages AI for scientific image analysis. His academic path reflects consistent excellence, with both his BSc and MSc degrees completed with top honors. He is recognized for his interdisciplinary mindset, leadership in collaborative research, and commitment to scientific integrity. Marco has also made notable contributions through student mentorship, international conference participation, and high-impact publications. With a strong analytical skillset and a passion for innovation, he is emerging as a promising researcher at the intersection of physics and machine intelligence.
Professional ProfileĀ
Educationš
Marco Corrias has pursued a distinguished academic path in physics and materials science. He earned his Bachelor of Science in Physics from the University of Cagliari in 2019, graduating cum laude with a thesis on thermoelectricity in complex materials. He then completed his Master of Science in Materials Physics and Nanoscience at the University of Bologna in 2021, again with cum laude distinction. His Master’s thesis explored the formation and dynamics of polarons in SrTiO3, demonstrating his deep understanding of condensed matter physics. Currently, Marco is undertaking a PhD in Computational Materials Physics at the University of Vienna, where he is engaged in interdisciplinary research that blends physics, computer vision, and artificial intelligence. Throughout his academic journey, Marco has consistently demonstrated excellence, curiosity, and a drive to innovate in both theoretical and applied aspects of physical science.
Professional Experienceš
Marco Corrias has amassed impactful professional experience during his ongoing PhD at the University of Vienna, where he plays a pivotal role in advancing automated image analysis techniques in materials science. As a founding member and main developer of AiSurf, he has designed and implemented a comprehensive open-source tool that uses machine learning and computer vision for microscopy image processing. His professional activities include scientific collaboration across disciplines, presenting research findings at international conferences, and mentoring graduate students. Marco has contributed to academic publications, including a high-impact paper recognized by IOP Publishing, and has played a leadership role in academic software development. Additionally, he co-supervised a master’s thesis, showcasing his capability in academic guidance and research communication. His role involves not only conducting simulations and data analysis but also managing software documentation and interdisciplinary project planning, underscoring his multifaceted professional engagement in computational research.
Research Interestš
Marco Corrias’ research interests lie at the interface of computational physics, materials science, and artificial intelligence. His primary focus is on the automated analysis of microscopy images, aiming to enhance pattern recognition and feature extraction using computer vision and machine learning techniques. He is particularly interested in applying these tools to understand physical phenomena in materials at the nanoscale. Marcoās work explores novel methodologies for signal processing and statistical modeling to improve the reproducibility and accuracy of scientific image interpretation. He is also deeply engaged in the development of open-source research tools that democratize access to advanced image analysis technologies. Other areas of interest include thermoelectric materials, polaron dynamics, and the application of high-performance computing in condensed matter systems. Marco is committed to interdisciplinary research that fosters innovation through the integration of physics-based modeling with data-driven techniques, contributing to both scientific discovery and technological advancement.
Award and Honorš
Marco Corrias has received several academic awards and honors that reflect his dedication and excellence in research. He was the recipient of the Best Poster Award at the prestigious IUVSTA-ZCAM conference, highlighting the quality and originality of his scientific presentation. His research article was selected for inclusion in a celebratory collection of high-impact papers by IOP Publishing, underscoring the scientific value and recognition of his work in the international research community. Marco also successfully completed the Path of Excellence program at the University of Cagliari, an honor awarded to top-performing undergraduate students. These accolades showcase his strong research potential and his ability to effectively communicate complex scientific ideas. In addition to formal recognitions, Marco has actively participated in international academic events, further building his reputation as a rising researcher in computational materials physics. His consistent achievements set a solid foundation for future contributions to his field.
Research Skillš¬
Marco Corrias possesses a strong set of research skills that span computational, analytical, and technical domains. He is highly proficient in programming languages such as Python, C++, R, and Unix, which he applies extensively in data analysis, scientific computing, and software development. His expertise includes machine learning, computer vision, and signal processing, particularly for the analysis of microscopy images in materials science. Marco is the key developer of AiSurf, an open-source software that integrates advanced algorithms for image recognition and pattern extraction. His skillset also includes statistical modeling, numerical simulation, and interdisciplinary collaboration. Marco is adept at documenting and maintaining research codebases and ensuring software usability within academic research contexts. He complements his technical proficiency with soft skills such as teamwork, analytical thinking, problem-solving, and project planning. Together, these skills position him as a highly capable and versatile researcher, well-equipped to address complex scientific challenges with innovative computational approaches.
Conclusionš”
Marco Corrias is a strong candidate for the Best Researcher Award, especially considering his innovative contributions to the fusion of computer vision and physics, open-source development, and award-winning research presentations. His work is highly interdisciplinary, bridging the gap between physics, machine learning, and microscopyāan area of growing scientific importance.
With continued publication and greater international engagement, Marco has the potential to emerge as a leading figure in computational materials science and AI-based image analysis. He is suitable for the award, and his profile reflects both current excellence and promising future impact.
Publications Top Notedā
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Title:
Automated real-space lattice extraction for atomic force microscopy images
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Authors:
Marco Corrias, Lorenzo Papa, Igor SokoloviÄ, Viktor Birschitzky, Alexander Gorfer, Martin Setvin, Michael Schmid, Ulrike Diebold, Michele Reticcioli, Cesare Franchini
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Year of Publication:
2023
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Journal:
Machine Learning: Science and Technology
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DOI:
10.1088/2632-2153/acb5e0
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Source:
Crossref
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Citation (as of now):
(Please note: live citation counts change over time. For the most accurate and current citation count, you should check Google Scholar or Scopus directly.)