جستجوی استاد راهنمای دانشگاهی

• Search Based Software Engineering
• Software Testing
• Evolutionary Computation
• +۷ مورد دیگر

Giovani Guizzo is a Software Engineer at Kii working as a Blockchain Engineer and Front-end developer with React, while maintaining an active research profile in Search-Based Software Engineering. He earned his PhD in Computer Science from the Department of Informatics at Federal University of Paraná (UFPR) in Brazil under Professor Silvia Regina Vergilio in 2018. His academic collaborations include significant affiliations with University College London where he has published as a researcher. His research program centers on applying evolutionary computation and search-based techniques to software engineering challenges, particularly in software testing and optimization. Guizzo's work bridges theoretical advances in multi-objective optimization with practical software engineering applications, resulting in innovative solutions for test model inference, mutant reduction strategies, and automated program repair. His approach often combines natural language processing with finite state machine generation to transform bug reports into actionable test models. Guizzo's publication record reveals a consistent trajectory of increasing impact in top-tier software engineering venues. His recent work demonstrates sophisticated integration of multi-objective evolutionary algorithms with practical software testing challenges, particularly in the areas of model inference from natural language bug reports and optimization of mutation testing processes. The evolution of his research shows progression from foundational work on design patterns in evolutionary algorithms toward more complex applications in automated software testing and repair. His achievements include: SSBSE 2021 Challenge Winner for innovative work on fitness functions in automated program repair Distinguished Artifact Award at ICSE 2021 recognizing reproducibility in genetic improvement research Microsoft Azure Research Award in 2017 supporting his work in cloud-based software engineering research Guizzo maintains active engagement with the research community through editorial roles for IET Software and Science of Computer Programming, membership on the SSBSE Steering Committee, and service on program committees for major conferences including ESEC/FSE, ASE, GECCO, and ICSE. His academic visits to University College London (3 months in 2017) and Queen Mary University (1 month in 2017) established lasting research collaborations with Dr. Jens Krinke, Dr. Federica Sarro, and Dr. John Drake that continue to produce high-impact publications. Through his interdisciplinary approach combining software engineering, evolutionary computation, and natural language processing, Guizzo has established himself as a significant contributor to the search-based software engineering community, with research that consistently addresses practical challenges while advancing theoretical foundations.

Nathalia Nascimentoمشاهده پروفایل

پژوهشگر ارشد

• Multiagent Systems
• Internet of Things
• Artificial Intelligence
• +۳ مورد دیگر

Nathalia Nascimento is a Research Fellow at Pennsylvania State University, USA, holding a doctorate from Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil. Her expertise spans Computer Engineering and Artificial Intelligence with institutional affiliations reflecting active research roles in North American academia. Her educational foundation includes doctoral research at PUC-Rio focused on interdisciplinary computing systems. Research interests prominently feature Multiagent Systems , Internet of Things , Artificial Intelligence , Software Engineering , Software Product Line , and Software Framework development, emphasizing AI integration into adaptable software architectures. Recent publications demonstrate a cohesive trajectory in leveraging large language models for human-AI collaboration, system adaptability, and performance validation. Key trends include architectural innovations for chatbot automation control, self-adaptive multiagent coordination, and rigorous empirical analysis of LLM capabilities in programming contexts, highlighting her focus on practical AI-software synthesis. Dr. Nascimento actively contributes to academic governance through program committees for EASE 2025 (AI Models/Data Track), CASCON 2025 (Posters Track), and Mining Software Repositories 2024 (Mining Challenge), reflecting community engagement without documented advising responsibilities or grant leadership.

Earl T. Barrمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Automated Program Repair
• +۵ مورد دیگر

Earl T. Barr is a Professor of Software Engineering at University College London (UCL), where he heads the System Software Engineering Group and is a member of the Centre for Research on Evolution, Search and Testing (CREST). He received his Ph.D. in Computer Science from the University of California, Davis in 2009. His educational background includes: Ph.D. in Computer Science, 2009, University of California, Davis Barr's research focuses on software engineering, particularly program analysis, automated program repair, and the application of machine learning to code (AI4Code). He is renowned for his work on dual channel analysis, which examines how code combines natural language elements (in identifiers, comments, and stylistic choices) with formal programming language. His research also explores game theory applications to software development processes and how dual channel constraints can improve type inference and code understanding. His recent publications demonstrate a strong trend toward leveraging large language models for code understanding and modification, with particular emphasis on dual channel constraints and natural type inference. His work bridges traditional software engineering techniques with modern AI approaches, showing how machine learning can enhance program analysis and repair while maintaining rigorous theoretical foundations. Notable awards include: ACM SIGSOFT Distinguished Paper Award for Automated Software Transplantation (2015) ACM SIGSOFT Distinguished Paper Award for Learning Natural Coding Conventions (2014) ACM SIGSOFT Distinguished Paper Award for Collecting a Heap of Shapes (2013) Best Paper Award for TrustDavis: A Non-Exploitable Online Reputation System (2005) Barr actively supervises numerous PhD students and postdocs, with current research focusing on AI for code, software security, and program analysis. He collaborates extensively with Santanu Dash of Royal Holloway on dual channel program analysis, and they jointly supervise PhD students through the EPSRC Centre for Doctoral Training in Cyber Security for the Everyday. His work often combines theoretical rigor with practical tool development, resulting in several publicly available research tools that influence both academic research and industry practice. He leads the System Software Engineering Group at UCL, which focuses on developing novel approaches to software engineering challenges at the intersection of human and machine aspects of programming. Current research directions include dual channel analysis for vulnerability detection, game-theoretic approaches to development processes, and AI-assisted software development.

Lola Burgueñoمشاهده پروفایل

دانشیار

• Software Engineering
• Model-Driven Software Engineering
• Artificial Intelligence in Software Development
• +۵ مورد دیگر

Lola Burgueño is an Associate Professor at the University of Malaga (UMA), Spain, where she is a member of the Atenea Research Group and part of the Institute of Technology and Software Engineering (ITIS). She completed her PhD with honors in April 2016 from the University of Málaga, following a master's degree in Software Engineering and Artificial Intelligence (2012) and a Computer Science and Engineering degree (2011). Her academic journey includes postdoctoral positions at the Open University of Catalonia (Barcelona, Spain; 2018-2022) and CEA List (Paris, France; 2018-2020), along with visiting researcher appointments at the University of Alabama (USA; 2014), Vanderbilt University (USA; 2016), and Université de Montréal (Canada; 2022). Dr. Burgueño's research spans several interconnected domains: Software Engineering and Model-Driven Software Engineering Artificial Intelligence integration in software development processes Uncertainty management during software design phases Model-based software testing methodologies Performance optimization of model transformations Digital twin technologies and Socio-Cyber-Physical Systems Her publication record shows an evolving research trajectory from foundational work in model transformations and non-functional requirements toward increasingly sophisticated integration of AI techniques with traditional software engineering approaches, with recent emphasis on ethical considerations in AI-enhanced software modeling and human-centered aspects of digital twin technologies. Professional service and recognition: PC (co-)chair for ECMFA'21, SLE'22 and JISBD'25 Active Program Committee member for ASE, ICSE, MODELS, SLE, and other premier software engineering conferences Editorial Board member of the Journal on Software and Systems Modeling (SoSyM) Steering Committee member of the ACM SIGPLAN International Conference on Software Language Engineering (SLE) Member of the WG on Diversity & Inclusion of Informatics Europe Dr. Burgueño maintains strong international collaborations across Europe and North America, regularly reviewing for top-tier journals including TSE, JSS, EMSE, and SoSyM, and contributing to the advancement of software engineering research and education globally.

Paul Grünbacherمشاهده پروفایل

دانشیار

• software product lines
• model-based development
• software evolution
• +۲ مورد دیگر

Paul Grünbacher serves as an Associate Professor and Deputy Head of the Institute of Software Systems Engineering at Johannes Kepler University Linz, Austria. With over 150 publications in international peer-reviewed venues, he's established himself as a leading researcher in software engineering, particularly in specialized domains requiring sophisticated modeling approaches. His primary research interests include software product lines , model-based development , software evolution , requirements engineering , and software monitoring . These interconnected fields reflect his focus on creating adaptable, maintainable software systems that can evolve over time while maintaining quality and functionality. His work bridges theoretical foundations with practical applications in complex software environments. Analysis of his recent publications reveals a consistent focus on temporal aspects of software evolution, particularly in product line contexts. His research demonstrates strong emphasis on creating methods to track, analyze, and support software changes across multiple dimensions including spatial distribution and temporal progression. The increasing integration of monitoring techniques with requirements engineering represents an emerging trend in his more recent work. Fellow of Automated Software Engineering (2021) Editorial Board Member, Empirical Software Engineering Journal (Springer, 2018-present) Editorial Board Member, Information and Software Technology Journal (Elsevier, 2015-present) Steering Committee Member, IEEE/ACM International Conference on Automated Software Engineering (2004-present) Grünbacher has served as a program committee member for numerous prestigious conferences including ASE, ICSE, and REFSQ across multiple years. He led the Christian Doppler Laboratory for Monitoring and Evolution of Very-Large-Scale Software Systems from 2013-2021, securing significant research funding and directing a team focused on practical solutions for evolving complex software systems. His editorial roles demonstrate recognition of his expertise in empirical software engineering methodologies. As head of the Christian Doppler Laboratory for Monitoring and Evolution of Very-Large-Scale Software Systems (2013-2021), Grünbacher directed a research team developing innovative approaches for monitoring and evolving complex software systems. His current work through the Institute of Software Systems Engineering continues this focus, with increasing attention to cyber-physical systems and digital process twins.

Esther Guerraمشاهده پروفایل

استاد

• Model-Driven Engineering
• Software Engineering
• Domain-Specific Languages
• +۷ مورد دیگر

Esther Guerra is a Full Professor in the Department of Computer Science at the School of Engineering, Autonomous University of Madrid. She joined the university in 2010 after previously serving as a professor at the Universidad Carlos III de Madrid from 2004 to 2010. Her academic career spans over two decades with consistent contributions to software engineering research and education. Dr. Guerra's research focuses on Model-Driven Engineering (MDE), Domain-Specific Languages, and software testing. She has made significant contributions to language engineering, particularly in language product lines, metamorphic testing, and the development of tools for model-based engineering. Her work bridges theoretical foundations with practical applications, especially in chatbot development, low-code platforms, and augmented reality systems. She leads the MISo research group which actively develops tools like Merlin, MetaDepth, and Wodel-Test. Her publication record shows a consistent trajectory of high-impact research, with recent work focusing on adaptive modeling languages, chatbot engineering, and test amplification frameworks. She has published in top-tier journals including ACM Transactions on Software Engineering and Methodology, Journal of Systems & Software, and Software and Systems Modeling. As an educator, Dr. Guerra has taught numerous courses including Software Analysis and Design Project, Automated Software Development, and Model-Driven Software Development. She has supervised numerous undergraduate and master's theses focused on practical applications of model-driven techniques. Dr. Guerra is actively involved in the academic community, serving on program committees for major conferences including ASE, MODELS, ICSE, and SPLASH. She has contributed to the organization of several workshops and symposia focused on software engineering topics.

Sergey Vakhrushevمشاهده پروفایل

دانشیار

• Glycomics
• Proteomics
• Glycoproteomics
• +۷ مورد دیگر

Sergey Vakhrushev serves as Associate Professor in the Department of Cellular and Molecular Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences. He leads the Vakhrushev Group, which focuses on proteome-wide characterization of O-glycan structures at specific sites in O-glycoproteins. His research addresses fundamental challenges in glycoproteomics through innovative methodological approaches. Dr. Vakhrushev's primary research centers on post-translational modifications, particularly protein glycosylation. His group has made significant breakthroughs using genetically engineered 'SimpleCells' to overcome limitations in O-glycoproteome analysis, reporting over 15,000 O-glycosites and 5,000 O-glycoproteins. His work spans next-generation glycoproteomics, tyrosine O-GalNAc glycosylation, clinical glycoproteomics, and computational glycoinformatics. The research addresses critical challenges in simultaneous identification and quantification of native glycan structures on single glycosites, as well as glycosite occupancy and stoichiometry determination. His recent publications demonstrate a strong focus on advancing glycoproteomics through methodological innovation with applications spanning basic science to clinical diagnostics. His work on aberrant glycosylation in cancer development shows particular promise for biomarker discovery. The research has significant implications for understanding biological functions in health and disease across multiple organ systems including liver, kidney, and brain. Dr. Vakhrushev maintains an extensive international collaboration network spanning institutions in Zaragoza, Porto, Singapore, Muenster, Copenhagen, Split, Rome, Wien, and Athens. His research has garnered substantial attention, with publications being picked up by 72 news outlets, blogged by 3 sources, and widely shared across social media platforms including 39 X posts and numerous Bluesky references. His work has attracted significant academic interest with over 100 Mendeley readers across recent publications.

Makrand Khanwaleمشاهده پروفایل

پژوهشگر

• Multiphase flows
• Finite Element Methods
• Numerical Analysis
• +۳ مورد دیگر

Makrand Khanwale is a Physical Science Research Scientist in the Department of Mechanical Engineering at Stanford University, working with Professors Ali Mani and Gianluca Iaccarino. His research focuses on developing numerical methods for simulating multiphase flows, turbulence, and complex physical processes using advanced computational frameworks. He holds a PhD in Mechanical Engineering and Applied Mathematics from Iowa State University (2021), advised by Drs. Baskar Ganapathysubramanian and James Rossmanith, and a B.Tech. in Chemical Technology from the Institute of Chemical Technology, Mumbai (2015). Education: PhD, Iowa State University (2016–2021): Co-major in Mechanical Engineering and Applied Mathematics B.Tech, Institute of Chemical Technology (2011–2015) Research Interests: Khanwale specializes in multiphase flow simulations, finite element methods, numerical analysis, and turbulence modeling. His work emphasizes energy-stable numerical schemes, adaptive mesh refinement, and high-performance computing for applications in green hydrogen production, compressible multiphase flows, and electrochemical systems. Key Projects: INSIEME project under PSAAP III program at Stanford Development of the PROTEUS open-source framework for multiphase flow simulations Modeling of Reynolds Stress Models using forced turbulence simulations Scientific Awards: Finalist, Scientific Visualization and Data Analytics Showcase (Super Computing ‘22) Center for Turbulence Research Postdoctoral Fellowship (Stanford) FMJH/LMH Postdoctoral Fellowship (EM2C, CentraleSupélec, Paris) Research & Teaching Excellence Awards (Iowa State University) Labs & Collaborations: His work is part of collaborative efforts at Stanford’s Center for Turbulence Research and involves partnerships with institutions like Iowa State University and LSU. He contributes to open-source tools like PROTEUS, advancing adaptive mesh techniques and parallel computing.

• Graph Theory
• Domination Theory
• Topological Indices
• +۳ مورد دیگر

Bermudo Navarrete is a University Professor in the Department of Economics, Quantitative Methods and Economic History at Pablo de Olavide University's Higher Polytechnic School in Seville, Spain. His academic career spans over two decades, with teaching positions at multiple international institutions including the University of Seville, Popular Autonomous University of Puebla (Mexico), and The College of the Bahamas. Professor Navarrete specializes in Graph Theory and Discrete Mathematics, with particular expertise in domination theory, topological indices, and mathematical analysis. His research focuses on differential of graphs, hyperbolicity in graphs, and vertex-degree-based topological indices. His work bridges theoretical mathematics with applications in chemical graph theory and network analysis. His extensive publication record shows a clear evolution from early work in operator theory to his current focus on graph theory applications. Since 2012, his research has centered on domination parameters, differential sets, and topological indices in various graph structures, with increasing applications to chemical graph theory and computational methods. Throughout his career, Professor Navarrete has maintained an active international research presence with numerous research stays at institutions worldwide including universities in Russia, Venezuela, USA, Poland, Mexico, Germany, Colombia, Argentina, Brazil, and the Dominican Republic. He teaches undergraduate courses in Algebra, Calculus, and Final Degree Projects for Computer Engineering students across multiple specializations including Information Systems, Data Science, and Mind in Information Systems. His teaching reflects the mathematical foundations required for modern computer science applications.

• Software Engineering
• Model-Driven Engineering
• Software Architecture
• +۵ مورد دیگر

Alexander Egyed serves as a full Professor at the Institute of Software Systems Engineering, Johannes Kepler University Linz, where he directs the LIT Secure and Correct Systems Lab. His leadership spans 350+ research outputs and 50+ projects, with current active grants securing research through 2029 in critical software engineering domains. His research focuses on advancing model-driven engineering practices through innovations in software evolution, variability management, and process guidance. Key contributions include reactive link propagation for model consistency, AI-driven refactoring of legacy systems, and industrial-strength process compliance solutions. His work bridges formal methods with practical industrial applications, particularly in secure system development and software modernization. Recent publications (2024-2025) reveal a pronounced shift toward AI-integrated solutions for legacy system transformation, with consistent emphasis on scalable techniques for model consistency and variability control. This trajectory demonstrates increasing industrial collaboration in developing actionable engineering guidance tools. His scientific excellence is recognized through: ACM Best Paper Award (2015) ACM Recognition of Service Award (2024) ACM SIGSOFT Distinguished Paper Awards (2021, 2023) Best Paper Award (2014) Professor Egyed currently leads major funded initiatives including the FWF-sponsored 'Co-Existence of Modeling Language Versions and Co-Evolution' (2025-2029) and dual 'RefactorAI' projects for legacy system modernization (FFG 2025-2028). His supervision of 12 graduate students reflects commitment to academic mentorship alongside his extensive editorial and program committee service across 147 recorded academic activities. He directs the LIT Secure and Correct Systems Lab, a nexus for interdisciplinary research in formal verification, model-driven security, and AI-assisted software engineering, maintaining strong industry partnerships for real-world validation of research outputs.

• Production Technology
• Engineering
• Virtual Preparation
• +۵ مورد دیگر

Lennart Malmsköld is a Lecturer at University West , affiliated with the Department of Industrial Economics. His work bridges research and education in production technology, with a focus on virtual preparation and computer-aided training. Research Interests: Production processes, production systems, virtual preparation, digital manufacturing, computer-aided training. His research explores ergonomics simulations, virtual preparation, and operator training in low-automation environments, particularly in the automotive industry. Recent Research Trends: Recent publications highlight augmented reality (AR) applications in industrial assembly, AI-driven inspection systems, and university-industry collaboration for curriculum design. He investigates multimodal AR interfaces, data handling in global manufacturing, and work-integrated learning. Teaching Experience: Malmsköld has 8 years of teaching experience at University West in the Mechanical Engineering program. He supervises doctoral students and contributes to degree theses.

• Prostate Cancer
• Cancer Epigenetics
• Chemoprevention
• +۳ مورد دیگر

Avinash Kumar serves as a Research Scientist at the Cancer Research laboratories within Long Island University's College of Pharmacy and Health Sciences, where he also directs the Small Animal Imaging Core facility. He joined LIU after completing postdoctoral research at the University of Mississippi Medical Center's Cancer Institute (2013-2016), following a Department of Biotechnology Postdoctoral Fellowship in India. His educational foundation includes: Ph.D. in protein biochemistry and biophysics from National Chemical Laboratory, University of Pune (2012) DBT-Postdoctoral Fellowship at National Center for Cell Science, Pune Postdoctoral Research Fellowship at University of Mississippi Medical Center Dr. Kumar's research centers on MTA1's role in prostate cancer progression and metastasis, investigating how this chromatin modifier promotes tumor development through epigenetic regulation and PTEN inactivation. His work pioneers dietary stilbenes like resveratrol and pterostilbene as MTA1-targeted chemopreventive agents, with recent studies expanding into AI-driven drug discovery and combination therapies for treatment-resistant disease. His laboratory utilizes genetically engineered mouse models to study prostate cancer initiation and progression. Analysis of his publication record reveals consistent focus on MTA1 biology and natural product interventions, with increasing emphasis on translational applications including preclinical IND-enabling studies and AI-based therapeutic development. His work bridges molecular oncology, epigenetics, and nutritional science to develop novel prostate cancer strategies. His scientific recognition includes: Best Poster Award at UMMC Research Day (2015) Keerthi Sangoram Memorial Endowment Award (2012) DBT-Postdoctoral Fellowship (2011) CSIR-UGC Senior Research Fellowship (2008) CSIR-UGC Junior Research Fellowship (2006) Dr. Kumar actively mentors junior researchers as evidenced by his senior authorship on numerous student presentations at AACR meetings and institutional Discovery Days. He serves as an ad-hoc journal reviewer and maintains active membership in the American Association for Cancer Research. His laboratory directs the Small Animal Imaging Core facility, providing critical preclinical imaging resources for cancer research while collaborating closely with Dr. Levenson's team on prostate cancer mechanisms.

Carlos Scheelمشاهده پروفایل

استاد

• Sustainable Development
• Circular Economy
• Complex Systems Dynamics
• +۳ مورد دیگر

Carlos Scheel is a Professor at EGADE Business School, Tecnológico de Monterrey, where he has taught since 1973. His expertise spans sustainable innovation systems, circular economy models, and complex dynamics of industrial ecosystems. As a Senior Research Fellow at the University of Texas-Austin's IC2 Institute since 1989, he maintains significant international research collaborations. His research focuses on developing sustainable wealth creation frameworks through technological innovation. Key contributions include the SWIT model (Sustainable Wealth creation based on Innovation and Technology) with its three-tiered approach: Zero-Residue Industrial Ecosystems (ZRIES), Circular Value Ecosystems (CVES), and Shared Value Systems (SVS). His work bridges theoretical systems dynamics with practical applications in industrial ecology and regional development. Dr. Scheel's publication trends reveal a consistent focus on circular economy implementation (60% of recent works), systemic innovation (25%), and community resilience frameworks (15%). His research demonstrates strong interdisciplinary integration across environmental science, industrial engineering, and business strategy, with increasing emphasis on scalable zero-waste business models since 2016. Senior Research Fellow, IC2 Institute (University of Texas-Austin, 1989-present) Member, National System of Researchers (SNI Level I, CONACyT Mexico, 2007-present) Founding Member, AMD Global Consumer Advisory Board (2002-2004) International Advisor, UNIDO Private Sector Development Branch (1989-2012) With over 20 international projects funded by organizations including the World Bank, UNIDO, and USAID, Dr. Scheel has advised governments on industrial cluster development and innovation policy across 16 countries. His consulting work focuses on designing regional innovation systems that integrate technological entrepreneurship with sustainability imperatives. He leads research on Innovacities and circular economy business models, collaborating with institutions like PetStar on bottle-to-bottle recycling systems. His work with the FAIR Center for Financial Access and Research informs sustainable wealth creation frameworks that balance economic growth with ecological preservation.

Marsha Chechikمشاهده پروفایل

استاد

• Software Engineering
• Formal Methods
• Software Specification and Verification
• +۷ مورد دیگر

Marsha Chechik is a Professor in the Department of Computer Science at the University of Toronto within the Faculty of Arts and Science. She previously served as Chair of the Department of Computer Science (2019-2022) and as Acting Dean in the Faculty of Information (July-December 2022). Professor Chechik received her Ph.D. from the University of Maryland in 1996 and has established herself as a leading researcher in software engineering with a focus on formal methods. Her research interests include software safety and security, automated verification, software product lines, and model management. Professor Chechik has authored numerous papers in formal methods, software specification and verification, computer safety and security, and requirements engineering. Her work has evolved to incorporate newer areas such as machine vision reliability analysis, normative requirements with large language models, and machine learning development lifecycle analysis. Her research consistently bridges theoretical foundations with practical applications in software engineering. Professor Chechik has served in numerous leadership roles including Program Committee Co-Chair for major conferences such as ICSE 2018, TACAS 2016, VSTTE 2016, ASE 2014, CONCUR 2008, CASCON 2008, and FASE 2009. She is currently the Area Chair for ASE 2025 in Security and Other Non-Functional Properties. She has also served as Associate Editor in Chief of Journal on Software and Systems Modeling and as associate editor of IEEE Transactions on Software Engineering (2003-2007, 2010-2013). Best paper award at RE'12 (2012) SIGSOFT Distinguished Paper at ICSE'12 (2012) Winner of Best Student Paper Award at CASCON'07 (2007) Winner of Distinguished Paper Award at ICSE'07 (2007) Professor Chechik regularly mentors PhD students, with notable advisees including Michalis Famelis, Shiva Nejati, Jocelyn Simmonds, Ou Wei, and Aws Albarghouthi. Her advising philosophy emphasizes rigorous formal methods while addressing practical software engineering challenges. She has been involved in numerous research grants focusing on software verification, safety-critical systems, and requirements engineering. Currently, her work explores the intersection of formal methods with emerging technologies like large language models and machine vision systems. Professor Chechik maintains an active research lab focused on model-based software engineering, with projects spanning software product lines, model management, and verification techniques. Her team collaborates with industry partners to address real-world software engineering challenges while advancing theoretical foundations. Current work includes developing techniques for normative requirements operationalization, machine vision reliability analysis, and automated code reconciliation using AI techniques.

Marina Leontiadouمشاهده پروفایل

دانشیار

• Ultrafast charge dynamics
• Solar cell efficiency
• Light harvesting materials
• +۲ مورد دیگر

Dr. Marina Leontiadou is an Associate Professor at the University of Salford within the School of Science, Engineering & Environment. She serves as Head of Research for the Physics Group and Programme Leader for the STEM Foundation Year. Her academic journey includes BSc and MSc degrees in Physics from the University of Cyprus, followed by a PhD at the University of Surrey's Advanced Technology Institute studying spin-dynamics in semiconductor structures. After postdoctoral research at the University of Manchester's Photon Science Institute focusing on photovoltaic materials, she joined Salford in 2018 as a Lecturer (Assistant Professor), where she was promoted to Reader (Associate Professor) in 2022. Dr. Leontiadou's research focuses on: Ultrafast charge dynamics in novel semiconductor materials Solar cell efficiency enhancement through novel materials Light harvesting materials for renewable energy applications Colloidal quantum dots and their optoelectronic properties Novel materials development for sustainable energy solutions Her publication record demonstrates sustained expertise in quantum dot physics and renewable energy materials. Over the past decade, her work has progressively focused on charge carrier dynamics in quantum dot systems, examining how surface chemistry and material composition affect photovoltaic performance. A notable trend in her recent work is exploring less toxic alternatives to traditional quantum dot materials, with several publications on indium-based systems as potential replacements for cadmium-containing quantum dots. Dr. Leontiadou has received significant recognition: Member of the Board of Trustees of the Greek School of Manchester (2025) IOP Award Committee member (2022) Committee member of IOP Materials and Characterization Special Interest Group (2021) Successful leadership of Salford's Physics department through IOP Juno Practitioner status (2018, renewed 2022) Staff Lead for Equity, Diversity and Inclusion in Human and Natural Sciences Directorate (2021-2023) Co-chair of the Athena Swan Self-Assessment Team (2021-2023) As an educator, she leads the STEM Foundation Year program preparing students for Physics, Acoustics, Mathematics, and Electrical & Electronic Engineering degrees. She teaches in the BSc Physics program and supervises undergraduate and postgraduate research. She has secured research funding including the Research Impact Fund (2020-2021) for the 'PhysConnect' project and Research Capital Investment Fund (2022-2023) for an ultrafast laser system. She actively contributes to the Centre for Future Engineering research center and has organized the International Day of Women and Girls in Science annually since 2021. Dr. Leontiadou maintains international collaborations through the GreenConnect project building connections across Cyprus's green line using green solutions. She serves as External Supervisor and Visiting Academic at the University of Manchester's Department of Materials.