جست‌وجوی استاد و پژوهشگر

Alexandra Rouletمشاهده پروفایل

استادیار

• Labour Economics
• Gender Economics
• Public Economics
• +۳ مورد دیگر

Alexandra Roulet serves as Assistant Professor of Economics at INSEAD and holds a CEPR Research Fellowship. Previously, she advised President Macron and Prime Minister Borne on economic policy from June 2022 to September 2023. Education: Ecole Normale Supérieure (Paris) PhD in Economics, Harvard University (2017) Research Focus: Her work centers on labour economics with specialized attention to gender wage disparities, job search dynamics, and unemployment insurance impacts. She integrates environmental economics through analysis of technological choices under market competition, and explores education economics via school tracking effects on mental health. Methodologically, she leverages administrative datasets and firm-level analysis for causal inference in policy-relevant contexts. Publication Trends: Recent outputs (2017-2022) reveal consistent investigation of labour market structures, particularly gendered firm-level wage effects and spatial job search behavior. Her research demonstrates interdisciplinary expansion into environmental innovation and educational policy, characterized by rigorous quasi-experimental designs using French administrative data. Scientific Recognition: 2017 Upjohn Institute Dissertation Award (co-winner) Professional Engagement: As an INSEAD faculty member, she contributes to graduate education and research supervision. Her government advisory role underscores direct policy impact, particularly in French economic strategy. The CEPR affiliation connects her to pan-European economic research networks for collaborative projects. Research Infrastructure: Her CEPR Research Fellowship provides access to extensive academic networks and policy forums, facilitating data-sharing partnerships and interdisciplinary collaboration across European institutions.

Jian Zhangمشاهده پروفایل

استاد

• Computer Vision
• Pattern Recognition
• Data Analytics
• +۳ مورد دیگر

Prof. Jian Zhang is a Professor in the School of Electrical and Data Engineering at the University of Technology Sydney (UTS), specializing in computer vision, pattern recognition, and multimedia signal processing. He leads the Multimedia Data Analytics Lab at the Global Big Data Technologies Centre, focusing on agri-food sector applications such as livestock monitoring and AI-driven solutions for agricultural efficiency. Education : PhD, School of Information Technology and Electrical Engineering, University of New South Wales, 1999 MSc, The Flinders University of South Australia, 1994 BSc, East China Normal University, 1982 Research Interests : His work spans 2D/3D computer vision, large-scale image/video analytics, and cross-disciplinary projects in agriculture and remote sensing. He has pioneered AI systems for livestock counting, poultry welfare monitoring, and fish quality assessment, funded by organizations like Meat & Livestock Australia and Australian Eggs. Grants & Projects : Current projects include AI-based hen health monitoring ($5M+ funding since 2011) Collaborations with industry partners like Sydney Fish Market and Fremantle Port Students & Academic Leadership : Supervised 19 PhD graduates and 5 research fellows Recruiting new PhD candidates in computer vision and data analytics Labs & Teams : Director of the Multimedia Data Analytics Lab, collaborating with global experts through UTS's Distinguished Visiting Scholars program.

Marcelo Fioreمشاهده پروفایل

استاد

• Category Theory
• Lambda Calculus
• Equational Logic
• +۵ مورد دیگر

Marcelo Fiore is a Professor in Mathematical Foundations of Computer Science at the Department of Computer Science and Technology, University of Cambridge, and a Fellow of Christ's College. His research spans category theory, lambda calculus, equational logic, type theory, and mathematical structures in computer science. University: University of Cambridge Department: Department of Computer Science and Technology Academic Rank: Professor College Affiliation: Christ's College Fiore's work focuses on the intersection of category theory and computer science, particularly in abstract syntax, denotational semantics, and algebraic structures. Recent publications explore combinatorial models, normalization by evaluation, and homotopy type theory applications. 2025: Creation/annihilation operators in mathematical structures 2024: Lawvere theories in toposes and differential linear logic 2023: Homotopy type theory and normalization frameworks 2022: Second-order abstract syntax formalization and quotient types Fiore has advised PhD students including N. Arkor (2022) and O.M. Elsayed (2011), who researched monadic structures and second-order algebraic theories respectively. He contributes to departmental initiatives such as the Accelerate Programme for Scientific Discovery and Data Trusts Initiative at Cambridge.

Yuntian Dengمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Yuntian Deng is an Assistant Professor at the University of Waterloo and a Visiting Professor at NVIDIA. He holds affiliations with Harvard SEAS as an Associate and the Vector Institute as a Faculty Affiliate. He completed his PhD in Computer Science at Harvard under Professors Alexander Rush and Stuart Shieber, followed by a postdoc under Yejin Choi. His research focuses on Natural Language Processing and Machine Learning, with notable contributions in chatbot interaction analysis (WildChat), implicit reasoning models, and markup-to-image generation. He has developed influential tools like OpenNMT and WildVis, and his work has been featured in outlets like the Washington Post and used by OpenAI and Anthropic. Education: PhD in CS (Harvard), Postdoctoral Research (University of Washington). Key achievements include the ACM Gordon Bell Prize for GenSLMs, Best Demo Runner-up at ACL 2017, and Best Paper at DAC 2020. His research emphasizes scalable datasets, efficient reasoning techniques, and real-world applications of AI models. Research interests span NLP, machine learning algorithms, and their applications in areas like dialogue systems, generative models, and ethical AI evaluation. Notable projects include WildChat (1M ChatGPT interactions), implicit chain-of-thought reasoning, and neural steganography for text-based information hiding. His articles explore topics ranging from knowledge distillation to diffusion models, with a focus on bridging theoretical advancements and practical implementations. He actively collaborates with industry partners like NVIDIA and maintains open-source tools to advance AI research accessibility.

Dewei Yiمشاهده پروفایل

مدرس ارشد

• Computer Vision
• AI-enabled Healthcare
• Hybrid Intelligent Systems
• +۱۶ مورد دیگر

Dewei Yi is a Senior Lecturer (Associate Professor) in the Department of Computing Science, School of Natural and Computing Sciences at the University of Aberdeen, UK. He holds a PhD from Loughborough University and is an active researcher in AI, computer vision, and intelligent systems. He serves as Director of the MSc AI and MSc Robotics and AI programmes. Research Interests: His research spans AI-enabled healthcare, medical image processing, intelligent vehicles, robotics, precision agriculture, remote sensing, and applied machine learning. He focuses on hybrid intelligent systems, personalised AI, federated learning, fairness, and explainability. Recent Publication Trends: His latest work includes medical image quality evaluation using contrastive learning, federated learning for diabetic retinopathy, UAV-based solar panel inspection, vascular image analysis, and emotion recognition from ECG data, reflecting a strong trend toward healthcare and intelligent systems with real-world impact. Scientific Awards: Fellow of the Higher Education Academy (FHEA) Outstanding Reviewer, Transportation Research Part C (TRC) Advising and Grants: Dr Yi supervises multiple PhD students in AI, computer vision, and machine learning. His graduated PhDs include Debinal Bakyavathi Rajan, Sami Hamid Al Sulaimani, and Adinath Abhimanyu Ghadage. He has secured significant funding as PI and Co-PI, including a £408K Smartawl 5.0 project and a £794K Cancer Research UK grant (Co-PI). Labs and Teams: He leads research in AI for healthcare and intelligent vehicles, collaborating with institutions like University of Warwick, Loughborough University, and industry partners such as AVL Powertrain Ltd. His work is supported by interdisciplinary teams focusing on embedded AI, medical applications, and sustainable technologies.

• Type Theory
• Dependent Types
• Functional Programming
• +۱۱ مورد دیگر

Andreas Abel is a Senior Lecturer in the Division of Computing Science at the Department of Computer Science and Engineering, Chalmers University of Technology and the University of Gothenburg. He has previously served as an Assistant Professor at Ludwig-Maximilians-Universität (LMU) Munich and has been a visiting researcher at INRIA in Paris. His primary affiliations are with Chalmers and the University of Gothenburg, where he conducts research and teaches in programming languages and type theory. Chalmers University of Technology, Department of Computer Science and Engineering, Senior Lecturer University of Gothenburg, Division of Computing Science LMU Munich, Assistant Professor (former) INRIA Paris, Visiting Researcher Abel’s research lies at the intersection of type theory, functional programming, and formal verification. He is particularly known for his work on dependent types, normalization by evaluation, and the development of the Agda proof assistant. His interests include constructive logic, logical frameworks, modal and linear typing, program verification, and compiler construction. He leads the Modal Dependent Type Theory project funded by the Swedish Research Council (Vetenskapsrådet) and has contributed to several other major research initiatives in programming language theory. His recent publications reflect a strong focus on foundational aspects of type systems, including cubical type theory, decidability of conversion, and formalization of algebraic completeness. These works appear in top-tier venues such as ICFP, LICS, POPL, and TYPES, showcasing both theoretical depth and practical implementation in Agda. Distinguished Paper Award, ICFP 2019 Editor, Theoretical Pearls column, Journal of Functional Programming Member, IFIP WG 1.3 on Foundations of System Specification Abel actively supervises students and contributes to the research community through program committee memberships for major conferences including LICS, ICFP, and CPP. He is a senior developer of Agda and the maintainer of the BNFC (Backus-Naur Form Compiler) tool. His work bridges theoretical computer science with practical software development for formal methods. He is involved in several research groups and projects, including the Programming Logic Group at Chalmers and the international EUTYPES network. His role as principal investigator and core contributor in multiple funded projects highlights his leadership in the field of programming language foundations.

Maria Francesca Spadeaمشاهده پروفایل

استاد

• Medical Image Processing
• Artificial Intelligence in Healthcare
• Radiomics
• +۵ مورد دیگر

Prof. Dr.-Ing. Maria Francesca Spadea serves as Director of the Institute of Biomedical Engineering (IBT) at Karlsruhe Institute of Technology (KIT), part of the Helmholtz Association. Her leadership role includes overseeing research initiatives, teaching activities, and administrative responsibilities within the institute. Located in space 512, she maintains regular consultation hours on Wednesdays from 10:30-11:30 am by appointment. Professor Spadea's research spans several cutting-edge areas in biomedical engineering, with particular focus on medical image processing, artificial intelligence applications in healthcare, and radiomics. Her work bridges computational techniques with clinical applications, emphasizing practical solutions for medical imaging challenges. She has pioneered approaches in federated learning for medical image translation, particularly in CT/MRI synthesis for radiation therapy applications. Her research also extends to cancer cell analysis, vascular biomechanics, and medical robotics, demonstrating a broad yet cohesive research portfolio that addresses critical challenges in modern healthcare. Analysis of Professor Spadea's recent publications reveals a strong emphasis on AI-driven medical imaging solutions, particularly in the translation between different imaging modalities (like MRI-to-CT) using federated learning approaches that preserve patient privacy. Her work demonstrates growing specialization in radiation therapy applications, with multiple publications addressing synthetic CT generation for treatment planning. There's also a clear trajectory toward multi-institutional collaboration, as evidenced by her involvement in projects spanning multiple research centers across Europe. Professor Spadea actively mentors numerous students, including M. Krohmer Zabaleta, N. Skupien, and M. Destito, who have completed bachelor's and master's theses under her supervision. Her research group appears well-integrated within the broader Institute of Biomedical Engineering, collaborating extensively with colleagues like P. Zaffino and C.B. Raggio on multiple projects. The group maintains strong connections with clinical partners, as evidenced by publications addressing real-world medical challenges in radiation therapy, cardiology, and neurosurgery. The research activities of Professor Spadea's team are centered within the Institute of Biomedical Engineering at KIT, with particular focus on medical imaging processing and AI applications. Her laboratory appears to specialize in developing computational tools for medical image analysis, with recent work emphasizing privacy-preserving federated learning frameworks that enable multi-institutional collaboration without sharing sensitive patient data. The team maintains active collaborations with clinical departments, particularly in radiation oncology, as evidenced by numerous publications addressing CT synthesis for radiation therapy planning.

• Echocardiography
• Cardiac Imaging
• Right Heart Function
• +۵ مورد دیگر

Karima Addetia serves as an Associate Professor in the Department of Medicine-Cardiology at the University of Chicago. Her academic career has been dedicated to advancing echocardiographic techniques and their clinical applications, particularly in the assessment of right heart function, cardiac amyloidosis, and tricuspid valve pathology. She has established herself as a leading researcher in cardiac imaging through extensive collaborations with the World Alliance of Societies of Echocardiography (WASE) and frequent co-authorship with Dr. Roberto M. Lang, a prominent figure in cardiovascular imaging. Dr. Addetia's research interests span multiple critical areas in cardiovascular medicine. She has pioneered work in right heart assessment, establishing normative values for right ventricular size and function through large-scale multicenter studies. Her investigations into cardiac amyloidosis have significantly advanced the understanding of echocardiographic patterns associated with this condition, particularly regarding apical sparing and strain patterns. She has also made substantial contributions to tricuspid valve assessment, examining both normal anatomy and pathological conditions including device-related complications. More recently, her work has incorporated artificial intelligence applications in echocardiography, exploring how machine learning can improve diagnostic accuracy and workflow efficiency. The trajectory of Dr. Addetia's research publications reveals a consistent focus on quantitative cardiac imaging with increasing sophistication over time. Her early work established foundational knowledge about right ventricular morphology and function, while more recent publications integrate advanced technologies like AI and focus on specific disease states like cardiac amyloidosis. A notable pattern is her participation in large, collaborative studies that establish normative values across diverse populations, addressing important gaps in understanding how cardiac measurements vary by age, sex, and ethnicity. Her work consistently bridges technical echocardiographic advancements with direct clinical applications. Dr. Addetia's collaborative approach is evident through her extensive involvement with the WASE study group and numerous multicenter investigations. Her research methodology typically combines rigorous quantitative analysis with clinical correlation, producing findings that directly impact diagnostic criteria and clinical practice guidelines. While specific grant information isn't detailed in the available publications, her leadership in major collaborative studies suggests significant research funding support for her work in cardiac imaging innovation.

• Visual Neuroscience
• Eye Movement Disorders
• Nystagmus Research
• +۶ مورد دیگر

Professor Jonathan Erichsen serves as Professor of Visual Neuroscience and Deputy Head of School within the School of Optometry and Vision Sciences at Cardiff University. With a distinguished career spanning several decades, he has established himself as a leading researcher in visual neuroscience and eye movement disorders. Professor Erichsen's research has evolved from early work on central near response pathways in the brain, including vergence and the pupillary light reflex, to a broader focus on eye movement disorders. His primary research interests include the control of visuomotor behavior, eye movement abnormalities in neurodegenerative conditions, and visual function assessment in individuals with nystagmus. He has pioneered innovative methodologies including stereotaxic surgery, immunohistochemistry, neural pathway tracing, and microstimulation in his investigations. His recent publications demonstrate a clear trend toward clinical applications of eye movement research, particularly in developing better assessment tools for visual function in nystagmus patients. The research spans from fundamental neuroanatomy to practical clinical tools, with significant contributions to understanding infantile nystagmus, Huntington's disease-related eye movement abnormalities, and visual function in children. His work increasingly integrates advanced eye tracking technologies with clinical applications. Professor Erichsen founded the Cardiff Research Unit for Nystagmus (RUN) approximately twenty years ago, establishing a large cohort of volunteers with infantile nystagmus to study how environmental factors like stress affect visual performance. More recently, he established the Eye Movement Experimental Research Group (EMERG) to expand research into eye movement abnormalities associated with neurodegenerative conditions including Huntington's disease, schizophrenia risk, and dystonia. His research has demonstrated that traditional measures of visual performance, such as visual acuity, are not significantly affected by changes in eye movements of individuals with nystagmus, suggesting the need for developing better outcome measures in clinical practice. Professor Erichsen remains actively involved in postgraduate supervision and continues to produce high-impact research in visual neuroscience.

• Computer Vision
• 4D Vision
• Machine Learning
• +۹ مورد دیگر

Professor Adrian Hilton is a distinguished faculty member at the University of Surrey, serving as Director of the Centre for Vision, Speech and Signal Processing (CVSSP) and Director of the Surrey Institute for People-Centred AI. He is affiliated with the School of Computer Science and Electronic Engineering and leads the Visual Media Research Lab (V-Lab). His research focuses on pioneering next-generation 4D computer vision technologies that enable machines to understand and model dynamic real-world scenes. Key areas include 3D/4D shape capture, computer vision, machine learning, graphics, and animation for applications in sports analysis, film/TV production, virtual reality, and medical imaging. His work bridges the gap between real and computer-generated imagery, with notable contributions in volumetric capture, motion capture, and free-viewpoint video. Hilton's recent publications demonstrate a strong trend toward multimodal integration, particularly combining audio and visual processing for spatial audio applications, while advancing 4D reconstruction techniques for human performance capture. His work increasingly incorporates transformer architectures and neural rendering techniques for improved illumination estimation, shadow modeling, and multi-view consistency. Scientific Awards and Recognition Two EU IST Innovation Prizes Manufacturing Industry Achievement Award Royal Society Industry Fellowship (2008-2011) Royal Society Wolfson Research Merit Award in 4D Vision (2013-2018) Fellow of the Royal Academy of Engineering (FREng) Fellow of the International Association for Pattern Recognition (FIAPR) Fellow of the Institution of Engineering and Technology (FIET) Hilton actively mentors PhD and post-doctoral researchers through his leadership of CVSSP, which has a grant portfolio exceeding £31M and comprises 170 researchers. He has successfully commercialized several technologies, including systems used by the BBC for sports commentary visualization. His research collaborations span major industry partners including BBC, BT, Sony, Framestore, and The Foundry. He co-founded the G3 Games forum and the CVMP Conference on Visual Media Production, demonstrating strong engagement with the creative industries. Current research projects include the S3A Programme Grant in Future Spatial Audio and InnovateUK's ALIVE project for 360 video reconstruction.

• Landscape Ecology
• Urban Ecology
• Sustainability Science
• +۳ مورد دیگر

**Jianguo Wu** is the Dean’s Distinguished Professor of Landscape Ecology and Sustainability Science at Arizona State University (ASU), holding joint appointments in the School of Life Sciences and School of Sustainability. His affiliations include the Center for Biodiversity Outcomes, Water Institute, Global Drylands Center, and roles as Senior Global Futures Scientist. He earned his B.S. from Inner Mongolia University and M.S./Ph.D. from Miami University, followed by NSF postdoctoral fellowships at Cornell and Princeton Universities. **Education**: B.S. in Biology, Inner Mongolia University (1982) M.S. in Ecology, Miami University (1987) Ph.D. in Ecology, Miami University (1991) **Research Interests**: Landscape ecology, urban ecology, biodiversity-ecosystem functioning, and landscape sustainability science. His work emphasizes ecosystem services, human wellbeing linkages, and interdisciplinary solutions to global environmental challenges. **Awards**: Includes AAAS Fellow (2007), Leopold Leadership Fellow (2009), Distinguished Landscape Ecologist Award (2010), and recognition as a Web of Science Highly Cited Researcher (2019–2020). **Service & Leadership**: Editor-in-Chief of Landscape Ecology since 2005, Founding Director of the Sino-US Center for Conservation, Energy, and Sustainability Science (2007–present), and leader in multiple international editorial and advisory roles. **Labs/Teams**: Directs the Center for Human-Environment System Sustainability (CHESS) at Beijing Normal University and contributes to interdisciplinary initiatives like the Global Futures Scientists and Scholars program.

Hugo Paquetمشاهده پروفایل

پژوهشگر

• Probabilistic Programming
• Categorical Semantics
• Game Semantics
• +۴ مورد دیگر

Hugo Paquet is a Researcher at INRIA Paris and a member of the ANTIQUE team at École Normale Supérieure , PSL University. He completed a PhD in Computer Science (2015–2019) at the University of Cambridge under Glynn Winskel , focusing on concurrent game semantics for probabilistic programming. His postdoctoral work includes positions at LIPN, Paris (2022–2024, funded by a Marie Skłodowska-Curie Award) and University of Oxford (2020–2022). He has contributed to conferences including LICS , ESOP , FSCD , and POPL . Education : PhD in Computer Science (University of Cambridge, 2019) Research Interests : Probabilistic programming (semantics, inference algorithms, nonparametric models), categorical semantics (game semantics, concurrency models, adjunctions), combinatorial species, and 2-dimensional categories. Teaching : Category Theory (2023–2024), Bayesian Statistical Probabilistic Programming (2021–2022), Lambda-calculus and Types (2020–2021), and small-group teaching at Cambridge (Logic, Discrete Mathematics, Semantics). Awards : Marie Skłodowska-Curie Award under the Paris Region Fellowship Programme Labs : INRIA Paris, ANTIQUE team (2024–present)

• Quantum Science and Technology
• Condensed Matter Experiment
• Superconductivity
• +۴ مورد دیگر

Kasra Sardashti is an Assistant Professor of Physics at the University of Maryland and Principal Investigator at the Laboratory for Physical Sciences. He holds a Ph.D. in Materials Science and Engineering from UC San Diego (2016), and previously served as Assistant Professor of Physics & ECE at Clemson University. His research focuses on hybrid superconductor-semiconductor systems for quantum information processing, sensing, and communication through the Laboratory for Band Engineering of Quantum Systems (LaBEQs). Key research areas include band engineering at superconductor-normal material interfaces, advanced materials growth, nanofabrication, and low-temperature physics. His work is supported by NSF, DOE, AFOSR, and DARPA. He has pioneered voltage-tunable superconducting devices and hybrid quantum systems, with applications in classical-quantum processors and sensors. Notable contributions include studies on niobium-germanium interfaces and epitaxial superconducting heterostructures. Education: Ph.D. in Materials Science & Engineering, UC San Diego (2016) Previous Roles: Research Scientist, Center for Quantum Phenomena, NYU He received the 2021 ORAU Powe Junior Faculty Enhancement Award. His lab actively recruits postdocs, graduate students (Physics/Chemistry/Engineering), and undergraduates. Recent milestones include the 2024 Summer Internship Program and graduating an M.S. student. LaBEQs emphasizes interdisciplinary collaboration, integrating materials science, quantum engineering, and cryogenics. Ongoing projects explore low-loss materials for superconducting electronics and piezo-acoustic quantum transduction in complex oxide heterostructures.

Emily Callanderمشاهده پروفایل

استاد

• Health Economics
• Women's Health
• Maternal Health
• +۱۱ مورد دیگر

Emily Callander is a Professor of Women’s Health Economics at the Monash Centre for Health Research and Implementation, Monash University, and Head of Discipline in Health Services Management at the University of Technology Sydney (UTS). She leads the Women’s Economics and Value Based Care research program and holds leadership roles in national health policy, including as Vice President of Women's Healthcare Australasia and member of the Pharmaceutical Benefits Advisory Committee Economics Subcommittee. BA in Economics and Policy, Griffith University PhD in Health Economics, University of Sydney Postdoctoral training at NHMRC Clinical Trials Centre and Charles Perkins Centre, University of Sydney Her research focuses on maternal and women's health, utilizing linked administrative data, economic evaluation, and modelled analysis to influence health policy and delivery. Her work spans efficient staffing models, rural health access, national maternity initiatives (e.g., Safer Baby Bundle, Normal Birth Strategy), and cost analyses for global maternal health programs supported by the Gates Foundation. Her recent publications reflect a strong trend in health economic evaluations of maternity care models, medication use in pregnancy, digital health implementation, and preterm birth prevention. These works emphasize real-world applicability, equity, and cost-effectiveness, aligning with her mission to embed economic evidence into health systems. She has been supported by prestigious NHMRC awards, including a Doctoral Scholarship, Early Career Fellowship, and Career Development Fellowship. Her scientific contributions are recognized through active research projects and expert media commentary on maternity care policy. NHMRC Doctoral Scholarship NHMRC Early Career Fellowship NHMRC Career Development Fellowship Emily Callander advises on multiple national and international research projects, often as Chief or Associate Investigator, and collaborates with institutions such as Coventry University. She is actively accepting PhD students and contributes to policy through advisory roles in government and non-profit organizations. Her research is supported by grants from NHMRC, government departments, and international foundations. She leads the Women’s Economics and Value Based Care program at Monash and is a key member of the Transforming Maternity Care Collaborative. Her work is embedded in real-world health systems, partnering with consumers, providers, and policymakers to improve women’s health outcomes globally.

Daniel Kasperمشاهده پروفایل

پژوهشگر

• Evaluation of Education Systems
• Primary School Research
• Educational Disparities
• +۴ مورد دیگر

Daniel Kasper is a researcher at the University of Hamburg's Faculty of Education, specializing in Educational Science with a focus on International Educational Monitoring and Reporting. He currently serves as the National Project Manager for TIMSS 2027, continuing his leadership role from previous TIMSS cycles (2023, 2019). His work centers on large-scale educational assessments, statistical methodology, and primary education research. Dr. Kasper completed his Habilitation in Educational Science with special consideration of empirical educational research at TU Dortmund (2012-2020), followed by his PhD in Educational Science at the same institution (2010-2012). He earned his Diploma in Educational Science from the University of Münster (2001-2007). His research interests span evaluation of education systems, primary school research, educational disparities, and advanced statistical methods in education. He has developed significant expertise in TIMSS methodology, multilevel modeling, and analysis of large-scale assessment data, with numerous publications addressing methodological challenges in international comparative studies. Analysis of his 15 most recent publications reveals a strong focus on TIMSS methodology and results, particularly regarding mathematics and science competencies in primary education. His work demonstrates expertise in statistical methodology for educational assessment, with several publications developing and refining analytical techniques for large-scale data. A recurring theme is examining educational disparities related to student composition, socioeconomic factors, and gender differences. Dr. Kasper has served as National Project Manager for multiple TIMSS cycles (2019, 2023, 2027) and has been involved in PIRLS studies, demonstrating sustained leadership in major international educational assessments. His work bridges methodological innovation with practical application in educational monitoring. He teaches courses across all academic levels, including 'Introduction to Empirical Research Methods' for Bachelor students, 'Methods of Empirical Educational Research' for Master students, and advanced workshops on longitudinal scaling and the Rasch model for doctoral candidates. His teaching reflects his dual expertise in educational research methodology and statistical analysis.