جست‌وجوی استاد و پژوهشگر

Günter Barczikمشاهده پروفایل

استاد

• Computational Design
• Digital Representation Theory
• Algebraic Geometry in Architecture
• +۷ مورد دیگر

Professor Günter Barczik serves as a Full Professor at the University of Applied Sciences Erfurt within the Faculty of Architecture and Urban Planning, holding the Professorship for Design, Digital Representation Theory and Computational Design. He has been in this position since September 2011 and previously served as an Assistant Professor at Brandenburg University of Technology Cottbus-Senftenberg from October 2004 to October 2010. His office is located at Schlüterstraße 1, Room 414, and he also serves as the Equal Opportunities Officer for the institution. Barczik's research interests center on computational approaches to architectural design, with particular focus on digital representation theory, immersive technologies, and the application of algebraic geometry in architectural contexts. His work explores how mathematical concepts can expand architectural vocabulary and how new technologies can transform traditional design processes. He investigates the intersection of computational tools with creative thinking, sustainable architecture practices, and visual communication methods. Analysis of Barczik's publication history reveals a consistent trajectory exploring the integration of computational methods with architectural design. His work demonstrates a progression from fundamental explorations of algebraic surfaces in architecture (2009-2012) toward more applied investigations of immersive technologies, team dynamics in design processes, and the evolving relationship between designers and digital tools. A recurring theme throughout his research is the examination of how computational techniques can enhance traditional design thinking while addressing contemporary challenges in urban planning and architectural representation. With 22 publications accumulating 5,886 reads and 65 citations, Barczik has established himself as a significant contributor to computational design discourse. His work connects architecture with mathematics, computer science, and interdisciplinary team dynamics, reflecting a holistic approach to design education and practice. His research demonstrates consistent engagement with both theoretical frameworks and practical applications of computational design methods in architectural education and professional practice.

Zhong Lingمشاهده پروفایل

استادیار

• Labor Economics
• Economics of Education
• Personnel Economics

Dr. Zhong Ling is an Assistant Professor of Economics at Cheung Kong Graduate School of Business (CKGSB). She holds a Ph.D. in Economics from Yale University and a B.A. in Mathematics and Economics from Swarthmore College (graduated with High Honors). Her primary affiliations include research roles at CKGSB where she focuses on labor dynamics, education economics, and workforce analysis. Her research interests center on three interconnected domains: Labor Economics : Examining wage structures, skill demands, and gender disparities in employment Economics of Education : Investigating returns on educational investment and policy impacts Personnel Economics : Analyzing employer-employee relationships and workplace organization Recent publications demonstrate a strong focus on pandemic-related economic impacts, including labor market transformations during COVID-19, epidemiological modeling for public policy, and resource allocation strategies during health crises. Her work frequently employs advanced statistical modeling and interdisciplinary approaches. Awards & Fellowships: University Dissertation Fellowship, Yale University (2018-2019) Carl Arvid Anderson Prize Fellowship (2017) Phi Beta Kappa induction (2013) Multiple Yale scholarships including Fan Family Fellowship and Daniel Lathrop Lawton Scholarship Media engagements include expert commentary for CGTN on China's birth rate policies and workforce involution trends, showcasing her public policy relevance.

Andreas Wenzelمشاهده پروفایل

استاد

• Embedded Systems
• Diagnostic Systems
• Neural Networks
• +۶ مورد دیگر

Prof. Dr.-Ing. Andreas Wenzel is a Professor at Schmalkalden University of Applied Sciences in the Faculty of Electrical Engineering, specializing in Embedded Systems. His office is located in Building M, Room 0401, and he can be reached at +49 3683 688 5113. With a distinguished research career spanning over two decades, Prof. Wenzel has established himself as a leading expert in embedded diagnostic systems with applications across multiple domains including biomedical engineering, industrial automation, and assistive technologies. Prof. Wenzel's primary research interests focus on the development and application of embedded diagnostic systems, with particular emphasis on neural networks for pattern recognition, fuzzy logic systems for classification problems, and real-time monitoring solutions. His work bridges theoretical machine learning approaches with practical engineering applications, resulting in innovative solutions for quality control in manufacturing processes, medical diagnostics, and mobility assistance technologies. He has made significant contributions to EEG data analysis for sleep stage and anesthesia depth monitoring, as well as developing smart systems for injection molding quality assessment and advanced mobility solutions for elderly individuals. Analysis of Prof. Wenzel's publication record reveals a consistent research trajectory focused on applying computational intelligence to solve practical engineering problems. His work demonstrates exceptional versatility across domains while maintaining a cohesive research theme centered on embedded diagnostic systems. From 2012-2016, his research output shows increasing focus on real-time embedded solutions with industrial applications, particularly in manufacturing quality control and assistive technologies, while continuing his foundational work in biomedical signal processing. The interdisciplinary nature of his research is evident in collaborations with medical professionals, industrial partners, and robotics specialists. Prof. Wenzel leads the Embedded Diagnostic Systems Research Group at Schmalkalden University of Applied Sciences, which maintains strong industry partnerships, particularly in plastics manufacturing and medical technology sectors. His team develops practical embedded solutions that address real-world challenges in production quality monitoring, medical diagnostics, and mobility assistance. The research group's work is characterized by its practical orientation, with many projects resulting in deployable systems rather than purely theoretical contributions. Prof. Wenzel's strategic focus on applied research ensures that his work has direct industrial relevance and practical impact.

• Cancer genetics
• Somatic evolution of cancer
• Biostatistics
• +۵ مورد دیگر

Jeffrey Townsend is the Elihu Professor of Biostatistics and Professor of Ecology and Evolutionary Biology at Yale University. He serves as Co-Director of the Genetics, Genomics, and Epigenetics Program of the Yale Cancer Center and Co-Chair of the Cancer Evolution Working Group of the American Association for Cancer Research. His academic journey began with a Biology degree from Brown University (1994), followed by a PhD in Organismic & Evolutionary Biology from Harvard University (2002), and a Miller Fellowship at UC Berkeley (2004). Professor Townsend's research spans two primary areas: cancer genetics/epidemiology and biostatistical modeling of disease spread. His lab develops algorithmic approaches to identify cancer-causing mutations by applying evolutionary theory to somatic mutation patterns. In epidemiology, he pioneers probabilistic methods for modeling disease transmission that account for parameter uncertainty, providing more robust public health guidance. His work bridges evolutionary biology, biostatistics, and medical research with significant implications for personalized cancer treatments and infectious disease control strategies. His research interests encompass cancer evolution, genomic analysis, infectious disease modeling, and evolutionary biology applications to medicine. Townsend's publications reveal a strong focus on mutation patterns in lung cancer, viral evolution, and mathematical approaches to understanding disease dynamics. His recent work includes analyses of KRAS mutations in NSCLC, the evolution of SARS-CoV-2 immunity, and precision projections for delaying resistance mutations in cancer therapy. Reducing Disease Risk Research Award (2023, Yale School of Public Health) Translational Research Prize (2016, Yale Cancer Center) Young Investigator's Prize (2005, American Society of Naturalists) Top Four Life Science Theses (2002, Council of Graduate Schools) Walter M. Fitch Prize for Best Young Investigator (2001) Professor Townsend advises graduate students and postdoctoral researchers in the Townsend Lab, where they work at the intersection of evolutionary biology, biostatistics, and medical research. His lab maintains active collaborations with Yale's Cancer Center, School of Public Health, and numerous co-authors including Francesc Lopez-Giraldez, Zheng Wang, and Alison Galvani. Current projects focus on cancer evolution mechanisms, optimal timing for vaccine boosters, and mathematical models that incorporate uncertainty for public health decision-making. The Townsend Lab operates at 60 College Street, 7th Floor in New Haven, Connecticut, with close connections to Yale's Cancer Center and School of Public Health. The lab's research has practical applications in developing personalized cancer treatments and informing public health policy for infectious disease control, demonstrating the translational impact of Townsend's interdisciplinary approach to biomedical research.

Mathias Sablé-Meyerمشاهده پروفایل

پژوهشگر ارشد

• Mechanistic implementation of compositional mental representation
• Geometry perception in humans and non-human primates
• Human reasoning and cognitive fallacies
• +۵ مورد دیگر

Mathias Sablé-Meyer is a Postdoctoral Researcher at University College London's Sainsbury Wellcome Centre, working in Tim Behrens's lab. He completed his PhD under the supervision of Stanislas Dehaene at PSL/Collège de France and NeuroSpin, CEA, where he investigated humans' ability to manipulate highly abstract structures, particularly focusing on the perception of geometry. His research spans cognitive neuroscience, computational modeling, and experimental psychology, with a focus on understanding the mechanistic implementation of compositional mental representations. He employs methodologies including MEG, fMRI, behavioral experiments, and computational models to investigate how humans mentally represent abstract structures like geometric shapes, language, and mathematical concepts. Sablé-Meyer's work reveals fascinating insights about human cognitive uniqueness, particularly in geometric perception compared to non-human primates. His recent research examines sequence processing mechanisms and aims to establish foundations for mechanistic implementations of Language of Thought models. He has published in top journals including Cognitive Psychology , Trends in Cognitive Sciences , PNAS , and Journal of Neuroscience . Glushko Dissertation Prize from the Cognitive Science Society (2023) As a supervisor, he co-advises Master's students including Maxime Cauté, who is exploring cross-modal representation of sequences, and is involved with several other students including Svenja Kuchenhoff, Amy Wong, and others. His lab follows open science principles, with code systematically published on the Open Science Framework alongside articles. His research program bridges cognitive science, neuroscience, and artificial intelligence, with implications for understanding both human cognition and developing more human-like AI systems. He maintains active collaborations across institutions including UCL, Collège de France, MIT, and École Normale Supérieure.

• Algorithms
• Bioinformatics
• Comparative Genomics
• +۵ مورد دیگر

Séverine Bérard is a Lecturer in the Computer Science Department at the Faculty of Sciences, University of Montpellier, where she holds a Habilitation à Diriger des Recherches (HDR) since 2016. Her institutional roles include: Co-director of the Bioinformatics Master's program Elected member of the University Board of Directors (since 2021) Elected member of the Faculty of Sciences Council (since 2017) Appointed member of the University Training Committee (since 2016) Her research at ISE-M's Phylogeny and Molecular Evolution Team bridges computer science and bioinformatics, with core focuses on: Development of text algorithms and graph-based methods for genomic analysis Comparative genomics and ancestral genome reconstruction Quality assessment of genome assemblies and meta-assemblies Evolutionary modeling of chromosome rearrangements Her recent publications (2016-2021) demonstrate strong emphasis on algorithmic innovations for evolutionary genomics, including genome scaffolding techniques, DCJ rearrangement models, and ancestral genome reconstruction methods applied to organisms ranging from mosquitoes to bacteriophages. In education, she teaches across all academic levels (L1-M2) in both practical computer science (networks, programming) and theoretical disciplines (discrete mathematics, text algorithms), while leading curriculum development as co-director of the Bioinformatics Master's program.

Angelo Vallerianiمشاهده پروفایل

استاد پژوهشی

• Stochastic Processes
• RNA Biology
• Population Genetics
• +۸ مورد دیگر

Dr. Angelo Valleriani serves as Group Leader for Stochastic Processes in Complex and Biological Systems at the Max Planck Institute of Colloids and Interfaces in Potsdam, Germany, and coordinates the International Max Planck Research School (IMPRS) on Multiscale Bio-Systems. His research bridges theoretical physics and biological applications with a focus on quantitative modeling of complex biological phenomena. Dr. Valleriani earned his PhD in High Energy Physics from SISSA in Trieste, Italy (1996), following a Laurea Degree in Theoretical Physics from the University of Bologna (1992) with full marks and honors. His academic journey includes Visiting Scientist positions at Max Planck Institutes in Golm and Dresden before becoming a Group Leader in November 2000. His research interests encompass: Stochastic modeling of biological processes RNA biology and translational control mechanisms mRNA and tRNA turnover dynamics Population genetics and evolutionary biology Biostatistical data analysis Dr. Valleriani's recent publications (2022-2024) reveal a strong emphasis on computational approaches to biological problems, particularly in ribosome dynamics, protein synthesis regulation, and cellular remodeling processes. His work demonstrates sophisticated integration of mathematical modeling with experimental biology. He maintains active collaborations with researchers from multiple institutions including the University of Potsdam (Silke Leimkühler, Carsten Beta, Stefanie Barbirz), University of Cambridge (Davide Chiarugi), Weizmann Institute (Ziv Reich, Ruti Kapon), DRFZ Berlin (Ria Baumgrass), and others. The research group actively recruits MSc students from physics, mathematics, engineering, and bioinformatics backgrounds for challenging thesis projects in computational biology and biophysics.

Shiva Nejatiمشاهده پروفایل

استاد

• Software Testing and Verification
• Cyber Physical Systems
• Applications of AI to Software Engineering
• +۴ مورد دیگر

Shiva Nejati is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, where he leads research in software engineering with a focus on verification and analysis of cyber-physical systems. Previously, he served as a senior scientist (2012-2019) at the SnT Center, University of Luxembourg, and as a scientist (2009-2012) at the Simula Research Laboratory. He earned his M.Sc. and Ph.D. from the University of Toronto in 2003 and 2008, respectively. His research interests span Software Testing and Verification, Cyber Physical Systems, Applications of AI to Software Engineering, and Search-based Software Engineering. Nejati's work draws on techniques from formal software modeling, meta-heuristics optimization, machine learning, system engineering, and empirical methods. He has extensively worked on testing and fault localization of cyber physical systems, particularly applied to autonomous vehicles and IoT systems, while also exploring requirements traceability, automated configuration of product line systems, and simulation modeling of CPS. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional software verification techniques, particularly for complex cyber-physical systems. His work bridges search-based testing with formal verification methods to address the challenges of testing compute-intensive models in domains like autonomous vehicles and satellite systems. The research shows increasing focus on applying machine learning to solve longstanding problems in software testing and requirements engineering. Nejati serves in significant leadership roles across major software engineering conferences, including PC Chair for ASE 2026, General Chair for CASCON 2026, and various program committee and organizing committee roles for ICSE, ISSTA, MODELS, and other top-tier conferences. He is also an Associate Editor for EMSE Journal and ASE Journal, and previously served on the IEEE Transactions on Software Engineering editorial board. He teaches advanced courses including 'AI-enabled Software Verification and Testing' and 'Software Construction' at the University of Ottawa, while leading the Sedna lab which focuses on verification, analysis, and testing of complex systems. His research is conducted in close collaboration with industry partners across telecommunication, maritime, energy, automotive, and aerospace sectors.

Andrea Arcuriمشاهده پروفایل

استاد

• Software Testing
• Search-Based Software Engineering
• Automated Testing
• +۲ مورد دیگر

Andrea Arcuri is a Professor of Software Engineering at Kristiania University College in Oslo, Norway, where he leads the AISE lab. Since 2020, he also holds a part-time position as Adjunct Professor at Oslo Metropolitan University. After 5 years in industry (WesternGeco and Scienta/Telenor), he returned to academia full-time in October 2016. His research primarily focuses on automated software testing and search-based software engineering. Prof. Arcuri's research interests center around Software Testing , Search-Based Software Engineering , and Automated Testing techniques. He has made significant contributions to the field through the development of testing tools like EvoMaster for system-level test generation and EvoSuite for unit test generation. His work bridges theoretical foundations with practical applications, particularly in RESTful API testing and enterprise systems. His recent publications show a strong trend toward practical applications of search-based testing in industry settings, with particular emphasis on RESTful API testing, fuzz testing, and integration with modern development practices like DevOps. The research spans both theoretical foundations of search-based testing and practical tool development. ACM SIGSOFT Impact Paper Award 2023 for EvoSuite ICST 2022 10-Year Most Influential Paper Award ICSE 2021 10-Year Most Influential Paper Award Ranked 2nd Most Active Early Stage SE Researcher in JSS'18 Multiple Best/Distinguished Paper awards at SSBSE, ASE, and ISSTA Prof. Arcuri actively supervises PhD students and post-docs, including Iva Kertusha, Susruthan Seran, and Onur Duman. He serves in leadership roles for major conferences, including as FSE 2025 Artifact Track Chair and ICST 2022 Test Tool and Demo Track Chair. His research is supported through various academic grants and industry collaborations. He leads the AISE (Artificial Intelligence and Software Engineering) lab at Kristiania University College, where his team develops and maintains the EvoMaster system test generation tool. The lab focuses on practical applications of search-based software testing in real-world enterprise settings.

Ralf Brunsمشاهده پروفایل

استاد

• Data stream processing
• Evolutionary algorithms
• Machine learning
• +۶ مورد دیگر

Prof. Dr. Ralf Bruns is a full-time Professor in the Department of Computer Science at the Faculty of Business and Information Technology, Hannover University of Applied Sciences and Arts. His office is located at Ricklinger Stadtweg 120, 30459 Hanover, with direct contact available via phone (+49 511 9296 1817) and email. His research focuses on cutting-edge computational methodologies including: Real-time data stream processing systems Bio-inspired algorithms ( evolutionary and swarm intelligence ) Machine learning applications in enterprise systems Semantic Web technologies for knowledge representation Software architecture patterns for event-driven systems Complex Event Processing (CEP) frameworks His publications demonstrate a consistent focus on event-driven architectures applied to logistics, healthcare, IoT, and urban mobility systems. Recent work emphasizes agent-based modeling and real-time analytics for decision support in dynamic environments. Prof. Bruns leads two key research initiatives: the Software Architecture Working Group (AG SWA) and the Smart Data Analytics Research Cluster . He also serves as faculty representative in the Fachbereichstag Informatik (FBTI) and contributes to academic selection committees.