جست‌وجوی استاد و پژوهشگر

Jing Zhangمشاهده پروفایل

استادیار

• Translational Plant Phenomics
• Remote Sensing
• Robotics
• +۷ مورد دیگر

Dr. Jing Zhang is an Assistant Professor in the Department of Horticultural Science at North Carolina State University (NC State), affiliated with the NC Plant Sciences Initiative and the College of Agriculture and Life Sciences. Her research focuses on leveraging remote sensing, robotics, and data science to advance plant breeding and precision management in horticultural crops. She develops high-throughput phenotyping tools using multi-source sensor data (visual, multispectral, thermal, hyperspectral) across ground, aerial, and satellite platforms, aiding breeders in trait discovery and producers in optimizing resource use. Dr. Zhang holds a B.S. and M.S. in Agronomy and Grassland Science from South China Agricultural University, and a Ph.D. in Horticultural Science from the University of Florida. Her educational background bridges plant sciences and technology, enabling interdisciplinary approaches to agricultural challenges. Her research interests span precision agriculture applications, including UAS-based weed mapping, crop stress monitoring, and yield prediction. She collaborates actively with plant breeders and engineers to integrate machine learning and sensor technologies into crop management systems. Teaching includes introductory courses on AI applications in agriculture and specialized high-throughput phenotyping methods for students. Publications highlight her contributions to UAS-based crop monitoring, drought tolerance mechanisms in turfgrass, and phenotyping innovations. She mentors graduate students and postdocs, emphasizing multidisciplinary training. Current opportunities exist for students in computer science, engineering, or plant sciences to join her lab’s translational research efforts. Dr. Zhang’s lab is part of the Translational Plant Phenomics Program, fostering collaborations to address global food security through technology-driven solutions. Key projects include blueberry yield prediction models, sugarcane aphid infestation analysis, and drought-resistant turfgrass development.

Kuno Kurzhalsمشاهده پروفایل

پژوهشگر ارشد

• Data Visualization
• Eye Tracking
• Visual Analytics
• +۳ مورد دیگر

Kuno Kurzhals is a Research Fellow at the Institute for Visualization and Interactive Systems (VISUS) of the University of Stuttgart , affiliated with the Cluster of Excellence IntCDC . His work focuses on video visualization , eye tracking evaluation , and visual analytics for dynamic data. Research Interests : Video visualization, eye tracking, human-computer interaction, spatio-temporal analysis, and immersive environments. Recent Trends : Publications emphasize collaborative gaze analysis in AR/VR, mobile eye-tracking data processing, and gaze-adaptive interfaces. Key subfields include non-negative matrix factorization , user behavior in immersive systems , and evaluation of visualization literacy . Collaborative Work : Co-author in studies on projection displays for group gaze , collaborative molecular learning , and manufacturing process monitoring . Technical Focus : Innovations in fixation-image charts , gaze spiral visualization , and AOI transition trees for analyzing eye movement patterns. Applications : Tools developed for dance choreography planning , music practice reflection , and public transport map analysis . Labs & Teams : Affiliated with the Weiskopf Group at VISUS, contributing to the Cluster of Excellence IntCDC . Collaborates with researchers like Daniel Weiskopf , Maurice Koch , and Nelusa Pathmanathan on interdisciplinary projects.

Uğur Algancıمشاهده پروفایل

دانشیار

• Remote Sensing
• Geomatics Engineering
• Land Use and Land Cover Analysis
• +۳ مورد دیگر

Uğur Algancı is an Associate Professor at Istanbul Technical University's Department of Geomatics Engineering in the College of Engineering. His research focuses on remote sensing, satellite image processing, and artificial intelligence applications in geospatial sciences. Current projects include: 2025: Multi-sensor Bathymetric Mapping (SRP Project) 2021-2023: Satellite-Derived Bathymetry for Horseshoe Island (TUBITAK Project) Research interests span: Coastal and marine geospatial analysis Land use/land cover change detection Super-resolution image enhancement AI-driven environmental monitoring Shallow water bathymetry Geospatial decision support systems Recent work demonstrates expertise in: Deep learning for coastline segmentation Historical aerial photograph restoration Forest fire prevention systems Earthquake-related air quality analysis Antarctic bathymetric mapping

Jessica Fewمشاهده پروفایل

پژوهشگر ارشد

• Energy use in domestic buildings
• Energy Performance Certificates (EPCs)
• Smart meter data analysis
• +۳ مورد دیگر

Dr Jessica Few is a Research Fellow in Data Science and End Use Energy Demand at the Bartlett School of Environment, Energy & Resources, University College London. She has been in this position since January 2021 and leads significant research initiatives within the Smart Energy Research Lab (SERL) Observatory, contributing to national energy policy discussions. Her academic background includes: PhD in Energy and the Built Environment from UCL Energy Institute (2016-2020) Research Scientist at the National Physical Laboratory (2013-2016) MPhys Physics degree from Durham University (2009-2013) Jessica's research focuses on critical energy demand issues: Differences between Energy Performance Certificate (EPC) modeled energy use and actual metered consumption Analysis of smart meter data to understand household energy patterns Impact of economic factors like the cost-of-living crisis on energy behaviors Ventilation practices in homes from both technical and sociological perspectives Her work on EPC over-prediction has generated substantial policy impact, being cited in the Skidmore review of net zero opportunities and receiving national media coverage including features in the Daily Telegraph. She leads multiple SERL statistical reports that provide comprehensive analyses of UK domestic energy use patterns across different societal segments, utilizing data from over 13,000 households. Her current research projects include: MAGC Project with the World Bank and University of Cape Town GHG-SMETER project with BEIS investigating thermal efficiency ratings SERL-EHS project linking smart meter data with the English Housing Survey Jessica contributes to academic education as a guest lecturer for PhD and MSc programs at UCL and supervises multiple MSc dissertation students while serving as a personal tutor for the Data Science for Cultural Heritage program.

Dariusz Siudakمشاهده پروفایل

دانشیار

• Relational perspective of the organization
• Complex networks in financial markets
• Artificial intelligence in management
• +۲ مورد دیگر

Dr hab. Dariusz Siudak is an Associate Professor at the Institute of Management , part of the Faculty of Organization and Management at Lodz University of Technology . He serves as Head of the Division of Economics and Finance and is a member of the Management and Quality Studies Discipline Council , IFE Study Program Council , and IDS Scholarship Committee . His work spans interdisciplinary research at the intersection of finance, network science, and artificial intelligence. Research Interests : Relational organizational theory, complex financial networks, AI-driven management systems, system dynamics in enterprise governance, and value migration analytics. Scientific Contributions focus on: Financial multiplex networks and cross-correlation dynamics AI applications in value migration modeling Network topology impacts on stock returns Corporate governance and board interlock analysis Markov chain modeling of network transitions Scientific Recognition : First place, NetMiner 20th Event (2022) Lecture of Marek Siudak award (2018) Dean’s award for scientific achievements (2018) Beta 2014 award nomination (2014)

• Cost Accounting
• Activity-Based Costing
• Management Accounting
• +۴ مورد دیگر

Burçin Tutcu , Associate Professor at Akdeniz University ’s Korkuteli Vocational School , has served since 2020 in the Department of Accounting and Tax Applications , after joining as Lecturer in 2017. Between 2021-2024 she also acted as Head of Department. Education Doctorate (2019) – Yildiz Technical University, Graduate School of Social Sciences, Accounting & Finance Master’s (2007) – Beykent University, Institute of Social Sciences, Business Administration Bachelor’s (2003) – Bursa Uludağ University, Faculty of Economics & Administrative Sciences, Econometrics Research Focus Her scholarship lies at the intersection of cost accounting , management accounting and digital transformation . Early work concentrated on activity-based costing (ABC) and time-driven ABC models for higher-education institutions, leading to a doctoral dissertation proposing a process-based ABC framework for universities. More recent investigations apply machine-learning techniques to financial performance forecasting in sectors such as IT, iron & steel, renewable energy and automotive. A parallel stream explores tax policy , sustainability reporting and green taxation , reflecting an expanding agenda towards environmental and regulatory issues. Publication Trends Across 40 WoS-indexed articles since 2017, three dominant patterns emerge: (1) empirical cost-system implementations in specific industries, (2) predictive analytics utilising AI/ML for financial ratios and energy variables, and (3) cross-country comparative studies on accounting standards and tax compliance. The temporal shift from pure cost accounting to data-driven and sustainability-oriented research illustrates an adaptive scholarly trajectory. Scientific Awards & Recognition Google Scholar h-index: 29 Scopus h-index: 15 Extensive peer-review service for national journals and academic appointment juries Advising, Grants & Professional Service While no specific PhD or Master’s students are listed, she has mentored numerous vocational-level projects and actively participates in thesis juries at other universities. External funding details are not provided in the text, yet her prolific publication record and conference engagements suggest sustained grant support or institutional research allocations. Laboratories & Teams She leads the Accounting and Tax Applications teaching team at Korkuteli Vocational School and coordinates curriculum development for cost-accounting courses across associate-degree programmes. Outside academia, she continues to practise as a certified freelance accountant (SMMM) under TÜRMOB, providing a practical feedback loop between scholarship and professional application.

Soumick Chatterjeeمشاهده پروفایل

پژوهشگر

• Deep Learning
• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• +۵ مورد دیگر

Soumick Chatterjee is a Postdoctoral Researcher at the Glastonbury Group within the Genomics Research Centre of Human Technopole , Milan, Italy. He completed his PhD in Computer Science (summa cum laude) at Otto von Guericke University Magdeburg , Germany, focusing on reducing artifacts in MRI using deep learning. Education : PhD (2022), MSc (2017), and BCA (2013) in Computer Science. Current Role : Postdoc in Genomics Research Centre, Milan. His research spans deep learning applications in medical imaging, including MRI reconstruction , motion correction , brain tumor classification , and vascular segmentation . He also emphasizes interpretability of AI models through tools like TorchEsegeta. Publications (23+ in 2023) include work on undersampled MRI reconstruction, uncertainty quantification, and vessel segmentation via maximum intensity projection loss. Notable scientific achievements include winning the CHAOS Challenge (2019) and runner-up in the MOOD Challenge (2021). As a supervisor , he guided multiple Master’s students in deep learning projects. He co-organized events like ISACT 2021 and SMILE-UHURA 2023. Open science advocate with code publicly available on GitHub.

• Scientific Visualization
• Data Visualization
• Computer Graphics
• +۴ مورد دیگر

Pere Pau Vázquez Alcocer is an Associate Professor in the Department of Computer Science at Universitat Politècnica de Catalunya (UPC), affiliated with the ViRVIG research group and the School of Informatics (FIB). With a PhD in Software from UPC (2003), he specializes in Scientific Visualization , Data Visualization , and Virtual Reality applications. His work bridges Computer Graphics with Medical Data Visualization and Molecular Visualization , emphasizing AI applications to visualization . His research spans two decades, focusing on Interactive volume rendering VR-based biomedical analysis Perceptual optimization in visualizations Urban mobility data modeling with recent publications in Computer Graphics Forum , IEEE CG&A , and arXiv on AI-driven visualization frameworks and molecular interaction techniques. His 15 most recent publications (2025-2023) demonstrate trends in AI integration for data visualization, immersive analytics for biomedical applications, and optimization of rendering techniques on mobile and VR platforms, with keywords spanning Computer Science , Neuroscience , and Urban Planning . Awarded the Best PhD thesis (2003) and Best Paper at international conferences, he has supervised 8 PhD students including Pedro Hermosilla (now Assistant Professor at TU Wien) and Jesús Díaz (now Associate Professor at Universitat de Vic). Teaching for over 20 years at UPC across five schools, he currently leads courses in Data Visualization , Scientific Visualization , and Virtual Reality .

• Academic Productivity
• Gender Disparities in Science
• Statistical Analysis
• +۳ مورد دیگر

Dr. Wojciech Roszka is a Lecturer at the Department of Statistics, Poznan University of Economics. He serves on the Committee for Periodic Evaluation of Academic Teachers and contributes to the Polish Statistical Association as a member of the Audit Committee of the Poznan Branch. Current academic affiliation: Poznan University of Economics Primary role: Lecturer in Statistics Committee memberships: Academic Evaluation, Polish Statistical Association Audit Research interests focus on: Academic productivity patterns and systemic inequalities Gender disparities in scientific collaboration and publication Spatial microsimulation and statistical data integration Longitudinal analysis of research careers His publication trends reveal sustained attention to productivity classification, statistical methodology, and socio-economic factors in science, with recent work expanding into environmental transcriptomics and longitudinal faculty evaluation frameworks. Other roles : Office location: Building C, Room 404 Contact: 61 854 36 85

Frieder Stolzenburgمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation
• Machine Learning
• +۷ مورد دیگر

Prof. Dr. Frieder Stolzenburg is a Professor for Knowledge-Based Systems at the Harz University of Applied Sciences since 2002. Current roles include Vice Rector for Research and Equal Opportunities (2022-2027) and Deputy Head of the Doctoral Center for Engineering and Information Technology . Major research areas span Artificial Intelligence, Machine Learning, Multi-Robot Systems, Cognitive Reasoning , and Music Cognition . PhD in Disjunctive Logic Programming (1998) Habilitation on Multiagent Systems and RoboCup (2006) Academic Leadership: Vice Dean (2018-2022), Program Coordinator Research focuses on hybrid AI systems combining formal logic with cognitive models, including periodicity detection in music perception and UAV-based agricultural monitoring . Recent work explores large language models for explainable AI and deep learning applications in plant disease classification . Selected scientific awards: Best Poster/Demo at KI-2012 3rd Place RoboCup German Open 2008 Koblenz University Prize 1993 Prolog Programming Competition 3rd Place 1994 Key memberships include CLAIRE , German Informatics Society (GI) , and German University Association (DHV) . Teaching emphasizes Agent Systems , Theoretical Computer Science , and Intelligent Knowledge Engineering .

Peter Fienerمشاهده پروفایل

استاد

• Soil Erosion
• Surface Runoff
• Water and Soil Resource Management
• +۷ مورد دیگر

Peter Fiener serves as Professor for Water and Soil Resource Research at the Department of Geography, Faculty of Applied Computer Sciences, University of Augsburg since 2013. He concurrently holds the position of Dean of Students in the Department of Geography (since 2016) and coordinates the Marie Skłodowska-Curie Innovative Training Network SOPLAS (since 2021). His academic journey includes prior appointments as Professor at the Indo-German Centre for Sustainability, Indian Institute of Technology Madras (2011-2012) and Senior Scientist at the University of Cologne (2004-2013). PhD from Technische Universität München (2003) Habilitation from University of Cologne (2010) Master's in Geography from Universität Augsburg and LMU München (1998) Professor Fiener's research program focuses on measuring and modeling surface runoff, soil erosion, and lateral matter fluxes in agricultural landscapes. He investigates the effects of spatio-temporal patterns and connectivity on water and matter movement, coupling these processes with biogeochemical cycles in terrestrial and aquatic ecosystems. A significant recent emphasis has been on macro and microplastics in arable soil systems, particularly their redistribution mechanisms. His geographical research areas of specialization include South India and Central Africa, where he has conducted extensive field studies on sustainable agricultural practices. Analysis of his 2024-2025 publications reveals a strong research trajectory toward microplastic detection methodologies, advanced soil erosion modeling using machine learning, and carbon dynamics in eroding landscapes. His work increasingly integrates remote sensing technologies with computational approaches to address large-scale soil conservation challenges, demonstrating particular innovation in plasticulture detection using satellite data and erosion nowcasting systems. Coordinator of Marie Skłodowska-Curie Innovative Training Network SOPLAS Professor Fiener leads the Water and Soil Resource Research Team comprising multiple doctoral researchers including Dr. Florian Wilken, Dr. Pedro Batista, and Dr. Lena Katharina Öttl, alongside numerous M.Sc. researchers. His M²ESH laboratory supports advanced measurement and modeling of soil hydrological processes. Current research directions include understanding tillage erosion's role in carbon dynamics, developing cost-effective microplastic detection protocols, and assessing long-term impacts of agricultural practices on landscape evolution across multiple temporal scales.

Aleš Smrdelمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Usability Testing
• User Interface Design
• +۳ مورد دیگر

Aleš Smrdel is an Assistant Professor at the Faculty of Computer and Information Science, University of Ljubljana. He is affiliated with the Laboratory for Biomedical Computer Systems and Imaging. Research Interests: Designing and implementing user interfaces Usability testing and human-computer interaction Biomedical signal analysis, particularly ECG and ischemia detection Selected Publications: Focus on algorithm development for cardiovascular diagnostics, including ST segment analysis and open-source tools for ECG evaluation. Laboratory: Active member of the Laboratory for Biomedical Computer Systems and Imaging.

Taotao Caiمشاهده پروفایل

مدرس

• Graph Data Processing
• Social Network Analytics
• Data Mining
• +۶ مورد دیگر

Dr. Taotao Cai serves as an Honorary Lecturer and Postdoctoral Research Fellow in the School of Computing at Macquarie University, bringing expertise in graph analytics and machine learning. Previously, they held an Associate Research Fellow position at Deakin University's School of Information Technology. Their academic foundation includes a Ph.D. from Deakin University and a Master's in Computer Science from Shenzhen University, China. Education: Ph.D. in Computer Science, Deakin University, Australia Master of Computer Science, Shenzhen University, P.R. China Research spans graph data processing, social network analytics, and data mining with significant contributions to causal graph neural networks, influence maximization, and privacy-preserving machine learning. Recent work demonstrates strong interdisciplinary applications in remote sensing, healthcare decision systems, and battery management, while maintaining core focus on dynamic network analysis. The research portfolio reveals increasing sophistication in causal reasoning within graph structures and practical implementations for real-world systems. Publication trends from 2023-2025 show concentrated activity in graph neural networks (40%), privacy/security (25%), and remote sensing applications (20%), with emerging work in causal classification and medical AI. This evolution reflects both theoretical advancement and practical problem-solving across diverse domains. No formal scientific awards are documented in available sources. While no formal student advising is recorded, collaborative patterns indicate active mentorship within research teams. Grant activity remains unspecified, but extensive cross-institutional collaborations (particularly with Deakin University and international partners) suggest participation in multiple funded projects. Current trajectories point toward causal graph neural networks for explainable AI and privacy-enhanced federated learning systems as primary research frontiers. Active participation in international research networks is evident through co-authorship spanning Australia, China, and global institutions, with particular strength in graph algorithm development and social network analysis communities.

• Phonology
• Phonetics
• Psycholinguistics
• +۳ مورد دیگر

Karthik Durvasula, Ph.D., is an Associate Professor in the Department of Linguistics, Languages, and Cultures at Michigan State University, where he conducts experimental research on phonological representations and features. His work bridges theoretical phonology with empirical methodologies to investigate speakers' knowledge of phonological generalizations across diverse languages. His academic background includes a Ph.D. in Linguistics from the University of Delaware. Durvasula's research focuses on experimental phonology, employing techniques from psycholinguistics and phonetics to probe questions about phonological feature representation. He investigates syllable structure, neutralization phenomena, and speech perception mechanisms, with cross-linguistic studies spanning Spanish, Russian, Mandarin, and English. His approach integrates acoustic analysis, articulatory coordination measurements, and perceptual experiments to address theoretical questions in phonological representation. Analysis of his 15 most recent publications (2025-2019) reveals consistent emphasis on experimental phonology, particularly syllable structure in consonant clusters, phonological vs. phonetic neutralization, and perceptual learning mechanisms. His work demonstrates how experimental data can resolve theoretical debates in generative phonology, with recurring methodologies including acoustic measurements, gestural timing analysis, and cross-linguistic perceptual studies. No scientific awards or honors are documented in the available information. While specific details about graduate student advising and research grants are not provided, his publication record indicates active mentorship in experimental linguistics. His research program likely involves securing external funding for laboratory-based phonetic studies and cross-linguistic fieldwork. Though no dedicated laboratory is mentioned, his experimental work suggests collaboration with phonetics and psycholinguistics research groups, potentially involving speech production and perception facilities at Michigan State University.

Tess Homanمشاهده پروفایل

استادیار

• Fundamental Fluid Dynamics
• Fluid-Particle Flow
• Bubbly Flow
• +۵ مورد دیگر

Tess Homan is an Assistant Professor at the Power & Flow group within the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e). Her research focuses on fundamental fluid dynamics , with an emphasis on data analysis and experimental techniques to study fluid-particle flows , bubbly flows , and biological systems . She is also involved in the Complex Multiphase Flows theme at TU/e. Research Trends: Articles span microfluidic mixing , metal particle combustion , and deep learning applications in fluid dynamics. Key subfields include artificial cilia dynamics , hyperspectral thermometry , and hydrogen-based metal regeneration . Scientific Contributions: Developed low-cost deep learning segmentation for bubble detection in industrial processes Advanced high-speed imaging techniques to analyze metal dust flames Investigated metachronal wave programming for fluid control in artificial cilia systems Education & Outreach: Teaches Experimentation for Mechanical Engineering and MATLAB Homologatie at TU/e.