Find Academic Supervisors

Carola Gomez RodriguezView profile

Associate Professor

• Ecology
• Biogeography
• Macroecology
• +4 more

Dr. Carola Gómez-Rodríguez is an Associate Professor of Ecology at the University of Santiago de Compostela (USC), affiliated with the Department of Functional Biology and the Cross-disciplinary Research Center in Environmental Technologies (CRETUS). She leads the BiBiCI research group (Biodiversity, Biogeography, and Integrative Conservation) and the GID-BioR teaching innovation group. Her work focuses on macroecological mechanisms shaping biodiversity patterns, integrating molecular, ecological, and phylogenetic data. She has held roles such as Associate Editor for the Journal of Animal Ecology (2017–2025) and contributed to science communication through outreach initiatives like madresBDV and educational resources in R programming for biodiversity analysis. Previous affiliations include the Natural History Museum (London), University of Vigo, and Doñana Biological Station. Education: PhD in Environmental Sciences (University of Salamanca, 2009), supervised by Dr. Carmen Díaz-Paniagua and Dr. Javier Bustamante. Postdoctoral research at University of Vigo (2009–2011) and Natural History Museum, London (2013–2015). Research Interests: Biodiversity dynamics, ecological processes, trait-based ecology, phylogenetic methods, and the impact of climate change. Key projects include analyzing dispersal limitations, genetic diversity congruence, and community turnover across spatial and temporal scales. Grants & Leadership: Coordinator of CRETUS-funded BiBiCI group (Xunta de Galicia), member of British Ecological Society Grants Committee (2018–2024). Active in gender equality initiatives at CRETUS and the School of Biological Sciences. Teaching: Ecology courses (USC), including Ecology II , Analysis of Biological Diversity , and master-level modules on biodiversity origins and patterns. Developed Biodiversidad con R for R programming in ecological analysis. Outreach: Hosted radio segments on biodiversity, created educational videos on biogeography and ecology, and co-founded madresBDV to highlight women in science. Resources include e-learning modules on biodiversity metrics and identification guides for invertebrate fauna.

• Artificial Intelligence
• Computer Vision
• Data Mining
• +7 more

Motiur Rahaman is a research-focused academic at Charles Sturt University, Australia, affiliated with the Data Mining Research Group (DaMRG) in the School of Computing, Mathematics and Engineering. His work bridges artificial intelligence with practical applications in agriculture and healthcare. Charles Sturt University Data Mining Research Group (DaMRG) Department of Computer Science His research interests center on artificial intelligence, computer vision, and data mining , with strong applications in remote sensing for agriculture (e.g., weed detection in crops) and medical imaging analysis (e.g., predicting ICU admission from X-ray features in COVID-19 patients). He also explores speech emotion classification using augmented audio data. His work often involves Gaussian mixture modeling, spatial correlation analysis, and deep learning techniques. The recent publications show a clear trend toward applied AI in solving real-world problems, particularly in sustainable agriculture and public health. His interdisciplinary collaborations reflect a strong emphasis on translating AI models into practical tools for farmers and clinicians. Scientific Awards: World-first computing and artificial intelligence COVID-19 severity scoring study (Grant, May 2020) Dr. Rahaman has been involved in significant grant-funded research, particularly in AI for healthcare. He collaborates extensively with researchers in viticulture, medicine, and agricultural technology. While no formal advisees are listed, his role in doctoral theses and datasets suggests mentoring and team leadership. He is a key contributor to the Smart Wine Project , which developed an open image library for grapevine nutrient disorders, demonstrating his involvement in data-driven agricultural innovation.

Aboozar TaherkhaniView profile

Senior Lecturer

• Artificial Intelligence
• Data Science
• Big Data
• +12 more

Dr. Aboozar Taherkhani is a Senior Lecturer in the School of Computer Science and Informatics at De Montfort University, UK, within the Faculty of Computing, Engineering and Media. His research integrates computer science and neuroscience, focusing on artificial intelligence, deep learning, and spiking neural networks. He is affiliated with the Institute of Artificial Intelligence (IAI) at DMU and has previously served as a full-time Research Fellow at Nottingham Trent University. His research interests include: Artificial Intelligence and Machine Learning Deep and Spiking Neural Networks Multimodal Data Analysis Image and Nonlinear Signal Processing Robotics, IoT, and Natural Language Processing Activity Recognition and Computational Neuroscience The recent publications highlight a strong trend in deep learning applications across domains such as healthcare (breast ultrasound segmentation, bone scaffolds), agriculture (hydroponics), robotics (3D reconstruction, gesture recognition), and privacy-preserving AI. His work emphasizes both theoretical advancements in neural models and practical implementations on edge devices and multimodal systems. Dr. Taherkhani has secured research funding through the Leverhulme Trust Research Project Grant RPG-2016-252 on multimodal data spaces. While no specific awards are listed, his extensive publication record in top journals reflects scholarly impact. He teaches courses such as Intelligent Mobile Robots, Natural Language Processing, Deep Neural Networks, and programming in C++, Python, and C#. He leads a research lab at DMU and supervises graduate students, though specific advisee names are not provided. His lab focuses on AI, robotics, and embedded intelligent systems.

Alexandra Branzan AlbuView profile

Professor

• Computer Vision
• Pattern Recognition
• Machine Learning
• +6 more

Dr. Alexandra Branzan Albu is a Professor in the Department of Electrical and Computer Engineering at the University of Victoria. She holds additional roles as Program Director for the Electrical Engineering program and Chair of the Academic Women Caucus. Her research focuses on computer vision applications in environmental monitoring, medical imaging, and document analysis. She earned her BSc, MSc, and PhD from the University of Bucharest and is a Professional Engineer (PEng). Education: BSc in Electrical Engineering MSc in Electrical Engineering PhD in Electrical Engineering Research Interests: Computer vision for underwater environmental monitoring (collaborations with ASL Environmental Sciences, Ocean Networks Canada) Medical imaging analysis and bioprosthetic heart valve durability assessment Document image retrieval and segmentation (e.g., mixed-media documents, business forms) Deep learning architectures for low-light image enhancement and anomaly detection Teaching Approach: Emphasizes problem-based learning and experiential education through hands-on projects. Courses include Computer Vision (ECE471/536) and Medical Image Processing (ECE435/BME403). Published pedagogical research explores societal impacts of technology and critical thinking development in STEM education. Labs & Collaborations: Active partnerships with industry (Cascadia Seaweed, VIVITRO Labs, SAP Canada) Leadership in underwater image analysis projects using Ocean Networks Canada's observatory data Development of Imageria outreach initiatives to increase women's participation in engineering

Jing ZhangView profile

Assistant Professor

• Translational Plant Phenomics
• Remote Sensing
• Robotics
• +7 more

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 KurzhalsView profile

Research Fellow

• Data Visualization
• Eye Tracking
• Visual Analytics
• +3 more

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 AlgancıView profile

Associate Professor

• Remote Sensing
• Geomatics Engineering
• Land Use and Land Cover Analysis
• +3 more

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

Dariusz SiudakView profile

Associate Professor

• Relational perspective of the organization
• Complex networks in financial markets
• Artificial intelligence in management
• +2 more

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
• +4 more

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 ChatterjeeView profile

Researcher

• Deep Learning
• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• +5 more

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
• +4 more

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
• +3 more

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 StolzenburgView profile

Professor

• Artificial Intelligence
• Knowledge Representation
• Machine Learning
• +7 more

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 FienerView profile

Professor

• Soil Erosion
• Surface Runoff
• Water and Soil Resource Management
• +7 more

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 SmrdelView profile

Assistant Professor

• Human-Computer Interaction
• Usability Testing
• User Interface Design
• +3 more

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.