Find Academic Supervisors

• Environmental Informatics
• Bioaerosol Monitoring
• Computer Vision Applications
• +3 more

Valiulis Gediminas serves as an Associate Professor at Vilnius University's Šiauliai Academy within the Department of Informatics Engineering. His academic career spans both engineering fundamentals and advanced environmental applications, with a pronounced shift toward bioaerosol monitoring and computer vision systems since 2018. His research interests focus on Environmental Informatics and Automatic Bioaerosol Detection , particularly developing computer vision models for pollen classification using light scattering techniques. This work bridges Environmental Science , Computer Vision , and Public Health through real-time pollen monitoring systems that serve allergy sufferers. His methodology combines fluorescent particle analysis , clustering algorithms , and sensor calibration to advance aerobiological research. Analysis of his publication trends reveals a strategic evolution: early work (2004-2012) centered on control systems engineering (granulation processes, microinverters), while recent output (2018-2024) demonstrates deep specialization in bioaerosol informatics . Key contributions include the Rapid-E particle counter validation, ozone-pollen interaction studies, and real-time pollen forecasting systems for clinical applications. His interdisciplinary approach connects atmospheric science with machine learning to solve environmental monitoring challenges. Automatic pollen recognition systems development Fluorescent bioaerosol characterization Real-time environmental data applications Computer vision for ecological monitoring While no formal advising relationships or scientific awards are documented in the source material, his collaborative research consistently involves multi-institutional teams across Lithuania and Europe. Current projects focus on enhancing bioaerosol sensor accuracy and developing clinical decision-support tools for allergy management through real-time environmental data integration.

Hani Ragab HassenView profile

Associate Professor

• Cybersecurity
• Deep Learning Applications
• Natural Language Processing (NLP) in Cybersecurity
• +7 more

Hani Ragab Hassen is an Associate Professor leading the Cybersecurity with AI Research Group at the School of Mathematical & Computer Sciences, Heriot-Watt University. He specializes in cybersecurity, particularly in applying machine learning and NLP to address challenges such as malware analysis, intrusion detection, and access control systems. His roles include Associate Director of PGR Studies, Academic Integrity Officer, and former leadership in Learning & Teaching and Research programs. Research interests focus on cybersecurity fundamentals, including deep learning for malware detection, NLP-driven vulnerability assessment, and P2P systems. He has supervised numerous PhD students, currently advising three candidates on airport cybersecurity, NLP-based vulnerability detection, and network intrusion systems. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure security. Publications span malware detection frameworks (e.g., ActDroid, Droiddissector), network security tools (NTFA), and machine learning optimization (D2TS). He has developed datasets like SI22 for DDoS analysis and contributed to open-source tools. His research emphasizes practical applications of AI in securing networks and cloud environments. Notable contributions include advancing Android malware detection via control flow graphs and text analysis, and pioneering cloud security protocols like Stick for social platforms. His interdisciplinary work bridges cybersecurity with machine learning and data science, addressing real-world threats through innovative solutions.

Jeremy NealView profile

Associate Professor

• Maternal and Child Health
• Obstetric Research
• Labor Progression Analysis
• +3 more

Dr. Jeremy Neal is an Associate Professor and Co-Director of the Postdoctoral Program at the Vanderbilt University School of Nursing. His research focuses on improving maternal and neonatal outcomes through translational studies on labor progression, inflammatory biomarkers, and clinical decision-making tools like the physiologic partograph. He has led multiple NIH-funded studies examining disparities in labor care among Black and white women, midwifery integration in healthcare systems, and cesarean birth reduction strategies. Dr. Neal holds a BSN from Bowling Green State University (1995), an MS in Nurse-Midwifery from The Ohio State University (2005), and a PhD in Nursing Science (2008). His teaching includes nurse-midwifery specialty courses and doctoral-level instruction. His research interests emphasize optimizing labor care through evidence-based practices, reducing preventable cesarean births, and leveraging biomarkers to predict labor onset. Recent innovations include a digital physiologic partograph to enhance clinician-patient shared decision-making. Key grants include NIH/NIMHD funding (2021-2023) for studying racial disparities in labor care and Vanderbilt Provost Awards advancing midwifery's role in reducing cesareans. Publications span journals like Birth , Journal of Midwifery & Women's Health , and American Journal of Obstetrics & Gynecology . Awards: 2021 Fellowship in ACNM, 2020 Excellence in Teaching Award, 2018 Best Research Presentation Reviewer for Obstetrics & Gynecology , American Journal of Obstetrics & Gynecology , and midwifery-focused journals His work bridges clinical practice and research, advocating for cost-effective, equitable care while advancing midwifery's role in modern obstetrics.

• Nanopore DNA Sequencing
• Computational Materials Science
• 2D Materials Engineering
• +5 more

Maria Fyta serves as a Professor of Biotechnology at RWTH Aachen University's Faculty of Biology, leading research in the Department of Biotechnology from her lab in the Biology Building (Worringerweg 3, Aachen). Her work bridges computational physics, nanotechnology, and molecular biology to develop next-generation biosensing platforms. Her research focuses on nanopore-based DNA/protein sequencing , utilizing 2D materials (graphene, MoS 2 , h-BN) and nanodiamond functionalization for single-molecule detection. Key projects include ionic liquid catalysis systems , computational alloy design , and molecular dynamics simulations of biomolecular translocation. Recent work emphasizes machine learning integration for signal analysis and materials discovery. Analysis of her 15 most recent publications reveals dominant trends in Nanopore engineering for biomolecular sensing Computational materials design of 2D systems and alloys Machine learning applications in nanofluidics While no specific scientific awards are documented in the provided materials, her extensive publication record demonstrates significant contributions to nanotechnology and biophysics. Professor Fyta's group develops advanced simulation frameworks for biomolecular translocation and collaborates on experimental validation of nanoscale devices. Current efforts focus on enhancing read-out capabilities in functionalized nanopores and designing bio-mimetic sequencing platforms.

Allah BuxView profile

Research Fellow

• Computer Vision
• Medical Image Analysis
• Deep Learning
• +6 more

Allah Bux is a Research Fellow at the Department of Linguistic, Literary and Aesthetic Studies, University of Bergen. His work focuses on advanced computer vision techniques, medical image analysis, and deep learning applications. He holds expertise in 3D reconstruction, anomaly detection, and surveillance systems. His research interests include developing novel neural network architectures for tasks such as skin cancer diagnosis, head pose estimation, and human action recognition. He also explores spatiotemporal analysis and attention mechanisms in CNN models. Recent trends in his publications emphasize integration of vision transformers, dual attention networks, and transfer learning for solving real-world problems in healthcare, security, and education. No scientific awards or grants are explicitly listed in the provided text. He has no documented advisees. His research involves collaborations in medical imaging, autonomous surveillance systems, and educational data analysis, with a focus on practical applications of AI.

Tihomir RangelovView profile

Researcher

• Language Documentation
• Oceanic Languages
• Phonetics
• +4 more

Tihomir Rangelov is a postdoctoral researcher at the Department of Linguistic and Cultural Evolution at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. He is a member of the Comparative Oceanic Linguistics (CoOL) group . His work focuses on language documentation, description, and revitalization of endangered Oceanic languages, particularly Ahamb spoken in Vanuatu. His research integrates historical linguistics, phonetics, and typology to explore sound systems and grammatical structures. Education: PhD in Linguistics (2020), University of Waikato, New Zealand (Thesis: A Grammar of Ahamb) MA in Computational Linguistics (2013), University of Iceland/Reykjavík BA in Icelandic Studies (2008), University of Iceland MA in Scandinavian Studies (2007), Sofia University Research Interests Rangelov’s research emphasizes: Documenting endangered languages of Vanuatu, especially Ahamb Phonetic analysis of rare sounds like prenasalized bilabial trills Historical linguistics and Oceanic language phylogeny Community-driven language revitalization strategies Publications Trends His articles explore: Unusual phonetic phenomena (e.g., bilabial trills) Grammatical structures in Austronesian languages Technological tools for language maintenance Comparative methods in Oceanic linguistics Advising & Grants Rangelov has led fieldwork projects in Vanuatu and participated in international conferences. His work is supported by the Max Planck Society and collaborative grants with institutions like the University of Waikato. Lab/Team Active member of the CoOL group , focusing on comparative analyses of Oceanic languages and their typological features.

Ian R H TelfordView profile

Researcher

• Plant Systematics
• Taxonomy
• Biogeography
• +7 more

Dr. Ian R. H. Telford is a researcher at the University of New England, affiliated with the School of Environmental and Rural Science. He is actively engaged in herbarium curation, teaching, and botanical research with a strong focus on Australian flora. Research Interests: His primary research areas include plant systematics, taxonomy, and biogeography, particularly within the families Cucurbitaceae, Phyllanthaceae, Rutaceae, Lamiaceae, and Asteraceae. He is dedicated to understanding species limits and evolutionary relationships in Australian endemic plants, especially in northeastern New South Wales, where biodiversity remains under-documented. He also prepares scientific illustrations for his studies. Publication Trends: His recent publications (2005–2012) reflect a consistent focus on taxonomic revisions, species delimitation, and molecular phylogenetics. Collaborative international research is a hallmark of his work, particularly on Cucurbitaceae and Phyllanthaceae. Many studies combine morphological and molecular data to resolve complex species boundaries and biogeographic patterns. Scientific Awards: Carrick Teaching Excellence Award (2006) Teaching and Community Engagement: Dr. Telford trains undergraduate and postgraduate students in field collection and herbarium techniques. He leads a team of volunteers in specimen preparation and data entry, contributes to school outreach programs, and provides plant identification services to naturalist groups. His educational impact is recognized through a national teaching award. Labs and Teams: He leads a herbarium curation team at UNE, overseeing best practices in collection management and data integrity. This team includes trained volunteers and student assistants, contributing to both research and public engagement during open days and exhibitions.

• Mammalogy
• Australian Marsupials
• Taxonomy
• +4 more

Professor Andrew Baker is a leading mammalogist at Queensland University of Technology specializing in Australian marsupials, particularly carnivorous species like Antechinus and dunnarts. With over 130 publications spanning more than two decades, he has made significant contributions to taxonomy, conservation biology, and wildlife monitoring techniques. His research has led to the discovery and description of multiple new mammal species and has significantly advanced understanding of Australian marsupial diversity. Baker's research interests center on mammalian taxonomy, conservation genetics, and ecological monitoring of threatened Australian species. His work frequently employs innovative methodologies including owl pellet analysis, eDNA sampling, and geometric morphometrics to study elusive small mammals. He has pioneered non-invasive techniques for monitoring threatened species like the Julia Creek dunnart and has documented dramatic life history strategies in semelparous marsupials. His research bridges fundamental taxonomy with urgent conservation needs, particularly in the context of climate change and habitat loss. Professor Baker's recent publications reveal a consistent focus on species discovery, taxonomic revision, and conservation assessment of Australian marsupials. His work increasingly integrates molecular techniques with traditional morphological approaches, reflecting the field's evolution toward integrative taxonomy. A significant portion of his recent research addresses practical conservation challenges, developing field methodologies for monitoring threatened species and assessing their conservation status through IUCN Red List evaluations. Ronald Strahan Memorial Award (2024) Contributor to IUCN Red List assessments for multiple Australian marsupial species Co-editor of Strahan's Mammals of Australia (4th Edition, 2023) Leader of the Australasian Mammal Taxonomy Consortium Professor Baker has mentored numerous early-career researchers who have become co-authors on his publications, particularly in field studies of threatened marsupials. His work has been supported by multiple conservation-focused grants, though specific funding amounts aren't detailed in the publication record. His research has directly informed conservation management practices, including targeted survey guidelines for threatened species like the Julia Creek dunnart. Baker leads research teams focused on Australian mammal taxonomy and conservation, frequently collaborating with Queensland government agencies, the Australian Museum, and international researchers. His work with the Australasian Mammal Taxonomy Consortium represents a major collaborative effort to document and classify Australia's mammalian biodiversity before potentially losing species to extinction.

Edy Tri BaskoroView profile

Professor

• Combinatorics
• Graph Theory
• Discrete Mathematics
• +2 more

Prof. Edy Tri Baskoro, M.Sc., Ph.D., is a faculty member at the Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology. His academic career spans combinatorics, graph theory, and discrete mathematics, with extensive research on Ramsey graphs, metric dimensions, and graph labelings. Education: Bachelor's from ITB (1987), Master's from University of New England (1992), Ph.D. from University of Newcastle (1996) His research focuses on combinatorial structures, including Ramsey minimal graphs, partition dimensions, irregularity strength, and quadratic embedding constants. Key subfields include tree graphs, path-cycle Ramsey problems, and algorithmic graph theory. Recent publications address edge-locating colorings, unicyclic Ramsey graphs, and applications of graph theory in educational programs. He has contributed to teacher training initiatives in Lombok, Cirebon, and Makassar, as well as textbook development for machine learning. His work involves collaborations in graph theory research and projects like PKR Graph Theory for Nation Building. While no specific awards are documented in the provided text, his contributions to combinatorial research and mathematics education in Indonesia are significant.

Albin ZeheView profile

Researcher

• Natural Language Processing
• Text Mining
• Sentiment Analysis
• +3 more

Albin Zehe is a Researcher at the Chair of Data Science (Informatik X) within the Institute of Computer Science at the University of Würzburg's Faculty of Mathematics and Computer Science. He holds an M.Sc. degree and has maintained an active research and teaching profile since at least 2016, with his office located in Room 03.021 of the CAIDAS Building on the Hubland Nord campus. Zehe's research primarily focuses on applying Natural Language Processing techniques to literary analysis, with a special emphasis on sentiment analysis in German literature. His work bridges computer science and humanities, developing computational methods to analyze novels and other literary works. He has expressed particular interest in Tolkien's writings, reflected in his 2022 publication analyzing Tolkien's Legendarium using NLP and Graph Neural Networks. His publication record shows a progression from literary analysis (2016-2018) to broader NLP applications including social media analysis (Twitch.tv in 2020) and time series forecasting (2020). Recent work has expanded to graph-based analysis of literary universes and scene segmentation in fiction. Zehe has served as PC member for major conferences including ACL (2021 & 2023), EMNLP (2021 & 2022), ECMLPKDD (2020 & 2021), ECAI (2020), and AAAI (2020-2022), demonstrating his active role in the academic community. He has taught Machine Learning for Natural Language Processing every summer semester from 2018 to 2023, along with the Natural Language Processing Practicum , and previously taught courses in algorithms, information retrieval, and Web 2.0 technologies. He has co-organized academic challenges including the ChAT challenge at ECML-PKDD 2020 and the Shared Task on Scene Segmentation at KONVENS 2021.

• Spatio-temporal databases
• Document analysis
• Handwriting recognition
• +3 more

Roman Ptak is a researcher at the Department of Computer Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His work focuses on document analysis, handwriting recognition, and geohistorical data modeling. Research interests include: Document Analysis: Specializing in text line segmentation and handwriting recognition techniques Geohistorical Data: Addressing heterogeneity in historical information systems Image Processing: Developing algorithms for document examination and artifact analysis Roman's recent research trends show: 2024: Tensor voting applications in handwriting analysis 2023: Advanced segmentation techniques for handwritten documents 2021: Heterogenic spectral database development 2020: Hybrid approaches combining histograms and projection methods 2019: Ink spectral analysis and polymorphic microscopy 2017: Historical document authentication and GIS-based cultural geography studies Contact: roman.ptak@pwr.edu.pl

• Explosion Protection
• Biogas Technology
• Combustion Engineering
• +5 more

Dr. Zoltán Siménfalvi serves as Dean of the Faculty of Mechanical Engineering and Informatics at the University of Miskolc, Hungary, holding the academic rank of Professor. His leadership encompasses oversight of academic programs, research initiatives, and administrative functions within the faculty, positioning him at the forefront of mechanical engineering education and innovation in Central Europe. His research spans explosion protection, biogas technology, combustion engineering, and sustainable energy systems. Key focus areas include computational fluid dynamics (CFD) simulations for hazardous area classification, flash point determination of flammable mixtures, hydrogen/methane dispersion modeling, and optimization of anaerobic digestion processes. His work bridges theoretical analysis with industrial applications in energy safety and renewable resource utilization. Analysis of his 15 most recent publications (2022-2024) reveals dominant themes in explosion hazard analysis (60% of works), particularly 2D/3D hazardous area modeling, gas detector performance in ammonia environments, and FLACS-CFD simulations for hydrogen-methane mixtures. Biogas technology constitutes 25% of output, emphasizing mixing efficiency in anaerobic digesters and process optimization. Remaining research addresses sustainable engineering through carbon capture strategies for V4 countries, coal gasification efficiency, and propane leakage dynamics. No scientific awards were documented in the available materials. Information regarding student advising, research grants, or laboratory supervision was not provided in source materials. His administrative role as Dean suggests strategic oversight of research funding and academic programs, though specific grant details remain unreported. No dedicated research laboratories or specialized teams were explicitly referenced, though his publications indicate collaboration with computational modeling groups and industrial safety partners for experimental validation of CFD simulations.

• Forensic Science
• Drug Intelligence
• Organized Crime Analysis
• +6 more

Dr. Marie Morelato is a Senior Lecturer at the University of Technology Sydney (UTS), affiliated with the School of Mathematical and Physical Sciences and the Centre for Forensic Science. She holds a PhD in drug intelligence from UTS (2015) and a prestigious Chancellor’s Postdoctoral Research Fellowship (2015–2019). Her research focuses on forensic intelligence, illicit drug data analysis, and organized crime systems, emphasizing data triangulation from sources like cryptomarkets, seizures, and wastewater. She teaches courses such as Forensic Intelligence and serves as Course Director for the Bachelor of Forensic Science program. Marie has received awards including the UTS Teaching and Learning Award (2022) and recognition for contributions to student learning (2024). She leads grants on drug surveillance, including the Residue and Post Overdose Substance Testing (RePOST) project and studies on opioid-related harms. Her editorial roles include Associate Editor for Forensic Science International and contributions to the International Association of Forensic Sciences. Her work bridges forensic science with intelligence-led policing, advancing methodologies like machine learning for crime scene analysis and portable NIR drug detection. She collaborates with agencies like the Australian Federal Police and emphasizes interdisciplinary approaches to tackle complex criminal systems.

• Business Process Management
• Process Mining
• Applied Data Analytics
• +4 more

Prof. Jochen De Weerdt is an Associate Professor at the Department of Decision Sciences and Information Management, KU Leuven, affiliated with the Faculty of Economics and Business. He is part of the Information Systems Engineering Research Group (LIRIS) and a member of Leuven.AI. His research focuses on Business Process Management, Process Mining, IoT-integrated analytics, and data-driven decision-making. He teaches courses such as Business Information Systems and chairs the Postgraduate Studies in Big Data and Analytics. His professional activities include organizing international workshops (e.g., BPI'14 and BPI'13) and serving as a reviewer for top journals like Information Systems and Decision Support Systems . Academically, he holds a PhD (2012) and MSc/BSc degrees (2009/2007) in Business Economics from KU Leuven. His work bridges theory and practice, addressing challenges in process optimization, fraud detection, and cross-domain applications of machine learning. He has pioneered methods for IoT-enhanced predictive process monitoring and graph-based analytics in dynamic systems. Research interests span predictive process analytics, adversarial robustness in models, and geospatial data integration. Teaching emphasizes practical skills in business informatics and data science, with a focus on industry-relevant outcomes. He actively collaborates on projects funded by institutions like the Australian Research Council (ARC).

Julia BullardView profile

Associate Professor

• Information and Knowledge Organization
• Information Ethics
• Computer-Supported Cooperative Work
• +6 more

Julia Bullard serves as Associate Professor at the University of British Columbia's School of Information within the Faculty of Arts. Her work centers on the design and implementation of knowledge organization systems that align with community values and ethical principles, with research spanning classification theory, information ethics, and computer-supported cooperative work. Education: MA in Cultural Studies and Critical Theory, McMaster University MLIS, UBC School of Information PhD in Information Science, University of Texas at Austin Research Focus: Dr. Bullard investigates how knowledge organization systems reflect community values through frameworks like warrant theory, examining both theoretical foundations and practical implementations. Her work bridges information ethics with social computing, emphasizing EDI principles in classification design and community-driven metadata systems. She explores how volunteer contributions shape fanfiction repositories and how crowdsourcing can enhance knowledge organization while maintaining quality. Publication Analysis: Her 2015-2017 publications reveal consistent focus on classification design challenges across contexts—from fanfiction repositories to scientific software citation. Key trends include community-centered system design, ethical implications of taxonomies, and integration of theoretical frameworks with practical implementation. Her work demonstrates strong interdisciplinary connections between information science, human-computer interaction, and social computing. Scientific Recognition: Recipient of ISKO 2022 Best Paper Award Research Support: Dr. Bullard secured SSHRC Insight Development Grant funding for her research on information systems and community values, demonstrating the significance of her work in advancing equitable knowledge organization practices. While specific advisees aren't listed, her role involves mentoring graduate students in knowledge organization and information ethics. Collaborative Work: Her research involves interdisciplinary teams across institutions, evidenced by co-authored publications in top venues including Journal of Documentation, JASIST, and ACM conferences. Current work addresses urgent issues like revising classification systems to better represent Indigenous peoples, reflecting her commitment to socially responsible information design.