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Ludmila KunchevaView profile

Professor

• Pattern Recognition
• Machine Learning
• Classifier Ensembles
• +4 more

Ludmila Kuncheva is a Professor in Computer Science at Bangor University's School of Computer Science and Electronic Engineering. Her core research focuses on pattern recognition and machine learning, with specialized expertise in classifier ensembles, feature selection methodologies, and video analysis techniques. She leads significant research projects including the Leverhulme Trust-sponsored 'Prototype Selection from Streaming, Drifting and Partly Labelled Data'. Research Focus: Her primary research domains include machine learning frameworks for constrained clustering, video summarization methods, and animal re-identification systems. Recent work explores semi-supervised classification with applications in wildlife monitoring and sports analytics, demonstrating cross-disciplinary impact. Publication Trends: Her recent publications show strong emphasis on computer vision applications for ecological studies, particularly animal tracking through advanced video analysis. There's consistent focus on improving classification algorithms for imbalanced data and developing theoretical frameworks for prototype-based learning systems. Research Projects: Prototype Selection from Streaming, Drifting and Partly Labelled Data (Leverhulme Trust) Feature selection for COPD diagnostic systems KTP collaboration with Semantise Ltd. on industrial applications Teaching: Mathematics for Computing Algorithm Design with MATLAB Pattern Recognition and Neural Networks Final Year Project supervision

Tom JohnstenView profile

Professor

• Data Mining Algorithms
• Computational Biology
• Machine Learning Applications

Dr. Tom Johnsten is a Professor in the Computer Science Department at the University of South Alabama, part of the School of Computing. He holds a Ph.D. in Computer Science from the University of Louisiana at Lafayette (1998), an M.S. in Computer Science from Arizona State University (1992), and a B.S. in Mathematics from Oklahoma State University (1987). His research focuses on developing data mining algorithms, computational biology, and applying machine learning technologies to interdisciplinary challenges. His work bridges computational methods with biological systems, cybersecurity, and environmental data analysis. Notable contributions include advancements in DNA repair mechanisms, anomaly detection in data streams, and prescriptive maintenance frameworks. He has taught courses such as Digital Logic and Computer Architecture, Operating Systems, Programming Language Theory, and Data Mining. His office is located in Shelby Hall, Room 1119, with regular office hours on Tuesdays and Thursdays. Dr. Johnsten’s publications reflect a strong emphasis on cybersecurity, bioinformatics, and data-driven solutions. He has explored topics like mitochondrial DNA repair, robotic system security, and synthetic signal peptide design. While no scientific awards are explicitly listed, his extensive publication record highlights sustained academic contribution. Teaching and advising roles include mentoring students through courses like Research Methodologies and Database Design. His work integrates theoretical computer science with practical applications in diverse fields.

• Carbon Accounting
• Sustainability Reporting
• ESG/CSR
• +5 more

Dr. June Cao is a Senior Lecturer in the School of Accounting, Economics and Finance at Curtin University, within the Faculty of Business and Law. She holds a PhD and is a CPA Australia member, Chartered Accountant (CA ANZ), and Fellow of the Higher Education Academy (FHEA). Her research focuses on carbon accounting, sustainability reporting, ESG/CSR, and green innovation, employing advanced methodologies to address global sustainability challenges. She has been recognized with prestigious awards such as the FBL Research Output of the Year Award (2024) and multiple teaching excellence awards for her SDGs-embedded pedagogy. Her editorial roles include serving on the Editorial Advisory Board of the Journal of Accounting Literature , Lead Guest Editor of the Pacific Accounting Review , and Associate Editor of the Accounting Research Journal . Her research interests span new institutional accounting, carbon emissions regulation, integrated reporting, and big data analytics. Notable contributions include studies on low-carbon city initiatives, green supply chain management, and the impact of environmental policies on corporate behavior. She actively contributes to professional bodies like the AFAANZ Technical Committee and CPA Australia, and her teaching innovations have achieved 100% pass rates for students in CPA exams. Editorial Roles: Journal of Accounting Literature, Pacific Accounting Review, Accounting Research Journal Memberships: AFAANZ, CPA Australia, Chartered Accountants Australia and New Zealand, Higher Education Academy Key Research Themes: Carbon Accounting, Sustainability Reporting, Green Innovation, ESG, Big Data in Accounting Dr. Cao’s work bridges academia and industry, emphasizing transformative pedagogy and global sustainability. She has secured significant recognition for her research and teaching, reflecting her dual commitment to scholarly excellence and educational innovation.

• Statistical Learning
• High-Dimensional Data Analysis
• Network Statistics
• +7 more

Charles Bouveyron is a Full Professor of Statistics at Université Côte d'Azur , Nice, France, and holds a Chair in Artificial Intelligence. He serves as Director of the Institut 3IA Côte d’Azur and leads the Inria research team MAASAI on Statistical Learning and Artificial Intelligence. He is an associate editor for The Annals of Applied Statistics and founded the Statlearn workshops . Research Interests: Statistical learning in high dimensions Learning on networks and functional data Deep latent variable models Adaptive learning with uncertain labels Applications in Medicine, Image Analysis, Astrophysics, and Humanities Notable Contributions: Developed multiple R packages including HDclassif , FisherEM , and FunLBM . Created the Linkage.fr platform for network analysis with textual edges. PhD Students: Current: Seydina Niang (Deep Generative Models), Kilian Burgi (Marine Diversity Monitoring), Baptiste Pouthier (Multimodal Learning) Former: Giulia Marchello (Dynamic Networks), Rémi Boutin (Network Analysis), Dingge Liang (Recommender Systems), Nicolas Jouvin (Latent Variable Models), Alexandre Saint-Dizier (Image Aggregation), Warith Harchaoui (Optimal Transport), Pierre-Alexandre Mattei (Sparse Clustering), Rawya Zreik (Temporal Networks), Anastasios Bellas (Anomaly Detection), Camille Brunet (Sparse Clustering) Contact: Email: charles.bouveyron@univ-cotedazur.fr / charles.bouveyron@inria.fr Postal: Equipe Maasai, Inria Sophia Antipolis, 2004 route des Lucioles, 06902 France

• Landscape Architecture
• Landscape Urbanism
• Circular Economy
• +5 more

Cecilia Furlan is an Assistant Professor at the Institute of Landscape Architecture , part of the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). She holds a joint PhD in Engineering and Urbanism from KU Leuven and IUAV Venice. Landscape Urbanism Circular Economy Urban Metabolism Spatial Research Resource Scarcity Her research focuses on systemic design approaches for circular economy transitions in urban and regional contexts, particularly through projects like ATLANTES and REPAiR . She explores material flow mapping, post-industrial landscape regeneration, and urban wasteland transformation. Recent publications examine geodesign methods for circular construction hubs, ecosystem services in urban cemeteries, and spatial parameters for sustainable development. She contributes to international discourse through presentations at institutions in Austria, Belgium, Italy, Netherlands, and South Africa. 2020: Knowledge Frontiers Symposium grant 2019: EUROPAN 15 Runner-Up 2018: Premio Giovanni Ferraro PhD award 2014: Lisbon Open Room Competition honorable mention As a project leader for initiatives like Reindustrialisation Following the Brownfield Principle , she combines academic research with practical applications. She participates in peer-review activities for journals like Sustainability and Landscape Research , and organizes educational workshops on circular design.

• Network Science
• Information-Centric Networking (ICN)
• Urban and Transportation Networks
• +7 more

Wei Koong Chai is a Senior Lecturer in the Department of Computing and Informatics at Bournemouth University and Deputy Head of Department at University College London (UCL), also within the Department of Computing and Informatics. He has held these academic positions since 2016 and 2024 respectively, demonstrating sustained contributions to higher education and research leadership. His research focuses on network science, information-centric networking (ICN), urban and transportation networks, smart grids, and resilience in complex systems. Key areas include traffic congestion modeling using SIR epidemic models, robustness assessment of urban road networks, deep learning for traffic prediction, and content delivery resilience in distributed caching systems. His work bridges theoretical network models with practical applications in smart cities and critical infrastructure. The recent publications (2021–2025) highlight a strong trajectory in applying network analytics, machine learning, and distributed systems to urban mobility and cyber-physical systems. Themes include spatio-temporal prediction, multi-scale topological analysis, and adaptive communication in flying ad hoc networks. His collaborations span institutions and disciplines, indicating interdisciplinary engagement. Scientific Awards: No scientific awards listed in the provided text. Wei Koong Chai has advised students and researchers in computing and network systems, though specific names are not listed. He has contributed to peer review, notably for PLOS Complex Systems , and is involved in impactful research projects related to smart grids, urban analytics, and information resilience. His work has been supported through institutional affiliations and collaborative grants, though specific funding sources are not detailed. He is associated with research labs and teams focused on network science, smart cities, and information-centric systems at both Bournemouth University and UCL. His future work likely extends into AI-driven urban infrastructure optimization, resilient IoT networks, and next-generation content delivery architectures.

Marta Otero CaberoView profile

Professor

• Environmental Chemistry
• Water Treatment Technologies
• Waste Valorization
• +3 more

Marta Otero Cabero is a Full Professor at the University of León, specializing in Environmental Chemistry and Water Treatment Technologies within the Faculty of Biological and Environmental Sciences. Her research focuses on wastewater treatment, waste valorization, and sustainable materials development through adsorption processes and photocatalytic methods. University: University of León School: Faculty of Biological and Environmental Sciences Department: Applied Chemistry and Physics Academic Rank: Professor Education: PhD in Physical Chemistry (2000), University of León, thesis: "Utilization of sewage sludge: use of thermogravimetry for monitoring combustion and stabilization processes: manufacturing of new materials" Research Interests: Marta's work addresses critical environmental challenges through innovative approaches. She develops advanced adsorbent materials from industrial and agricultural wastes (brewery residues, paper sludge, olive oil cake) for removing pharmaceuticals, antibiotics, and toxic metals from water. Her research integrates circular economy principles by transforming waste streams into functional nanocomposites (magnetic activated carbons, biochars, polymer hybrids) while evaluating ecological impacts using bioassays. Publication Trends: Recent articles highlight her expertise in: (1) magnetic adsorbent synthesis from waste biomass, (2) solar-driven photocatalytic systems for contaminant degradation, (3) factorial design optimization of adsorption parameters, (4) ecotoxicity assessments with zebrafish embryo tests, and (5) upcycling lignocellulosic wastes into hierarchical porous materials. Key pollutants addressed include antibiotics, pharmaceuticals, heavy metals, and synthetic dyes. Additional Contributions: Marta has pioneered continuous-flow treatment systems, explored bioflocculant applications, and developed analytical methods for contaminant quantification. Her interdisciplinary work bridges chemical engineering, environmental toxicology, and sustainable material design.

• Environmental Geology
• Geotechnology
• Geoenvironmental Studies
• +4 more

Professor Eleni Kokkinou holds a position at the Hellenic Mediterranean University (HMU) as a Professor of Environmental Geology and Geotechnology, with an affiliation to the Institute of Computer Science at FORTH. She earned her Geology degree from Aristotle University of Thessaloniki, followed by a postgraduate diploma and PhD in Applied Geophysics from the Technical University of Crete. Her research focuses on environmental geology, geotechnical studies, geodata modeling, and coastal vulnerability. She has pioneered work in remote sensing for agricultural management, oil spill modeling in the Eastern Mediterranean, and precision agriculture using UAV technology. She has supervised over 73 diploma dissertations, 5 ongoing theses, and examined multiple international M.Sc. theses in Egypt and Cyprus. Teaching includes courses on GIS, geotectonics, and geoscience software at HMU and TEI Crete. She actively contributes to committees like the Research Management Board of HMU and is a licensed UAV pilot with expertise in geophysical prospection. Her work integrates geomatics, environmental monitoring, and civil protection strategies for coastal and marine systems. Key collaborations include Cairo University and the Technical University of Crete. She has developed decision-support systems for irrigation optimization and participated in major projects like the Nereids oil spill risk assessment initiative.

Wajih Ul HassanView profile

Assistant Professor

• System Security
• Network Security
• Machine Learning
• +5 more

Wajih Ul Hassan is an Assistant Professor of Computer Science at the University of Virginia (UVA), leading the DART Lab. His research focuses on system security, emphasizing practical solutions for safeguarding networked systems using data-driven approaches and scalable design. He was awarded the NSF CAREER Award in 2024. His service roles include program committee (PC) membership at IEEE S&P, NDSS, ACM CCS, and NSF panel participation since 2018. Research Interests : Hassan’s work centers on intrusion detection, provenance analytics, threat detection, and forensic analysis. He explores how provenance graphs and machine learning can enhance cybersecurity resilience against advanced persistent threats (APTs), AR/VR attacks, and configuration-based exploits. Teaching : He teaches CS 6501: Machine Learning in Systems Security , CS 4630: Defense Against the Dark Arts , and DS 6559: Machine Learning in Systems and Network Security . Courses emphasize threat detection, vulnerability management, and forensic investigation. Awards : NSF CAREER Award (2024) Labs & Teams : Directs the DART Lab, focused on applied security research and scalable defense mechanisms.

• Distributed Systems
• Peer-to-Peer Networks
• Cloud Computing
• +4 more

Peter G. Kropf is a Professor in the Department of Computer Science at the University of Neuchâtel, Switzerland, with a distinguished research career spanning over three decades. His academic journey reflects significant contributions to distributed systems, peer-to-peer networks, and cloud computing, with recent focus on IoT analytics and scientific computing applications. Dr. Kropf's research interests center on Distributed Systems , Peer-to-Peer Networks , Cloud Computing , Wireless Mesh Networks , and Scientific Workflows . His work demonstrates a clear evolution from foundational distributed systems research to practical applications in environmental monitoring, IoT analytics, and large-scale scientific computing. He has maintained consistent research productivity throughout his career, with publications appearing regularly from 1990 through 2024. Analysis of his recent publications reveals a strong trend toward real-time data processing for environmental applications, IoT analytics , and cloud-based scientific workflows . His work often bridges theoretical distributed systems concepts with practical implementations, particularly in environmental monitoring and resource management contexts. The interdisciplinary nature of his research connects computer science with environmental science and hydrology. Dr. Kropf has established long-term collaborations with researchers including Gilbert Babin (15 joint publications), Pascal Felber (14 publications), and Sabina Serbu (7 publications), forming a productive research network focused on distributed systems challenges. His work has appeared in prestigious venues including IEEE Internet Computing, Future Generation Computer Systems, and Middleware conference proceedings.

• Artificial Intelligence
• Machine Learning
• Agricultural Technology
• +3 more

Sayma Shammi is a Research Fellow at the University of Southern Queensland's School of Agriculture and Environmental Science. Her work focuses on integrating artificial intelligence and agricultural technology to enhance crop monitoring and climate resilience through innovative methods like UAV-based imaging and infrared thermography. BSc, North South University MSc, North South University PhD, Murdoch University Her research interests include artificial intelligence, machine learning, computer vision, and image processing in agriculture. She applies these technologies to early frost detection, water stress monitoring, and plant stress analysis using machine learning algorithms and remote sensing techniques. Recent publications highlight trends in precision agriculture, leveraging UAVs, multispectral imaging, and thermal data for crop health analysis. These works emphasize predictive modeling, climate adaptation, and data-driven farming solutions. ACS 1962 Medal (2023-2024) for outstanding doctoral research in Information Technology and Computer Science Vice-Chancellor's Gold Medal from North South University for academic excellence She has nine years of tertiary teaching experience, currently instructing AGR3105 Smart Data Farming, and collaborates with the Institute for Resilient Regions (IRR) at USQ to advance digital agriculture through technological innovation.

Carl MitchellView profile

Professor

• Biogeochemistry
• Hydrology
• Mercury Cycling
• +10 more

Carl Mitchell is a Professor in the Department of Physical and Environmental Sciences at the University of Toronto Scarborough Campus (UTSC), with graduate appointments in the Department of Geography and the School of the Environment at the University of Toronto. His research focuses on biogeochemical processes and contaminant transport, particularly mercury cycling, in diverse ecosystems including boreal forests, Arctic regions, and urban environments. PhD in Physical Geography, University of Toronto (2007) Postdoctoral Fellowship, Smithsonian Environmental Research Center (2008) Research interests include biogeochemistry , hydrology , mercury cycling , sulphur cycling , carbon cycling , and passive sampling techniques . His work explores how landscape features and human activities (e.g., forest harvesting, urbanization) influence mercury bioavailability and transport. Recent publications highlight studies on mercury dynamics in forest soils , beaver ponds , rice paddies , and Arctic ecosystems , with a focus on methylation/demethylation mechanisms and remediation strategies. Articles span environmental science, hydrology, and biogeochemical modeling. Awards include the Young Scientist Award from the Canadian Geophysical Union (2017), along with leadership roles as President (2019–21) and Past-President of the CGU. He serves as Associate Editor for Frontiers in Environmental Science . Supervised students and postdocs: Haiyong Huang (postdoc, 2024), Wai Ying Lam (postdoc, 2024), Sayuri Sagisaka Mendez (PhD candidate), and numerous alumni including David McLagan (now Assistant Professor, Queen’s University) and Colin McCarter (now Assistant Professor, Nipissing University). Teaching: EESB04 (Principles of Hydrology), EES1126 (Hydrology and Watershed Management) The WATER Group operates the CFI and MRI-funded Integrated Watershed Hydrology and Biogeochemistry Research Facility , combining field and lab-based methods to study contaminant transport.

• Biological Oceanography
• Nitrogen Cycling
• Carbon Cycling
• +7 more

Margaret Mulholland is a Professor at the Department of Ocean, Earth & Atmospheric Sciences , Old Dominion University. Her research focuses on biological oceanography , nitrogen cycling , and harmful algal blooms in marine and estuarine environments. Education : Ph.D. in Biological Oceanography (University of Maryland, 1998) M.M. in Marine Affairs (University of Washington, 1992) M.S. in Biological Oceanography (University of Washington, 1986) B.S. in Geology/Biology (University of Notre Dame, 1984) Research Highlights : Co-PI on multiple ECOHAB grants totaling over $5 million to study harmful algal blooms in Chesapeake Bay Investigated ocean acidification impacts on nitrogen fixation and microbial communities Explored nutrient dynamics in oxygen minimum zones and their effects on marine productivity Developed phycoremediation strategies for wastewater nutrient removal Scientific Contributions : Discovered cyanate utilization as a novel nitrogen source in marine systems Published extensively on dinoflagellate mixotrophy and bloom dynamics Examined climate change effects on coastal and Arctic nitrogen fixation Advising & Collaborations : Mentored numerous graduate students including Paul Bernhardt, Ben Widner, and Katherine Filippino. Collaborated with institutions like NOAA, NASA, and international universities on global nitrogen cycling studies. Labs & Teams : Leads the Marine Biogeochemistry Lab at Old Dominion University, focusing on coastal nutrient budgets and microbial interactions.

• Logic Programming
• Knowledge Representation
• Graph Databases
• +7 more

Ana Edelmira Pasarella Sanchez is a Professor in the Department of Computer Sciences at the Faculty of Mathematics and Statistics, Universitat Politècnica de Catalunya (UPC). She is a member of the ALBCOM research group, focusing on algorithms, bioinformatics, complexity, and formal methods. Her work bridges theoretical computer science with practical data systems. PhD in Computer Science, Universitat Politècnica de Catalunya Her research centers on logic programming, knowledge representation, and graph databases. She explores how formal methods can enhance data processing, particularly through dynamic pipelines and trust-aware access control. Her work integrates Datalog, semantic reasoning, and big data frameworks to improve scalability and correctness in knowledge systems. She has contributed to foundational semantics of logic programs and their applications in security and data integration. Her recent publications highlight a trend toward efficient, adaptive data processing systems, especially for graph analytics and knowledge graphs. She compares paradigms like MapReduce and pipelining, advocating for dynamic, functional approaches to big data. Her work increasingly addresses real-world challenges in federated knowledge graphs and access control. SACMAT 2017 Best Paper Award Pasarella has been involved in multiple competitive R&D+i projects, such as 'Modelos y Técnicas para el Procesamiento de Información a Gran Escala' and 'Modelos y métodos basados en grafos para la computación en gran escala,' indicating sustained funding and collaborative leadership. She advises on research direction within her group and mentors through collaborative publications. She has served on the scientific committee of the Latin American Informatics Conference (CLEI), contributing to the broader academic community. She is part of the ALBCOM research group and collaborates extensively with researchers like Fernando Orejas, Maria-Esther Vidal, and Elvira Pino, working on logic-based frameworks for data and security systems.

Stefan SeifermannView profile

Professor

• Energy Flexibility in Manufacturing
• Renewable Energy Systems
• Lean Production
• +4 more

Stefan Seifermann is a Professor for Production and Logistics at the Faculty of Industrial Engineering, Technische Hochschule Mannheim, since March 2019. He became Prodekan (dean) of his faculty in July 2022 and previously served as Studiengangleiter (program director) for the Master in Industrial Engineering from July 2019 to March 2023. Diploma in Industrial Engineering (TU Kaiserslautern, SFU Vancouver 2004) Dr.-Ing. (2017, TU Darmstadt) for dissertation on hybrid production cell automation His research focuses on Energy Flexibility in Manufacturing , Renewable Energy Systems , Lean Production , Production Process Optimization , Production Automation , and Industry 4.0 . He leads funded projects like the Kopernikus SynErgie series and FLoW-mIT. Recent publications analyze blockchain for supply chain traceability, deglobalization trends in manufacturing, and energy-flexible factories. He holds an office at Building L, Room 254, reachable at +49 621 292 6837. 2025 : KPI standardization in shopfloor management 2024 : Cost-benefit analysis of energy flexibility options 2023 : Environmental assessment of geothermal plants 2022 : Blockchain tracking, techno-economic flexibility studies 2018 : Value stream method 4.0, CNC automation 2017 : Flexible lean systems design in logistics He contributes to the Kopernikus Projects (SynErgie2-3) and FLoW-mIT (2023-2025), addressing energy grid stabilization and adaptive production systems. His work bridges technical feasibility with economic viability.