Find Academic Supervisors

Michela Bertolotto is a Professor in the School of Computer Science at University College Dublin (UCD). Her research focuses on spatio-temporal data modeling, GIScience, and applications of geospatial technologies in fields like urban planning and health informatics. She leads a research group and has supervised 19 PhD and 8 MSc students. Her work includes innovations in LiDAR-based flood risk visualization, semantic web quality assurance, and open-source spatial data analysis. Bertolotto has held roles including College Lecturer at UCD (2000–2006) and postdoctoral research positions at the University of Maine and University of Genoa. Education: BSc and PhD in Computer Science from the University of Genoa (1993, 1998). Professional achievements include over 100 publications, 24 grants (e.g., Science Foundation Ireland-funded Urban ARK project), and editorial roles at journals like the International Journal of Geographical Information Science. Awards include the UCD President's Research Award (2001) and NATO Postdoc Fellowship (1998–1999). Research interests span map personalization, volunteered geographic information (VGI), and geospatial data quality. Her lab develops tools like the LAMSkyCam (low-cost sky imaging system) and dynamic flood risk viewers. She chairs international conferences and serves on program committees for GIScience events.

• Spatio-temporal data modeling
• Mobile and web-based GIS
• Map personalisation
• +6 more

Dr. Timilehin Aderinola is a Marie Curie Postdoctoral Fellow at the School of Computer Science, University College Dublin. His research focuses on applying machine learning and computer vision to analyze human movement, particularly in neurological conditions like Parkinson's disease. He holds a PhD in Information Technology from Multimedia University, Malaysia (2022), and master's and bachelor's degrees from Federal University of Technology Akure, Nigeria (2017 and 2012). Education: B.Eng. (Hons) in Electrical and Electronic Engineering, Federal University of Technology Akure (2012) M.Sc. in Computer Science, Federal University of Technology Akure (2017) PhD in Information Technology, Multimedia University Malaysia (2022) Research Interests: Machine Learning and Computer Vision Human Motion Analysis (e.g., gait analysis, fall detection) Applications in healthcare and surveillance Awards: Silver Medal (2021) for commercialization potential of PhD work Honourable Mention (2021) at NP2C poster competition Advising/Grants: Co-supervised research projects on exercise classification and human pose estimation. Engaged in peer review for conferences like ECML-PKDD and ICoICT. Labs/Teams: Active in the Insight Centre for Data Analytics at UCD, focusing on NeuroInsight Marie Skłodowska-Curie Fellowship projects analyzing mobility data for neurological patients.

• Machine Learning
• Computer Vision
• Human Motion Analysis
• +3 more

Prof. Paul Cahill is a Full Professor and Head of the School of Biotechnology at Dublin City University (DCU), within the Faculty of Science and Health. He holds roles such as Chair of Vascular Biology & Therapeutics and Director of the Vascular Health Research Centre. His research focuses on cardiovascular diseases, particularly arteriosclerosis, vascular stem cells, and extracellular vesicles (EVs). Key areas include developing point-of-care diagnostics using exosomal profiling, understanding Notch/Hedgehog signaling in vascular lesions, and engineering vascular tissues using nanomaterials. His academic journey spans roles from Research Fellow (1990–1992) to Professor (2001–present) at DCU, with adjunct positions at institutions like the University of Rochester Medical Centre. His work integrates biomechanical stimuli, epigenetics, and computational modeling to address vascular disease mechanisms. He leads the Vascular Biology & Therapeutics Group and contributes to interdisciplinary research in medical engineering and biomaterials. Research highlights include investigating alcohol's dual effects on vascular stem cells, mechanotransduction in vascular cells, and exosome-based biomarker discovery. His lab employs advanced techniques like single-cell spectroscopy, microfluidics, and magnetic nanoparticles for drug delivery. Despite prolific publication output, no specific awards are listed, though his contributions to vascular biology are internationally recognized.

• Vascular Biology
• Extracellular Vesicles (EVs)
• Gene Regulatory Networks
• +5 more

Ehsan Namjoo serves as a Research Fellow in the Department of Electronics & Computer Engineering at the University of Limerick, with a primary affiliation at Lero – the Irish Software Research Centre. His multidisciplinary work bridges theoretical signal processing, machine learning applications, and hardware implementation for real-world systems. His research spans signal processing (DOA estimation under non-ideal noise conditions, EEG source imaging), machine learning (explainable AI for medical diagnostics, feature selection in cancer detection), and computer engineering (polar code decoders, visible light communication systems). Notable biomedical applications include breast cancer diagnosis and epileptic source analysis, while cybersecurity work focuses on intrusion detection in cloud environments. Recent publications (2021-2025) reveal a consistent trajectory toward developing lightweight, interpretable models for tabular medical data alongside robust signal processing frameworks for communication systems. His work increasingly integrates hardware-aware algorithms, particularly in polar coding implementations, and emphasizes practical validation through experimental demonstrations in visible light networks. As an active Lero researcher, Namjoo participates in Ireland's national software research ecosystem, contributing to interdisciplinary projects that connect theoretical innovations with healthcare, communications, and security applications through collaborative frameworks.

• Signal Processing
• Machine Learning
• Computer Engineering
• +3 more

Dr. Anh Vu Vo is an Assistant Professor at University College Dublin's School of Computer Science, specializing in high-scalability algorithms for LiDAR and urban spatial datasets. He holds a PhD from UCD, a Master's from the University of Melbourne, and a Bachelor's from HCMC University of Architecture. Roles : Lecturer/Assistant Professor since 2024, Postdoctoral Research Fellow (2019–2022), Research Scientist at NYU (2018–2019). Research Interests : LiDAR, Urban Science, Spatial Data Management, Distributed Computing, and Big Data. Key projects include CAMEO (Earth Observation platform), UrbanARK (flood risk assessment), and AIMVIE (mangrove mapping). He has authored over 30 peer-reviewed publications and secured grants such as the SFI Future Innovator Prize. Awards : 2022 EODisrupt Winner, 2015 IEEE GRSS Data Fusion Contest First Prize, Australian Endeavour Award. Teaching : Spatial Information Systems, Urban Sensing, and graduate-level courses. His work focuses on integrating LiDAR data with advanced computing frameworks to address urban challenges like flood risk and infrastructure planning.

• LiDAR
• Urban Science
• Spatial Data Management
• +4 more

Professor Paul Aplin is Head of the Department of Geography at Mary Immaculate College (MIC), Ireland, since 2022. He previously held academic positions at the University of Nottingham (2007-2022) and Edge Hill University (2015-2022). He holds a PhD from the University of Southampton, MSc from Aberdeen, and MA from Edinburgh. Education: MA (Edinburgh) MSc (Aberdeen) PhD (Southampton) His research focuses on remote sensing , geography , and environmental monitoring of tropical peatlands, urbanization, and biodiversity. He has contributed to the discipline through editorial leadership as Editor-in-Chief of the Land (Observation and Monitoring Section) and editorial board memberships for ISPRS Journal , Remote Sensing Applications , and Sensors . His work spans 15 years of international education and research collaborations in Hungary, Chile, China, Ethiopia, and Poland. Article Trends include applications of machine learning and satellite imagery for land cover classification, biomass estimation, and urban development analysis. His 15 most recent publications (2024-2020) emphasize neotropical peatlands , woody encroachment , and conservation strategies in biodiversity hotspots. Scientific Awards Ralph Brown Award (Royal Geographical Society) Fellow of the Royal Geographical Society He has also served as former Chair of the Remote Sensing and Photogrammetry Society, National Delegate to the International Society for Photogrammetry and Remote Sensing (ISPRS), and ISPRS Book Series Editor for eight years.

• Remote Sensing
• Geography
• Tropical Peatland Conservation
• +5 more

Dr. Aoife Donnelly serves as a Lecturer in the School of Food Science and Environmental Health at Technological University Dublin (TU Dublin), teaching environmental sciences, protection policy, and health impacts since 2016. Her academic foundation includes a Ph.D. in Engineering from Trinity College Dublin focused on Irish air pollution modeling, followed by industry experience as an Environmental Analyst specializing in emissions control and an EPA fellowship-funded postdoctoral position developing Ireland's national air quality forecast model. Her transdisciplinary research applies spatio-temporal statistical and deterministic modeling to environmental health challenges, with core expertise in air pollution forecasting, anthropogenic emissions analysis, and fungal spore concentration modeling. She pioneered investigations into population health benefits from blue and green exercise, sustainable transportation, citizen science engagement, and pro-environmental behavior change. Her methodological innovations bridge environmental science with public health outcomes through evidence-based intervention design. Analysis of her 2011-2019 publications reveals three dominant research trajectories: advanced air quality modeling techniques for Ireland (accounting for 70% of output), health impact assessments of environmental factors (20%), and interdisciplinary studies on nature-human interactions (10%). This progression demonstrates increasing integration of environmental engineering with behavioral health sciences, particularly in quantifying reciprocal benefits of human-nature engagement. Scientific recognition includes: EPA fellowship for postdoctoral air quality model development Dr. Donnelly's collaborative work spans environmental agencies, public health institutions, and sports science researchers, evidenced by co-authorship with Trinity College Dublin's Broderick and Misstear on atmospheric studies and MacIntyre on green exercise projects. Her research has secured funding through Ireland's Environmental Protection Agency for air quality forecasting systems and citizen science initiatives investigating sustainable physical activity. She maintains active partnerships with Ireland's environmental monitoring networks and international green exercise research consortia, directing projects that combine air pollution data with behavioral health metrics to inform urban planning and public health policy.

• Air Quality Modelling
• Environmental Health
• Spatio-temporal Statistical Modelling
• +7 more

Alessandra Mileo is Associate Professor and Data Science Programme Chair at Dublin City University's Faculty of Engineering and Computing. As a Principal Investigator at the Insight SFI Research Centre for Data Analytics, her research focuses on neurosymbolic AI, explainability, and representation learning. Education includes an M.Sc. and Ph.D. in Computer Science from the University of Milan. Current research investigates methods combining knowledge-driven and data-driven AI approaches to enhance explainability and reduce bias in machine learning systems. Research leadership includes EU projects like CityPulse (IoT stream processing) and industry collaborations on Internet of Everything infrastructures. Teaches data science courses and supervises multiple PhD students.

• Stream Reasoning
• Neurosymbolic AI
• Explainable AI
• +3 more

Dr. Sturrock is a Lecturer in Biophysics and Computational Biology in the Department of Physiology. He holds a B.Sc. in Applied Mathematics (2009) and a Ph.D. (2013) from the University of Dundee, focusing on spatio-temporal models of gene regulatory networks. His postdoctoral work includes research at The Ohio State University (macromolecular crowding, cell polarization) and Imperial College London (stochastic gene expression, synthetic Turing patterns). B.Sc., Applied Mathematics, University of Dundee (2009) Ph.D., University of Dundee (2013) His research centers on computational modeling of biological systems, including gene regulation, cell polarization, and cancer dynamics. Publications highlight the role of stochasticity in gene networks, spatial effects in signaling, and applications to glioblastoma and synthetic biology. Topics span mathematical biology, systems biology, and biophysics. Recent articles emphasize machine learning integration for genomic selection, Bayesian network inference, spatio-temporal cancer modeling, and stochastic simulations. Key methodologies include agent-based modeling, synthetic data generation, and compartmentalized systems analysis. He has collaborated with institutions such as the Mathematical Biosciences Institute at Ohio State and synthetic biology groups at Imperial College London, though no current lab affiliations are detailed in the provided text.

• Biophysics
• Computational Biology
• Gene Regulatory Networks
• +6 more