Find Academic Supervisors

• Aberration-Corrected Electron Microscopy
• Atomic-Resolution Imaging
• Nanomaterials Characterization
• +4 more

Dr. Lewys Jones is an Associate Professor in the Department of Physics at Trinity College Dublin . His research focuses on advancing Scanning Transmission Electron Microscopy (STEM) techniques for atomic-scale materials characterization, particularly in low-dose imaging, detector optimization, and 3D tomography. Key Research Areas: Aberration-Corrected Microscopy, Atomic-Resolution Imaging, Nanomaterials Analysis, and Machine Learning for Image Enhancement Instrumentation Expertise: Detector Calibration, Probe Drift Compensation, Low-Voltage Imaging, and Digital Pulse Read-Out Systems His work has resulted in multiple peer-reviewed publications (2013-2024) with a focus on electron microscopy innovations and nanostructured materials . Notable scientific awards include the Royal Society & SFI University Research Fellowship (2019) and the International Federation of Societies for Microscopy 'Young Scientist Award' (2014). He has contributed to open-access resources and educational tools for STEM data analysis, including the 'Smart Align' software.

• Pedestrian Trajectory Prediction
• Crowd Monitoring Systems
• Computer Vision
• +6 more

Muhammad Haris Kaka Khel is a part-time lecturer at Atlantic Technological University's Department of Computing in Ireland while pursuing his Ph.D. in pedestrian trajectory prediction. His research focuses on developing adaptive systems that analyze human behavior, social interactions, and environmental dynamics to forecast multiple possible pedestrian paths using the PATHS framework. He works under supervisors Dr. Kevin Meehan and Dr. Paul Greaney at ATU Donegal, with additional guidance from Dr. Marion McAfee (ATU Sligo) and Dr. Sandra Moffet (Ulster University). B.S. in Electrical Engineering (Communication specialization) from UET Peshawar, Pakistan (2019) Research master's at University of Kuala Lumpur, Malaysia (completed 2022) with Erasmus exchange experience at Politecnico di Torino, Italy Ph.D. candidate at Atlantic Technological University (expected completion 2026) Research Interests Khel's work addresses critical gaps in pedestrian trajectory prediction by modeling multiple possible paths rather than single deterministic outcomes. This approach enhances robustness in dynamic environments like urban streets and public spaces, with applications in: Autonomous vehicle navigation safety Urban planning and walkability improvements Event crowd management systems Smart surveillance for anomaly detection Accessible navigation for visually impaired Public transportation optimization Teaching & Collaboration As a part-time lecturer at ATU Donegal, he contributes to computing education while maintaining external collaborations including: Sponsored research with Saudi Arabia's Deputyship for Research and Innovation Graduate research assistant role at University Kuala Lumpur-British Malaysian Institute Former intern at Center of Intelligent Systems and Networks Research

Peter DoranView profile

Professor

• Clinical Trials Methodology
• Biomarker Discovery and Validation
• Acute Kidney Injury
• +3 more

Professor Peter Doran serves as Full Professor and Director of the UCD Clinical Research Centre at the UCD School of Medicine . With a PhD in Immunology from University College Dublin (2001), his work focuses on clinical trial methodology, biomarker validation, and critical illness complications. BSc: Dublin City University (1998) PhD: University College Dublin (2001) Research Interests span Clinical trials optimization Biomarker discovery for organ damage Acute kidney injury pathophysiology Immune response to SARS-CoV-2 Digital health implementation Host microbiome interactions His recent publications examine machine learning-based biomarkers, SARS-CoV-2 immunity thresholds, and regional practice variations in critical care. Professional Activities include chairing the UCD Biomedical Research Degrees Committee and serving on multiple international panels: American Association for the Advancement of Science, European Clinical Research Infrastructure Network (ECRIN), and European Middle Eastern African Society for Biobanking. Teaching Responsibilities encompass coordinating graduate clinical research modules and developing UCD's Clinical and Translational Research program. His laboratory, the UCD-Abbott Biomarker Programme, houses high-throughput validation systems for end-organ damage markers.

• Protein-based molecular switches
• Molecular simulation
• Non-adiabatic quantum dynamics
• +7 more

Dr. Donal Mac Kernan is a Research Scientist at the School of Physics, University College Dublin, with extensive expertise in computational biophysics and molecular modeling. His work focuses on developing protein-based molecular switches through physics-based rational design and genetic engineering. He serves as the director of the Irish CECAM node and is a Fellow of the Conway Institute for Biomedical and Biomolecular Research. BSc from University College Hospital Galway MSc from University of Maryland PhD in Chaos Theory from Université Libre de Bruxelles (awarded with "Le plus grand distinction") Dr. Mac Kernan's research spans multiple interdisciplinary fields including molecular simulation, non-adiabatic quantum dynamics, chaos theory, and artificial intelligence. His primary focus is on protein-based molecular switches that modulate protein function in response to biomarkers, with applications in optical activity, scattering, and cytotoxicity for chemotherapeutics. He has developed innovative approaches to computational (bio)materials modeling and has made significant contributions to understanding protein structure-function relationships in food science. His recent publication trends show a strong focus on computational biophysics, particularly in protein engineering and molecular simulation techniques. His work integrates experimental data with computational models to address challenges in biomaterial research, including multi-scale modeling, data validation, and reproducibility. He has pioneered approaches to FRET sensor design, protein flexibility analysis, and proton titration schemes for biomolecular simulations. Two patent filings related to protein-based molecular switches Fellow of the Conway Institute for Biomedical and Biomolecular Research Principal Investigator for multiple research awards totaling over 2M€ Dr. Mac Kernan has substantial teaching and mentoring experience, having supervised 14 undergraduate thesis students in theoretical physics. He teaches advanced courses including C programming for physics and chemistry students and quantum mechanics at the undergraduate level. His research group has secured significant funding for projects at the intersection of physics, biology, and computational science. As director of the Irish CECAM node, Dr. Mac Kernan leads computational science initiatives that connect researchers across Ireland with the European network for computational science. His work with the Nanoscale Simulators of Ireland and SimBioMa (European Science Foundation) demonstrates his commitment to collaborative research in computational biophysics and materials science.

• Multiple Myeloma
• Genomics
• Precision Medicine
• +6 more

Prof Siobhan Glavey holds the RCSI Chair and Professor of Pathology position, with dual affiliation at Royal College of Surgeons in Ireland (RCSI) and Beaumont Hospital. She serves as a Consultant Haematologist and Principal Investigator, leading clinical and translational research in multiple myeloma and precision medicine. Professor of Pathology, RCSI (2020-present) Honorary Senior Clinical Lecturer, RCSI (2019-2020) Clinician Scientist, RCSI and Beaumont Hospital (2019-present) Her research focuses on genomic profiling of multiple myeloma, particularly chromosome 1 abnormalities and SKY-92 high-risk subtypes. She investigates spatial immune cell relationships in bone marrow using AI algorithms, and develops novel therapeutic strategies including 5-azacytidine/venetoclax combinations and adoptive immunotherapy approaches. Recent publications highlight her work on: Genomic instability in high-risk myeloma AI-driven spatial pathology analysis Thromboprophylaxis challenges in myeloma Bispecific antibody safety/efficacy Myeloma microenvironment interactions She has secured competitive funding from: Health Research Board (HRB) Irish Cancer Society Breakthrough Cancer Research Beaumont Hospital Foundation Pfizer Industry Grants

Shubham VishnoiView profile

Researcher

• Physics-based Molecular Simulations
• Computational Protein Design
• GPCR Modelling
• +4 more

Dr. Shubham Vishnoi is a Postdoctoral Researcher at the University of Limerick within the Faculty of Science and Engineering, Department of Physics . He completed his PhD in Physics in 2023 under the supervision of Professor Damien Thompson, funded through the Science Foundation Ireland SSPC research center for Pharmaceuticals. He holds advanced degrees in Pharmaceutical Sciences from NIPER Mohali, India (M.S. 2019) and first-class honours in B.Pharm (2017). Research Expertise: Specializing in physics-based molecular simulations and computational protein design , his work focuses on G protein-coupled receptor (GPCR) modeling and atom-scale simulation techniques. He combines machine learning with high-throughput data analysis to solve critical challenges in biopharmaceutical formulation design , particularly for peptide-based therapeutics . 2021 SSPC Industrial PhD Placement Award Three-time winner of President's Volunteer Award (2020, 2021, and special recognition for COVID-19 Volunteering ) Industry Experience: Completed impactful placement at APC Ltd, Dublin (2021-2022) developing machine learning tools for drug solubility analysis and high-throughput screening visualization systems. Collaborated with Upstream Bioprocessing teams on digital transformation initiatives in pharmaceutical R&D.

Pepijn Van De VenView profile

Professor

• Machine Learning
• Artificial Intelligence
• eHealth
• +7 more

Pepijn Van De Ven is a Professor in the Department of Electronic and Computer Engineering at the University of Limerick, with affiliations to multiple research centers including the Centre for Research Training in Foundations of Data Science, Data-Driven Computer Engineering Research Centre, and Lero – the Research Ireland Centre for Software. His work bridges artificial intelligence with healthcare applications, particularly focusing on mental health interventions, mobile app development, and ambient assisted living technologies. PhD in AI Techniques for Marine Vehicles (UL, 2005) MSc in Electronic Engineering (Eindhoven University of Technology, 2000) His research interests center on leveraging machine learning and mobile ICT to enhance mental health care, with a specific emphasis on eMental Health, treatment prediction models, and context-aware intervention systems. He also explores computer vision applications in waste classification, medical imaging, and Industry 4.0 safety systems. The trends in his recent publications highlight interdisciplinary work combining computer vision (e.g., instance segmentation, contamination detection), mental health (e.g., depression, diabetes comorbidity), and AI-driven clinical tools (e.g., interpretable models, Bayesian analysis). Subfields like ecological momentary assessment, graph-based learning, and human-AI trust mechanisms are recurrent. Pepijn has contributed to teaching through modules on Android programming and has held leadership roles such as Course Leader for the National MSc in Artificial Intelligence at UL and Past-President of the International Society for Research on Internet Interventions (ISRII). He leads significant research projects including the PROACTIVE (UK-MRC), PERSONAE (Innovation Fund Denmark), and BINSPECT (Science Foundation Ireland) grants. Current research group: D2iCE (Design, Intelligence, and Computer Engineering) Collaborations: King’s College London, University of São Paulo, University of Bristol

• Deep Learning
• Cybersecurity
• Smart Manufacturing
• +3 more

Iram Arshad is a Research Engineer at the Technological University of the Shannon: Midlands Midwest, specializing in cybersecurity and deep learning applications. Their work addresses critical challenges in smart manufacturing, adversarial machine learning, and data security. Research contributions include frameworks for detecting backdoor attacks in deep neural networks and methodologies for enhancing transparency in technology education research. Arshad's expertise aligns with UN Sustainable Development Goals related to industry innovation and infrastructure. Education: Doctoral degree from Technological University of the Shannon (2024) Key research interests focus on backdoor attacks, deep learning model vulnerabilities, and Industry 4.0 cybersecurity. Recent work explores runtime data-free attack methods and big data testing challenges. Arshad has collaborated internationally on projects addressing adversarial machine learning and educational research transparency.

• Internet of Things (IoT)
• Cyber-Physical Systems (CPS)
• Smart Manufacturing
• +4 more

Dirk H J Pesch is a Professor at the School of Computer Science and Information Technology , University College Cork (UCC), and currently serves as Head of School. His research focuses on future networked systems for the Internet of Things (IoT) and Cyber-Physical Systems (CPS), with applications in smart communities, health, and manufacturing. He leads the Science Foundation Ireland-funded ADVANCE CRT and is a co-PI of the CONNECT Centre . Prior to UCC, he was at Cork Institute of Technology (now Munster Tech U), where he founded the Nimbus Research Centre. He holds a PhD from the University of Strathclyde and a Dipl.Ing from RWTH Aachen University. Research Interests include IoT/CPS protocols, system architectures, interoperability challenges, and AI-driven analysis for well-being. He has authored/co-authored over 250 publications and co-edited a book on energy-positive urban systems. His work spans conference organization (e.g., IEEE SmartComp 2025 General Chair) and industry collaborations, with €80M+ in grant funding. Key contributions include developing low-power wireless protocols (e.g., MeshMAC), smart building monitoring systems, and frameworks for IoT in energy-positive neighborhoods. His recent work explores loneliness detection via passive sensing and 6G-V2X technologies for autonomous driving. Grants & Leadership: Directed €16M of his own research grants, managed large-scale EU/Irish projects, and advised on industrial IoT implementations. His Nimbus Centre became a leader in IoT applications under his leadership. Labs/Teams: Founded Nimbus Research Centre; active in Cork Smart Gateway initiative. Supervised numerous students and researchers in interdisciplinary projects.

William J. MatthaeusView profile

Research Fellow

• Ecosystem Modeling
• Evolutionary Biology
• Climate-Vegetation Interactions
• +4 more

William J. Matthaeus is a Research Fellow at Trinity College Dublin, working on the ERC-funded TERRAFORM project. His research focuses on advancing mechanistic models of ecosystems, evolution, and plant-climate interactions using fossil-derived traits. He holds a PhD in Biology (2021) from Baylor University, an MSc in Population Genetics, and a BSc in Mathematics from the University of Delaware. Research Interests: Ecosystem dynamics and evolutionary processes in mathematical models Plant functional traits and their role in geologic-scale climate-vegetation feedbacks Integration of numerical methods and machine learning in ecological analysis Professional Context: Currently contributes to the TERRAFORM project's efforts to improve Earth system models through paleontological data synthesis. His interdisciplinary work bridges botany, computational science, and evolutionary biology.

Alina PremrovView profile

Research Fellow

• Biogeochemical Processes
• Ecosystem Modelling
• Climate Change Mitigation
• +3 more

Dr. Alina Premrov is a Research Fellow at the Discipline of Botany, Trinity College Dublin, the University of Dublin. Her research focuses on biogeochemical processes in terrestrial ecosystems, particularly peatlands, with an emphasis on greenhouse gas emissions, soil organic carbon dynamics, and climate change mitigation. She leads the EPA-funded CO 2 PEAT project, aiming to refine methodologies for reporting CO 2 removals and emissions from Irish peatlands. Prior roles include lecturing in Geography at Maynooth University and postdoctoral research on soil carbon and pesticide risk modelling. Education: PhD in Geology from Trinity College Dublin (2011), focused on nitrate leaching reduction measures in tillage farming. Postdoctoral work included contributions to the CForRep, AUGER, and SOLUM projects, advancing soil carbon stock estimation and biogeochemical modelling. Research Interests: Peatland restoration, GHG flux modelling, pesticide risk assessment, and policy-driven environmental science. Her work integrates advanced models like ECOSSE with observational data to address land use and climate impacts on ecosystems. Recent efforts focus on enhancing IPCC Tier methodologies for peatland reporting and developing tools like the miniRECgap package for CO 2 flux data gap-filling. Grants & Roles: Principal Investigator of the CO 2 PEAT project (EPA grant 2022-CE-1100). Collaborated on DAFM's PROTECTS project and contributed to ECOSSE model enhancements for drained peatlands. Her research has been published in journals like Science of the Total Environment and Geoderma. Labs & Teams: CO 2 PEAT project team at Trinity, ICARUS Department at Maynooth University. Active in interdisciplinary collaborations on ecosystem modelling and climate policy.

• Artificial Intelligence
• Machine Learning
• Data Science
• +5 more

Dr. Gregory Doyle is a Senior Lecturer in the Department of Computing at South East Technological University (SETU), part of the Faculty of Science. He holds a PhD in Computer Science (Data Science) from SETU, an MSc in Computer Applications from Dublin City University, and a BSc in Applied Computing from Waterford Institute of Technology. His research focuses on AI, machine learning, data science, InsurTech, Fintech, and service systems, with a strong emphasis on industry collaboration. Education: PhD in Computer Science (Data Science), SETU, 2010 MSc in Computer Applications, Dublin City University, 1996 BSc in Applied Computing, Waterford Institute of Technology, 1993 Dr. Doyle leads the Advanced Machine Intelligence Research (AdMIRe) group and directs the InsurTech Network Centre (INC) at SETU. His work spans applied research in intelligent systems, including projects on adaptive exergames for elderly exercise motivation and optoelectronic systems for data analysis. He has secured funding from national and European agencies and actively supervises postgraduate students. His recent publications explore topics such as tensiography platforms, data diffraction methods, and simulation models for engineering applications. He is deeply involved in interdisciplinary efforts, contributing to the UN Sustainable Development Goals through education and innovation.

Peter CarewView profile

Lecturer

• Computer Programming
• Artificial Intelligence
• Human-Centred Systems
• +5 more

Dr. Peter Carew is a full-time lecturer in Computing and Mathematics at SETU Waterford, specializing in computer programming, artificial intelligence, human-centred systems, and computer ethics. He holds a PhD (2009), MSc (2001), and BSc (1996). His research focuses on cultural heritage technologies, human-centred AI, and EDI (Equality, Diversity, Inclusion) in higher education. Education History: PhD in Computing (2009) Masters Degree in Computing (2001) Bachelors Degree in Computing (1996) Research Interests include developing smart digital heritage spaces using XML-based approaches, human-centred machine learning applications, and frameworks for EDI in HEI institutions. His work integrates interdisciplinary methods like action research and case studies to address real-world challenges in technology and education. Recent publications emphasize cultural heritage preservation, smart space modelling, and EDI frameworks. He has received the Teaching Hero Award (2021) for academic contributions. Advising & Grants: Supervised 2 works (names not listed). External roles include External Examiner positions at Cork Institute of Technology (2012–2015), Galway-Mayo Institute of Technology (2010–2011), and The Institute of Bankers in Ireland (2016–2021). Previously worked at Apple (1996–1998) and Allied Irish Bank (1995). Lab/Team: Associated with the INSYTE-Cooley Research Lab, focusing on cultural heritage systems and technology.

• Quality-of-Experience
• Virtual Reality
• Multimedia Systems
• +2 more

Dr. Niall Murray is a Senior Lecturer in the Department of Computer and Software Engineering within the Faculty of Engineering and Informatics. His research focuses on enhancing user experiences through immersive technologies and quality-of-experience measurement frameworks. His scholarly work spans virtual/augmented reality systems, multimedia quality assessment, and human-computer interaction paradigms. Recent investigations explore physiological signal analysis for experience evaluation and accessible computing solutions. Publications demonstrate consistent focus on optimizing extended reality applications across domains including education, industrial design, and assistive technology. Research outputs frequently incorporate multimodal interfaces and machine learning approaches.

• Wireless Sensor Networks
• Machine Learning
• Deep Learning Methods
• +5 more

Shagufta Henna is a Lecturer in Computer Science at the Department of Computing, Atlantic Technological University. Her research focuses on machine learning applications in wireless sensor networks, IoT systems, cybersecurity, and environmental monitoring. She contributes to UN Sustainable Development Goals through projects addressing environmental sustainability and health. Her expertise includes federated learning for malware detection in healthcare IoT, deep learning optimization for sensor networks, explainable AI for water quality prediction, and ensemble methods for human activity recognition. Recent work highlights include: Developing graph neural networks for IoT-based healthcare cybersecurity Accelerating environmental monitoring via deep learning in uncontrolled sensor networks Deploying SHAP-based XAI for water quality prediction interpretability No scientific awards explicitly listed. Research output includes 45 publications across journals and conferences, with recent contributions in Results in Engineering and IEEE proceedings. Active collaborations span international institutions focusing on AI-driven environmental and healthcare solutions.