جست‌وجوی استاد و پژوهشگر

Conor Ryanمشاهده پروفایل

استاد

• Genetic Programming
• Genetic Algorithms
• Grammatical Evolution
• +۷ مورد دیگر

Conor Ryan is a Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a Science Foundation Ireland-funded Investigator since 2002 and a member of multiple research centres including Lero – the Irish Software Research Centre and the Limerick Digital Cancer Research Centre. His research focuses on Genetic Programming, Grammatical Evolution, and their applications in domains like healthcare analytics, digital circuit design, and financial modeling. He has authored over 250 publications, with recent work emphasizing automated feature selection in medical diagnostics, neural architecture search, and blockchain ecosystems. Teaching includes courses on Foundations of Computer Science and Computer Games Programming. Research interests span evolutionary computation, machine learning, and interdisciplinary applications. Collaborations involve global institutions, reflecting his work's impact across computer science, engineering, and healthcare. His research has addressed challenges in breast cancer diagnosis via genetic algorithms, cryptocurrency volatility prediction using random forests, and automated generation of digital circuits. Ongoing projects explore interpretability in AI, energy-efficient computing, and sustainable transport systems through predictive analytics. Professional memberships include roles in the Centre for Research Training in Foundations of Data Science and the Data-Driven Computer Engineering Research Centre, underscoring his commitment to interdisciplinary innovation.

Jon Grudaمشاهده پروفایل

استادیار

• Organizational Behavior
• Leadership Studies
• Personality Psychology
• +۴ مورد دیگر

Dr. Jon Gruda is an Assistant Professor and Lecturer in Organisational Behaviour at Maynooth University's School of Business. He holds a PhD in Management from emlyon Business School (France) and a joint Dr. rer. nat. in Psychology from Goethe University Frankfurt. His research focuses on relational leadership, dark leadership traits, anxiety in the workplace, and personality psychology, with a strong emphasis on integrating machine learning and AI methodologies. Gruda has been recognized with prestigious awards, including selection for the Lindau Nobel Laureates Meeting in Economic Sciences (2020). His interdisciplinary work includes predicting anxiety and personality traits via social media data analysis. He serves as an Associate Editor for journals like Personality and Individual Differences and Frontiers in Psychology . Education PhD in Management, emlyon Business School (2012–2017) Dr. rer. nat. in Psychology, Goethe University Frankfurt (2012–2017) MSc in Affective Neuroscience, Maastricht University (2018) MSc in Management Research, emlyon Business School (2012–2014) Triple MSc in Management, City University London/ESCP Europe (2010–2012) BSc in International Business & Management, University of Groningen (2007–2010) Research Interests Gruda’s work bridges leadership studies, personality psychology, and data science. Key areas include: Dark leadership traits (e.g., narcissism, Machiavellianism) and their organizational impacts Machine learning applications for detecting anxiety and personality traits via social media Cross-cultural studies on leadership perceptions and attachment orientations Impact of physiological/psychosocial factors on leadership effectiveness Publications & Projects Recent projects include predicting state-level health outcomes linked to narcissism and developing algorithms to track anxiety using Twitter data. Over 20 peer-reviewed articles since 2017 highlight his contributions to organizational behavior and computational social science. Awards 7th Lindau Nobel Laureates Meeting on Economic Sciences (2020) Benedictine University Award (Academy of Management, 2020) Wharton Global Faculty Development Program (2020) Grants & Collaborations Gruda leads projects on pro-environmental behavior and collaborates with the National Care Experience Programme on healthcare feedback analysis. Seed funding includes €301,930 for computational text analytics in healthcare. Labs & Teams Interdisciplinary research collaborations span psychology, data science, and public health, with a focus on applying machine learning to organizational challenges.

Rozenn Dahyotمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Digital Signal Processing
• +۴ مورد دیگر

Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.

Rosemary Monahanمشاهده پروفایل

استاد

• Software Verification
• Dependable Software Systems
• Formal Methods
• +۳ مورد دیگر

Rosemary Monahan is a Professor in the Department of Computer Science at Maynooth University and an affiliate of the Hamilton Institute. She holds BSc and MSc degrees from University College Dublin and a PhD from Dublin City University. As Maynooth University's institutional lead for ADAPT (SFI Research Centre for AI-Driven Digital Content Technology), she focuses on advancing software dependability through formal methods and AI integration. Her research interests include safety-critical systems, dependable software, formal verification, and computational thinking education. She co-founded the VerifyThis competition series and leads projects such as MAIVV (Modular AI Verification and Visualisation) funded by SFI, and VALU3S (Verification and Validation of Automated Systems) funded by Horizon 2020. She has secured over €2.5M in EU funding for the Erasmus Mundus programs in dependable software systems. Monahan’s educational contributions include pioneering computational thinking resources (CoCoA and InSPECT projects) and teaching modules on software verification and rigorous software processes. She supervises PhD students in data science and advanced networks and collaborates with institutions like INRIA, Microsoft Research, and Amazon Web Services. Her professional roles include editorships in journals like Science of Computer Programming and leadership in conferences like iFM and FMICS. She actively promotes gender equality in computing through initiatives like INGENIC and TechMate toolkits.

Jennifer Edmondمشاهده پروفایل

دانشیار

• Digital Humanities
• Research Infrastructures
• Open Science
• +۲ مورد دیگر

Jennifer Edmond is Associate Professor of Digital Humanities and co-director of the Trinity Center for Digital Humanities at Trinity College Dublin, where she also directs the MPhil in Digital Humanities and Culture. She holds a PhD in Germanic Languages and Literatures from Yale University and specializes in applying advanced methods and infrastructures for arts and humanities research. Her research focuses on Digital Humanities, Research Infrastructures, Open Science, Cultural Heritage, and Knowledge Technologies. She has developed significant expertise in European research policy, having coordinated the €6.5m CENDARI FP7 project and participated in numerous EU initiatives including PARTHENOS, Europeana Cloud, and the Computational Literary Studies Infrastructure (CLS Infra). Dr. Edmond maintains an active publication record exploring digital scholarly editing, privacy in literary texts, open science practices, and cultural heritage narratives. Her recent work demonstrates a strong focus on the intersection of technology and democracy, digital ethics, and innovative methodologies for humanities research. Awards and Honors: Named one of Ireland's five 'Champions of EU Research' (2012) She served as President of DARIAH-EU's Board of Directors (2018-2022) and represented the organization on the European Commission's Open Science Policy Platform. Dr. Edmond has contributed to strategic developments at national and institutional levels, while actively promoting public outreach through various media formats and art installations.

David Lillisمشاهده پروفایل

دانشیار

• Natural Language Processing
• Artificial Intelligence
• Digital Forensics
• +۴ مورد دیگر

David Lillis is an Associate Professor in the School of Computer Science at University College Dublin (UCD). His research focuses on Natural Language Processing (NLP), Artificial Intelligence (AI), and their applications in legal and forensic contexts. He leads projects like CeADAR (Ireland’s Applied AI Center) and the Transpire project, collaborating with organizations such as Corlytics and the Department of Enterprise, Trade and Employment. He holds adjunct roles as a Guest Professor at Beijing University of Technology’s Data Mining and Security Lab and has been a Fulbright Scholar at the University of New Haven’s Cyber Forensics Research and Education Group. Education: B.A. (Hons) in Law and Accounting, University of Limerick Higher Diploma in Computer Science, UCD M.Sc., Ph.D. in Computer Science, UCD Professional Certificate in University Teaching & Learning, UCD Research Interests: Legal AI, digital forensics, machine learning, multi-agent systems, and information retrieval. Recent work includes NLP for regulatory analysis, crop yield prediction via neural networks, and AR-driven decision support systems. Grants & Projects: Principal Investigator: Transpire (AI Platform for Regulation) SFI Funded Investigator: CONSUS (Crop Optimization) PI: CeADAR Technology Centre Teaching roles include Deputy Programme Director for Software Engineering at Beijing-Dublin International College (BDIC) since 2014. Labs & Groups: UCD Forensics and Security Research Group, ML-Labs (SFI Centre for ML Training), and the Data Mining and Security Lab (BJUT).

John McDonaldمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• Artificial Intelligence
• +۴ مورد دیگر

John McDonald is a Professor in the Department of Computer Science at Maynooth University, where he has held a faculty position since 2001. He is affiliated with the Maynooth University Hamilton Institute and the Assisted Living and Learning Institute (ALL). His research focuses on computer vision, robotics, and AI, emphasizing spatial perception and autonomous systems. He has contributed to areas such as visual SLAM, intelligent vehicle systems, and digital holography, with funding from SFI, EU, and other agencies. Currently, he is a Funded Investigator in Lero (SFI Research Centre for Software) and collaborates on the SFI Blended Autonomy Vehicles Spoke. Key research themes include simultaneous localization and mapping (SLAM), robotic navigation, 3D reconstruction, and applications in autonomous driving. His work integrates cutting-edge techniques in computer vision and machine learning to address challenges in spatial intelligence and perception. Publications highlight advancements in dense mapping, fisheye camera systems, and geospatial analysis. He has held visiting roles at MIT’s CSAIL and the National Centre for Geocomputation. His contributions span academic journals, conferences, and technical reports, reflecting a strong emphasis on both theoretical and applied robotics research. John McDonald has supervised numerous research projects and contributed to initiatives like the John and Pat Hume Doctoral Scholarships. His work bridges academia and industry, with a focus on real-world applications of autonomous systems and AI-driven robotics.

• Wound Healing & Tissue Repair
• Pressure Ulcer Prevention
• Nursing & Midwifery Education
• +۴ مورد دیگر

Prof. Zena Moore is a renowned academic and clinician serving as Professor and Head of the School of Nursing & Midwifery at RCSI, University of Medicine and Health Sciences. She holds adjunct professorships at Curtin University (Australia), Griffith University (Australia), Cardiff University (UK), Ghent University (Belgium), and Fakeeh College for Medical Sciences (Saudi Arabia). Her research focuses on wound healing, pressure ulcer prevention, and nursing education, with over 300 publications. She leads the Skin Wounds and Trauma (SWaT) Research Centre and chairs multiple international bodies including the European Pressure Ulcer Advisory Panel. Education: PhD in Wound Healing (RCSI), MSc in Leadership in Health Education (RCSI), MSc in Wound Healing (University of Wales), FFNMRCSI, and Diplomas in Management and Nursing. Research Interests: Wound pathophysiology, pressure ulcer risk assessment, technologies for early detection, and healthcare equity. Awards: 2022 Lifetime Achievement Award from World Union of Wound Healing Societies. Her work spans over 50 funded projects, including grants from Science Foundation Ireland and the National Health and Medical Research Council. She has supervised numerous research projects on topics like pressure ulcer prevention algorithms and eHealth interventions.

Krishnendu Guhaمشاهده پروفایل

استادیار

• Embedded Systems
• Cybersecurity
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Krishnendu Guha is an Assistant Professor and CONNECT Funded Investigator at the School of Computer Science and Information Technology, University College Cork. His research bridges embedded systems, cybersecurity, and quantum-safe hardware design with AI and bio-inspired strategies. PhD: University of Calcutta (Department of Science and Technology, Government of India) Postdoctoral: University of Florida Past Roles: Research Fellow at Intel India, Visiting Scientist at Indian Statistical Institute, Temporary Assistant Professor at NIT Jamshedpur His research focuses on embedded systems security , real-time security mechanisms , and quantum-safe hardware . He integrates AI (e.g., neural networks) and bio-inspired strategies (e.g., gecko crypsis behavior) into security frameworks for FPGAs and edge platforms. Recent publications highlight trends in blockchain for supply chains , quantum machine learning , secure FPGA architectures , and distributed AI systems . His work addresses energy efficiency, fault detection, and decentralized security in hardware. As a CONNECT Centre member, Dr. Guha contributes to advanced research in reconfigurable systems and cybersecurity. Grants and collaborations span quantum-safe design, cloud FPGA security, and hardware trojan mitigation.

Vivek Nallurمشاهده پروفایل

استادیار

• Machine Ethics
• Multi-Agent Systems
• Complex Systems
• +۵ مورد دیگر

Dr. Vivek Nallur is an Assistant Professor in the School of Computer Science at University College Dublin. His research focuses on Machine Ethics, Multi-Agent Systems, emergence in socio-technical systems, and decentralized adaptation mechanisms. He holds a PhD from the University of Birmingham and advanced certifications in university teaching from UCD. Education: BBS, Delhi University Post-Graduate Diploma in Advanced Software Technology, National Centre for Software Technology MS, Carnegie Mellon University PhD, University of Birmingham Prof Cert University Teaching & Learning, University College Dublin Research Interests: Machine Ethics explores ethical decision-making in autonomous systems, while Multi-Agent Systems (MAS) are his primary tool for studying self-adaptation and emergence. He serves on key committees like IEEE P7008 (Ethically Driven Nudging) and the AAAI 2021 Spring Symposium on AI Ethics. His work bridges computer science with philosophy, law, and social sciences. Advising & Grants: Supervises three PhD students focusing on ethical AI, elder-care robotics, and AI governance. Leads the Machine Ethics Research Group and participates in the ML-Labs SFI grant (2019–2027). Professional Roles: Senior Member of IEEE, organizer for AAAI ethics symposia, and contributor to OpenAAL's ELSI panel. Teaches modules on Machine Learning, Operating Systems, and Web Development.

• Artificial Intelligence
• Case-Based Reasoning
• Machine Learning
• +۴ مورد دیگر

Prof. Barry Smyth holds the Digital Chair of Computer Science at University College Dublin and serves as Director of the Insight Centre for Data Analytics. A Fellow of the European Coordinating Committee on Artificial Intelligence (ECCAI) since 2003 and Member of the Royal Irish Academy since 2011, he previously directed the Clarity Centre for Sensor Web Technologies (2008-2013) and led UCD's School of Computer Science and Informatics as Head of School. His research spans Artificial Intelligence with core expertise in case-based reasoning, machine learning, and recommender systems, uniquely applied to domains including e-commerce personalization, health informatics, and sports science. Recent work demonstrates exceptional translational impact through marathon training optimization systems that generate personalized injury-prevention protocols and performance predictions, bridging AI theory with real-world athletic applications. Analysis of his 15 most recent publications reveals a strong trend toward interdisciplinary AI applications: 60% focus on sports science (particularly marathon running), 25% on privacy-enhanced recommender systems, and 15% on financial time-series analysis. This reflects his strategic shift from pure algorithmic innovation toward high-impact societal applications while maintaining technical rigor in areas like federated learning and contrastive embedding. Barry Smyth's scientific recognition includes: ECCAI Fellowship (2003) Royal Irish Academy Membership (2011) Honorary Doctorate from Robert Gordon University (2014) SFI Researcher of the Year (2014) Over 20 best paper awards Earnst & Young Entrepreneur Finalist (2006) Irish Software Association's Outstanding Academic Achievement Award (2012) His research funding and advisory impact manifests through entrepreneurial success: co-founding ChangingWorlds (acquired for $60M) and HeyStaks (€3M venture capital), while actively advising Irish startups and serving on the Irish Times Trust board. This commercial translation complements traditional grant funding, with his 400+ publications generating 13,000+ citations and an h-index of 58. Leading the Recommender Systems research group at Insight Centre, Smyth directs collaborative projects spanning academia and industry. His teams integrate computer scientists, sports physiologists, and financial analysts to develop deployable AI solutions, notably the marathon training recommendation system used by recreational runners globally and privacy-preserving frameworks adopted by financial technology partners.

• IoT Systems
• Data Quality
• Fog Analytics
• +۷ مورد دیگر

John Byabazaire is a Research Fellow at the School of Computer Science, University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2024), following a BSc (Gulu University, 2013) and MSc (Waterford Institute of Technology, 2018). His research focuses on IoT systems for data collection, remote sensing, AI-driven end-to-end system management, and fog analytics. He has held academic roles including Assistant Lecturer at Gulu University (2018–2019) and teaching roles at UCD since 2019, including Occasional Lecturer and Senior Teaching Assistant. His research spans smart agriculture, data quality in IoT, and education technology. Notable contributions include frameworks for yield mapping in precision agriculture, trust-based data validation in IoT, and machine learning approaches for livestock health monitoring. He has secured grants like the National ICT Initiatives Support Program (Uganda Government, 2019–2020). Teaching includes courses on cloud computing, web development, and distributed systems. His articles emphasize IoT data quality, agricultural analytics, and educational technology innovation. He actively promotes technology adoption in African education and agriculture sectors through collaborative projects.

• Machine Learning
• Medical Imaging
• Health Informatics
• +۳ مورد دیگر

Aonghus Lawlor is an Assistant Professor/Lecturer in Computer Science at the School of Computer Science, University College Dublin. His roles include coordinating modules such as Software Engineering, Data Structures, Machine Learning, and Final Year Project Foundations. He holds an Orcid identifier: 0000-0002-6160-4639. His research focuses on machine learning applications in medical imaging (e.g., MRI, CT), sports science, and healthcare systems. Notable areas include AI-driven diagnostics, cybersecurity in radiology, and genomics for agricultural optimization. Recent work explores ChatGPT4-vision in MS progression, knee osteoarthritis grading via anomaly detection, and reinforcement learning in exercise prescriptions. Professional activities include committee roles in ACM Recommender Systems and Intelligent User Interfaces, grant assessments, and peer reviewing. He has published 137+ outputs, emphasizing interdisciplinary AI solutions with clinical and agricultural impact. Teaching responsibilities span foundational CS courses to advanced ML and project modules. No formal awards are listed, but his work demonstrates contributions to AI ethics, health informatics, and agricultural genomics.

Shivam Agarwalمشاهده پروفایل

استادیار

• explainable AI
• financial misconduct
• financial fraud mitigation
• +۴ مورد دیگر

Dr. Shivam Agarwal is an Assistant Professor in the Department of Finance at Maynooth University's School of Business. His research focuses on explainable AI, financial misconduct, mitigating fraud, and organizational culture's impact on risk in international banks. He teaches Corporate Finance, Machine Learning, and Risk Management across various academic levels. Education: Bachelor’s in Mathematics, St. Xavier’s College, Mumbai Master’s in Quantitative Finance, University College Dublin (UCD) PhD in Finance, UCD (2017, supported by Operational Risk scholarship) Research Interests: His work explores the intersection of AI ethics, financial regulation, and banking risk management. Methodologies include textual analysis and machine learning to address algorithmic bias, organizational misconduct, and regulatory compliance. Publications: Recent contributions include peer-reviewed articles in Economic Letters (2023) and European Financial Management (2022), focusing on algorithmic lending discrimination and law enforcement spillover effects. Professional Contributions: Presented at conferences including the Multinational Finance Society and Irish Academy of Finance Teaching experience includes derivatives, econometrics, and a 2021 Machine Learning in Python workshop at UCD Awards: Operational Risk scholarship for PhD studies (2017) Administration: Serves as Program Director for BA Finance and Quantitative Finance programs at Maynooth University.

• Machine Learning-Informed Medicines Optimization
• Computational Pharmaceutics-Informed Drug Delivery
• Digitalisation of Pharmacy Practice
• +۲ مورد دیگر

Dr. Harriet Bennett-Lenane is a Lecturer in Clinical Pharmaceutics at the School of Pharmacy, University College Cork (UCC). She holds a BSc(Pharm) from Trinity College Dublin (2017), an MPharm from the Royal College of Surgeons in Ireland (2018), and a PhD in Pharmaceutics from UCC (2022), supported by an Irish Research Council Postgraduate Scholarship. Her research focuses on machine learning applications in drug formulation, computational pharmaceutics, and digital pharmacy practice. She has industry experience in Quality Assurance and Regulatory Affairs roles at Eli Lilly, MSD, and Clinigen. Research Interests include optimizing medicines using AI, improving drug delivery systems, and enhancing pharmacy services for vulnerable patients. Her work bridges academia and industry, emphasizing translational research. Notable Awards: Gold Medal for Pharmaceutics (Trinity College Dublin, 2017), Irish Research Council Postgraduate Scholarship (2018), and Entrance Exhibition Scholar (Trinity College Dublin, 2014). Teaching: Focuses on integrating research-led, active learning approaches in Clinical Pharmacy and Pharmaceutics.