جستجوی استاد راهنمای دانشگاهی

Muhammad Bilal Zafarمشاهده پروفایل

استاد

• Human-Centric AI/ML
• Fairness in Machine Learning
• Explainable Artificial Intelligence
• +۳ مورد دیگر

Professor Muhammad Bilal Zafar holds a faculty position at Ruhr University Bochum (RUB), where he heads the Chair of AI and Society within the Research Center for Trustworthy Data Science and Security. He is also a Principal Investigator (PI) at the Cluster of Excellence CASA and a member of the Horst Görtz Institute for IT Security. Previously, he worked as a Senior Applied Scientist at Amazon Web Services and a Research Scientist at Bosch Center for Artificial Intelligence. He completed his PhD at the Max Planck Institute for Software Systems (MPI-SWS) and Saarland University, advised by Krishna P. Gummadi and Manuel Gomez Rodriguez. His research focuses on human-centric AI/ML, emphasizing fairness, explainability, and robustness of AI systems. Key contributions include mechanisms for fair classification, bias detection in algorithms, and trustworthy AI applications. He actively engages in mentoring PhD and Master’s students, with current openings for candidates in Computer Science, Mathematics, and related fields. His work bridges theoretical advancements with practical solutions for ethical AI deployment. Notable collaborations include projects with AWS and Bosch, addressing challenges in algorithmic fairness and AI transparency. His publications span top venues like ACL, KDD, NeurIPS, and WWW, highlighting contributions to both foundational and applied aspects of AI ethics.

Taher Ghalebمشاهده پروفایل

استادیار

• Data-Driven Software Analytics
• Mining Software Repositories
• Continuous Integration and Delivery (CI/CD) – DevOps
• +۳ مورد دیگر

Taher Ghaleb is an Assistant Professor in the Computer Science Department at Trent University, Peterborough, Canada. He completed his Ph.D. at Queen’s University under Prof. Jenny Zou, followed by postdoctoral research at the University of Ottawa and a senior research role at the University of Toronto. His research focuses on applying data science and AI to address software engineering challenges. Education: Ph.D., Queen’s University, Software Evolution & Analytics Lab (SEAL) Postdoctoral Fellow, University of Ottawa Senior Research Position, University of Toronto Research Interests: Data-Driven Software Analytics: Empirical analysis of software development practices. AI in Software Engineering: Leveraging generative AI for code generation and bug detection. Continuous Integration/DevOps: Optimizing CI/CD pipelines for efficiency and reliability. LLM-Oriented Development: Integrating language models into software lifecycle processes. Publications: Taher’s work spans CI/CD practices, test case minimization, and AI-driven software testing. Recent trends emphasize empirical studies on open-source Android apps and flaky test prediction using language models. Awards: No explicit awards listed, but holds multiple U.S. patents related to software engineering and compiler systems. Advising & Grants: Seeks Master’s students and interns to join his team. Teaches courses like Software Design & Modelling (COIS 2240) and Software Engineering Project (COIS 4000) at Trent University. Labs & Teams: Formerly part of the Software Evolution & Analytics Lab (SEAL) at Queen’s University.

Davide Dominoniمشاهده پروفایل

دانشیار

• Urban Ecology
• Circadian Rhythms
• Light Pollution
• +۳ مورد دیگر

Davide Dominoni is a Reader (equivalent to Associate Professor) in Ecology and Environmental Change at the University of Glasgow's School of Biodiversity, One Health and Veterinary Medicine. His research focuses on how urbanization affects wildlife, particularly through light pollution, noise, and habitat alteration, with emphasis on avian circadian rhythms and adaptation mechanisms. Education: PhD in Biology (Max Planck Institute for Ornithology, Germany; 2009-2013) MSc in Nature Conservation (University of Parma, Italy; 2006-2008) BSc in Natural Sciences (University of Milan, Italy; 2001-2005) Research Interests: Dr. Dominoni investigates how artificial light at night disrupts biological rhythms, urban adaptation in birds, and conservation strategies for species in human-modified landscapes. His work integrates field experiments, long-term monitoring, and molecular approaches across projects studying great tits, blue tits, and tawny owls. Current Projects: Ageing in the light: Effects of artificial light on bird ageing Demographic adaptation of passerines along urban gradients Impacts of urbanization on biodiversity patterns Tawny owl ecology in urban areas Variation in circadian rhythms across species Advising & Grants: Supervises six PhD students researching urban ecology topics. Secured funding from NERC, EPSRC, Royal Society, and others for projects on urbanization's ecological impacts and evolutionary consequences.

Sergio Maffeisمشاهده پروفایل

دانشیار

• Computer Security
• Machine Learning
• Programming Languages
• +۳ مورد دیگر

Dr. Sergio Maffeis is an Associate Professor and Senior Lecturer in Computer Security at the Department of Computing, Imperial College London, within the Faculty of Engineering. He leads the Security & Machine Learning Lab and holds affiliations with the Engineering Secure Software Systems and Programming Languages research groups. His research focuses on cyber security, machine learning, formal methods, and programming languages. Maffeis earned his Ph.D. from Imperial College London and an MSc from the University of Pisa, Italy. Research interests include adversarial machine learning, intrusion detection systems, and secure software development. His work bridges theoretical foundations with practical applications, such as detecting Advanced Persistent Threats (APTs) and improving ML model robustness against adversarial attacks. Recent publications highlight advancements in combining machine learning with security, including KnowML for knowledge graph-enhanced ML-NIDS and APIRL for REST API fuzzing. He has supervised numerous PhD students, including Abdullah Aldaihan (Large Language Models for Cyber Threat Detection) and Fahad Alotaibi (Concept Drift in ML-based Security). Grants include EPSRC/GCHQ funding for certified verification of client-side web programs and GCHQ grants for web security and lab infrastructure. His lab collaborates on projects like the Security & Machine Learning Lab, exploring cutting-edge topics in secure AI and network defense.

• Information Systems
• Supply Chain Management
• Digital Transformation
• +۵ مورد دیگر

Federico Pigni serves as Dean of Faculty, Pedagogy, and Research at Grenoble Ecole de Management (GEM), where he holds a full Professorship in Information Systems within the Management of Technology and Strategy department. His academic journey includes a cum laude Business Administration degree and a Ph.D. in Management Information Systems and Supply Chain Management. He has held teaching roles at institutions including Carlo Cattaneo University, the Catholic University of Milan, and Università Commerciale Luigi Bocconi in Milan. Beyond academia, Pigni co-founded Lab4Consulting (2000–2006), a web and software consultancy focused on IT innovation in banking, and completed a post-doctorate at France Télécom R&D in Sophia Antipolis, developing inter-organizational ICT adoption methodologies. His research focuses on strategic applications of information systems, particularly in interorganizational contexts and digital technologies for customer service innovation. Notable projects include the EU-funded EpilepsyPOWER initiative promoting workplace inclusion for epilepsy patients, and the TRIPBAM project leveraging digital data streams for pandemic resilience. His work spans digital transformation frameworks, cybersecurity investments, and big data analytics' impact on competitive advantage. He has authored over 100 publications, including seminal works on IT ambiguity, DevOps frameworks, and supply chain digitalization. Pigni has led collaborative initiatives like the ECOLEAD network supporting SMEs' interorganizational systems and contributed to projects such as the SOLMED solar energy desalination initiative. His expertise bridges academic research with industry practice, emphasizing real-world applications of emerging technologies to drive organizational value creation and societal impact.

Zahid Islamمشاهده پروفایل

استاد

• Data Mining
• Cyber Security
• Machine Learning
• +۸ مورد دیگر

Zahid Islam is a Professor of Computer Science and Associate Dean (Research) at Charles Sturt University's Faculty of Business, Justice and Behavioural Sciences (FoBJBS). He leads the Data Science and Engineering Research Unit (DSERU) and the Cyber Security CRC initiatives. His research focuses on Data Mining, Cyber Security, Privacy-Preserving Techniques, and Machine Learning applications in real-world domains such as healthcare and agriculture. Key roles include: Associate Dean (Research), FoBJBS (since 2023) Director, DSERU (2019–2023) Theme Lead & Academic Lead, Cyber Security CRC (2021–2023) Research interests span: Data Mining: Classification, Clustering, Federated Learning, Missing Value Analysis Cyber Security: Malware Detection, Adversarial Attacks, IoT Security Applications: Healthcare, Agriculture, Smart Farming, Supply Chain Recent work includes developing frameworks for ransomware detection (RADAR dataset), collaborative learning in healthcare (CL3), and privacy-preserving techniques like UD-LDP. His cyber security research has earned the 2021 Cyber Security Researcher of the Year Award (AISA). Key grants include: $5M+ external funding for cybersecurity projects AI for Mental Health Support (2025) Adaptive Federated Learning Grant (2024) Labs/Groups: Data Mining Research Group (DaMRG), Machine Vision and Digital Health (MaViDH), Cyber Security Research Group (CSRG)

Peter Bloodsworthمشاهده پروفایل

مدرس

• Multi-agent Systems
• Cloud Computing
• Distributed Computing
• +۳ مورد دیگر

Dr. Peter Bloodsworth is a Lecturer and Professional Masters Programme Project Supervisor in the Department of Computer Science at the University of Oxford. He holds a PhD in Multi-agent Systems from Oxford Brookes University. His research focuses on multi-agent systems, cloud computing, distributed computing, and artificial intelligence, with applications in medical research and robotics. Dr. Bloodsworth has over a decade of academic experience, including a role as a Foreign Professor at the National University of Sciences and Technology (NUST) in Islamabad, Pakistan (2011–2016), and prior work as a Research Fellow at the University of the West of England (UWE), Bristol. He has contributed to major European projects such as the FP7-funded neuGRID project, where he acted as a workpackage leader and User Manager. His research emphasizes applying semantic technologies and multi-agent systems to solve complex problems, including medical ontology integration and grid computing in healthcare environments. Dr. Bloodsworth is a full member of the IEEE and a Chartered Member of the British Computing Society (BCS), reflecting his commitment to professional standards in computing. His recent research themes include deploying multi-agent systems for scalable cloud solutions, robotic control, and managing cloud resources through agent-based frameworks. He has over 30 publications in international journals and conferences, with notable work on cloud marketplaces, elastic multi-agent systems, and neuroimaging analysis using grid computing.

• Service-oriented Computing
• Web Services
• Workflow Technology
• +۷ مورد دیگر

Jun Yan is a Professor at the University of Wollongong's School of Computing and Information Technology within the Faculty of Engineering and Information Sciences. His roles include academic leadership and research supervision, with active involvement in committees like the Student Academic Experience Sub-Committee and Quality Assurance Review Group. Current research focuses on service-oriented computing, workflow technology, adaptive process management, and AI-driven systems. His work intersects with IoT, UAV systems, federated learning, and multi-agent reinforcement learning. Research interests span service-oriented software engineering, decentralized workflow management, and cybersecurity challenges in autonomous systems. Notable projects include an ARC-funded initiative on robust defenses against adversarial ML for UAV systems (2025–2027). He supervises Masters/PhD projects on topics like diffusion model-based MRI, graph prompt learning, and industrial defect detection. His publications from 2023–2025 emphasize scalable multi-agent systems, federated learning with non-IID data, and UAV applications in intelligent transportation. Key areas of contribution include trust models for e-commerce, privacy-preserving cloud computing, and fault-tolerant service architectures.

Florentin Rochetمشاهده پروفایل

استادیار

• Anonymous Communication
• Network Security
• Transport Protocols
• +۵ مورد دیگر

Florentin Rochet is an Assistant Professor at the University of Namur's Faculty of Computer Science. His research focuses on anonymous communication , network security , and encrypted transport protocols , with a particular emphasis on improving privacy-enhancing technologies and protocol design. He holds a PhD in Applied Cryptography and has contributed to projects like TCPLS (TCP/TLS integration) and CLAPS (Tor path selection). Key academic milestones include joining UNamur in 2022 as an Assistant Professor, completing a postdoc at the University of Edinburgh (2021), and serving on program committees for Usenix Security, ACM CCS, and PoPETs. He has received the Usenix Security Noteworthy Reviewer Award (2023) and the 2020 Alan Berman Research Publication Award. His research spans flexible anonymous networks , secure transport protocols , and authentication technologies , with notable work on improving Tor's resilience against attacks through location-aware path selection and enhancing TLS/TCP integration for modern networks. He also leads a research group exploring eBPF security and WebAssembly runtime protections. Teaching responsibilities include computer security and privacy courses, with a 6-year teaching assistant position involving bachelor's/master's instruction and PhD supervision. His lab focuses on applied cybersecurity, network protocol innovation, and privacy-preserving systems design.

• Cybersecurity
• Computer Security
• Hardware Security
• +۶ مورد دیگر

Herbert Bos is a Full Professor at Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department), the Network Institute, and the Systems and Network Security group. His research focuses on hardware and software security, including transient execution attacks, memory exploitation, and vulnerability detection. He has authored over 229 research outputs, including influential papers on Spectre mitigation, Rowhammer attacks, and fuzzing techniques. Notable contributions include frameworks like PANDAcap and BinRec. Bos teaches courses such as Binary and Malware Analysis and Operating Systems. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure security. Education details are not explicitly provided, but his academic titles (prof. dr. ir.) suggest advanced degrees in computer science and engineering. Ancillary activities include roles as an author for Pearson textbooks and a member of the Kiesraad in The Hague. Research interests emphasize cutting-edge hardware vulnerabilities (e.g., Spectre, Rowhammer), memory safety, and automated testing (fuzzing). Recent work highlights practical defenses against transient data leaks (Phantom Trails) and data-only attacks. Collaborations span international institutions, reflecting his global influence in cybersecurity. Publications since 2016 showcase advancements in CPU architecture security, kernel exploitation, and embedded device defenses. His datasets (e.g., PANDAcap SSH Honeypot) provide foundational resources for the security community. Grants and lab affiliations are inferred through his research outputs and teaching roles.

Wei Aiمشاهده پروفایل

استادیار

• Data Science for Social Good
• Machine Learning
• Causal Inference
• +۴ مورد دیگر

Wei Ai is an Assistant Professor at the University of Maryland, affiliated with the College of Information (INFO) and the Institute for Advanced Computer Studies (UMIACS). His research focuses on data science for social good (DSSG), integrating machine learning, causal inference, and experimental design to address societal challenges in education, virtual collaboration, and quantum computing. He leads the Center for Educational Data Science and Innovation (EDSI) and has secured grants from the NSF, Gates Foundation, and Walton Family Foundation for projects like M-Powering Teachers and classroom quality assessment tools. Education: PhD in Information from the University of Michigan (advised by Qiaozhu Mei). Previous academic roles include teaching at the University of Michigan and Peking University in courses like Data Mining and Information Retrieval. Research Interests: Machine Learning and Causal Inference, AI for Education, Virtual Teams and Social Identity, Large Language Models for Social Applications. He has published in venues such as PNAS, Management Science, ACL, and the Web Conference. Grants: Major awards include a NSF grant on middle-grade math instruction analysis (with Min Sun) and a Gates Foundation grant for classroom dataset development (with Jing Liu). Labs/Teams: CLIP Lab member, collaborating on interdisciplinary projects with UMIACS and the Joint Quantum Institute. Prospective students: Open to mentoring PhD students through INFO and Computer Science programs. Actively supervises current students in education technology and quantum computing domains.

• Bioinformatics
• Protein Structure Prediction
• Machine Learning
• +۳ مورد دیگر

Gianluca Pollastri is an Associate Professor in the School of Computer Science at University College Dublin (UCD). He leads a research group focused on machine learning applications in bioinformatics, particularly protein structure prediction and analysis. His academic roles include Associate Professor since 2016, Senior Lecturer from 2008, and Lecturer from 2003. He earned an MSc from the University of Florence and a PhD from the University of California, Irvine. His research integrates deep learning and neural networks to address challenges in protein subcellular localization, secondary structure prediction, and intrinsically disordered regions. Key tools developed include SCLpred, PaleAle, Porter, and PUNCH2. He has secured grants from Science Foundation Ireland, the Health Research Board, and UCD. Pollastri’s work emphasizes rigorous validation of machine learning methods in biology, as outlined in the DOME framework. His lab has produced over 100 peer-reviewed articles, with recent focus on leveraging pre-trained language models (PLMs) for protein analysis. Education: MSc, University of Florence PhD, University of California, Irvine Awards: Best M.Sc. Thesis in Artificial Intelligence (1999) Best Student Project in Artificial Intelligence (1997) His teaching includes modules on Bioinformatics, Connectionist Computing, and Programming. He coordinates research collaborations and maintains a lab with postdoctoral fellows and graduate students.

• Circular Economy
• Sustainable Development
• Sustainable Manufacturing
• +۴ مورد دیگر

Pezhman Ghadimi is an Assistant Professor of Manufacturing Systems at the School of Mechanical and Materials Engineering, University College Dublin (UCD). He holds a PhD in Industrial Engineering and Operations Management from the University of Limerick. His research focuses on Circular Economy, Sustainable Manufacturing, and Operations Research, with notable contributions to supply chain resilience, waste management, and global trade dynamics. He has secured significant grants, including a €2.56m Marie Curie Doctoral Network (iCircular3) for circular economy research. Education: BEng (Mazandaran University of Science & Tech, Iran), MEng (UTM Malaysia), PhD (University of Limerick), and a Professional Diploma in University Teaching & Learning (UCD). Research Interests: Circular Economy, Sustainable Development, Sustainable Supply Chains, Data Analytics, and Risk Analysis. He emphasizes applying these themes to global trade networks, medical device supply chains, and EV battery systems. Key Awards: Second Best PhD Student Award in Engineering (2015) by the Iranian Association for Postgraduate Students in Europe and Russia. He actively reviews for journals like International Journal of Production Research and Journal of Cleaner Production . Grants & Projects: Over 14 grants, including leadership in the iCircular3 project and contributions to CircularDev initiatives. His work addresses disruptions in global supply chains, particularly under pandemic conditions and geopolitical shifts. Labs/Teams: Leads research groups focused on circular economy strategies, sustainable manufacturing systems, and Industry 4.0 integration in supply chains. Collaborates internationally on projects involving China, the EU, and Ireland.

• Multi-Agent Systems
• Agent-Oriented Software Engineering
• Hypermedia Multi-Agent Systems
• +۷ مورد دیگر

Rem Collier is an Associate Professor in the School of Computer Science at University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2001) and has held academic roles including Assistant Lecturer (2004), College Lecturer (2005–2018), and his current position since 2018. His research focuses on Multi-Agent Systems (MAS), Agent-Oriented Software Engineering (AOSE), Hypermedia MAS, Digital Twins, and applications in smart agriculture and urban simulation. He leads the CONSUS project (2022–2024) and collaborates on CAMEO (2021–2024). Education: BSc (Pure/Applied Mathematics, University of Bristol, 1994), MSc (Computation, UMIST, 1995), MPhil (UMIST, 1996), PhD (UCD, 2001). Research interests include Agent Factory Framework, ASTRA programming language, and integrating MAS with microservices. Notable achievements include the CIA System Innovation Award 2003 (ACCESS architecture) and Best Paper Awards at EMAS2020 and Mobile Learning 2006. His work spans over 150 peer-reviewed publications and grants such as HOTAIR (2004–2005) and SIFT (2008–2011). Teaching includes modules on Multi-Agent Systems, Distributed Systems, and Security. He has coordinated courses at UCD and the Joint UCD-Fudan program in Beijing and Sri Lanka. Labs/Teams: Active in Hypermedia MAS Simulation, collaborating on projects like CONSUS and CAMEO, emphasizing smart agriculture and distributed knowledge graphs.

Markus Nüttgensمشاهده پروفایل

استاد

• Information Systems
• Business Process Management
• Digital Transformation
• +۴ مورد دیگر

Prof. Markus Nüttgens is a Professor at the University of Hamburg Business School's Department of Information Systems. His research focuses on digital transformation, business process management, sustainability management, and blockchain applications in Industry 4.0. He leads projects like smartTCS and EMOTEC , developing platforms for customer integration in technical services and mobile assistance systems. Notable contributions include frameworks for data-driven sustainability management, semantic verification in process modeling, and standards like DIN SPEC 33451 for service catalogs. His work bridges theory and practice, emphasizing hybrid value chain strategies, mobile service support systems, and process audits. He has pioneered methodologies for service engineering and smart service ecosystems, with a particular focus on empowering technical customer services through IT innovations. Prof. Nüttgens has contributed to over 50 peer-reviewed publications and actively participates in academic conferences, editing volumes on service modeling and process auditing. His research portfolio spans IT governance, cybersecurity awareness in enterprises, and the diffusion of Web 2.0 in healthcare and SME networks. He collaborates with industry partners to design productivity-enhancing solutions for hybrid service systems, ensuring alignment between technological advancements and organizational efficiency.