Find Academic Supervisors

Danny WeynsView profile

Professor

• Self-Adaptive Systems
• Software Engineering
• Cyber-Physical Systems
• +3 more

Professor Danny Weyns is a faculty member at the Department of Computer Science, Katholieke Universiteit Leuven (KU Leuven), and part-time affiliated with Linnaeus University, Sweden. His research focuses on self-adaptive systems, decentralized architectures, and cyber-physical systems, with applications in IoT and multi-agent systems. He has organized numerous international workshops and conferences, including VARSA, SOAR, and AOSE. Weyns earned his PhD from KU Leuven in 2006 and was a postdoc fellow funded by Flanders. His work emphasizes formal methods and runtime assurance for adaptive systems, with notable contributions to frameworks like ActivFORMS and tools for model-based simulation. Research interests include: self-adaptation mechanisms, control theory integration, and decentralized decision-making in complex systems. Recent publications explore machine learning applications in adaptation, empirical software architecture studies, and self-evolving systems. He has received recognition, including the Best Student Paper Award at SEAMS 2022.

• Mobile Software Engineering
• Intelligent Software Engineering
• Software Security
• +6 more

Xiaoyu Sun is a Lecturer in the School of Computing at Australian National University (ANU), specializing in Software Engineering with a focus on Mobile Software Engineering and Intelligent Software Engineering. She holds a PhD from Monash University (2023) and a Bachelor's degree in Computer Science from Beijing Normal University (2016). Her research emphasizes applying static code analysis, dynamic testing, and NLP techniques to enhance software security and reliability, particularly in Android systems. Current projects include tools for detecting compatibility issues and privacy leaks in mobile apps. Her research interests span code generation frameworks (e.g., A^3-CodGen), security management in open-source projects, and AI-enhanced software development practices. Collaborations with tech giants like Bytedance and Alibaba highlight her industry engagement. Xiaoyu is Co-Investigator in the Tech4HSE project (2025-2027), developing AI-based monitoring systems for workspace safety. She has published in top venues including ICSE, ASE, and IEEE Transactions on Software Engineering. Her work bridges academia and industry, addressing challenges in mobile app security, code reuse efficiency, and developer toolchain innovation. Ongoing efforts focus on AI-driven solutions for software engineering tasks and fostering transparent privacy practices in open-source AI applications.

Jie ZhangView profile

Lecturer

• Software Engineering
• Machine Learning Trustworthiness
• Fairness Testing
• +5 more

Dr. Jie Zhang is a Lecturer in Computer Science (Software Engineering) at King's College London, Department of Informatics. Her research bridges software engineering and artificial intelligence, focusing on enhancing trustworthiness in both fields. She obtained her PhD in Computer Science from Peking University (2018) and was a Research Fellow at University College London (2019–2022). She leads the King's Trusted Autonomous Systems Hub and contributes to the Sustainability, Finance, Health, and Security research hubs. Her work addresses fairness in AI systems, code generation efficiency, and vulnerability detection. Education : PhD in Computer Science, Peking University (2015–2018) Visiting Student, University College London (2016–2016) Intern, Microsoft Research Asia (2017) Research Interests : AI for Software Engineering: Code generation, automated testing, and program repair using LLMs. SE for AI: Fairness testing, bias mitigation, and model validation in machine learning systems. Trustworthiness of autonomous systems and cybersecurity applications. Recent Trends in Articles : Focus on fairness in autonomous systems, efficiency of generated code (EFFIBENCH), and empirical analysis of ChatGPT's non-determinism in code generation. Her work addresses intersectional fairness, stealthy backdoor attacks in code models, and benchmarking AI-generated outputs. Awards : 2025 ACM Sigsoft Early Career Award (for pioneering SE for AI contributions) 2022 IEEE TSE Best Paper Award Royal Society International Exchange Grant (2024) 2023 Chinese Female Young Scholars in AI+X Grants & Projects : ITEA GENIUS (2025–2028): Trustworthy autonomous systems ITEA GreenCode (2024–2027): Sustainable software engineering Labs/Teams : Active in King's Cybersecurity Centre, Software Systems Group, and Computing Education Research Centre (CERC).

• Cybersecurity
• Machine Learning
• Digital Networks
• +7 more

Yasser Morgan is a Teaching Professor at the Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology, specializing in the Department of Systems and Enterprises. He can be contacted at ymorgan@stevens.edu. PhD in Computer Science from Carleton University (2005) MS in Computer Science from ISSR, Cairo University (1997) His research spans multiple domains including Digital Networks (cellular and vehicular), Machine Learning with a focus on Artificial Neural Networks (ANN), and Cybersecurity solutions. He has pioneered standards for vehicular communications (WAVE) through IEEE-802.11p and 3GPP collaborations, impacting connected vehicle systems. His recent work focuses on cybersecurity frameworks, resource allocation in energy-efficient networks, and honeypot research. The 10 most recent publications highlight expertise in Cybersecurity (honeypot systems, passive attacks), Wireless Communications (UAVs, LTE, vehicular networks), and Machine Learning (real-time recognition systems). Key subfields include network coding, cognitive radio, energy harvesting, and secure communication protocols. Canadian Advanced Technologies Association Award 'Wilfrid Laurier University, Lazaridis School of Business Public Sector Leadership' for exceptional contribution to Public Safety Dr. Morgan has secured over $4.5 million in grants from NSERC, DRDC, and government agencies, with notable inventions including the international patent A Method and System for Cooperative Stochastic Positioning in a Mobile Environment (PCT No. EP2598913 A4). His consulting services in cybersecurity and teaching portfolio (SSW 540, SSW 567) reflect his interdisciplinary expertise in systems engineering and information security.

Hironori WashizakiView profile

Professor

• Systems Engineering
• Software Engineering
• Machine Learning
• +3 more

Hironori Washizaki is a Professor at Waseda University 's School of Fundamental Science and Engineering and a Visiting Professor at the National Institute of Informatics. He serves as IEEE Computer Society 2025 President and has led initiatives in software engineering, ML design patterns, and IoT systems. His work bridges academia and industry through roles at SYSTEM INFORMATION CO.,LTD. and eXmotion Co., LTD. Research Interests: His work spans software engineering, quality assurance, ML/IoT design patterns, and education innovation. He leads the SmartSE professional education program and standardizes software engineering bodies of knowledge through ISO/IEC/JTC1/SC7/WG20 . Scientific Awards: Golden Core Member (IEEE CS) Spirit of Computer Society Award KDDI Foundation Award Science and Technology Award, MEXT Best Paper Awards at ICSE, CSEE&T, and IWESEP Leadership & Grants: He has secured major grants (JSPS, MEXT) and held editorial roles at IEEE Transactions on Emerging Topics in Computing, IJSEKE, and IEICE journals. As IEEE CS Japan Chapter Chair and SEMAT Japan Chapter Chair , he fosters international collaborations. Labs & Teams: He leads the Global Software Engineering Laboratory at Waseda, focusing on traceability, reuse, and quality. This lab drives projects like ProMeTA (program metamodel taxonomy) and Trace ANY (software maintenance metrics).

Hunter N. MoseleyView profile

Professor

• Bioinformatics
• Computational Biology
• Metabolomics
• +12 more

Hunter N. Moseley is a Professor in the Department of Molecular and Cellular Biochemistry at the University of Kentucky. He maintains an active research laboratory focused on bioinformatics and computational biology, with a strong emphasis on metabolomics and systems biochemistry. His work bridges computational methodology development with biological applications, particularly in data integration and analysis. Education: B.A. in Chemistry, Computer Science, and Mathematics, Huntingdon College (1992) Ph.D. in Biochemistry, University of Alabama at Birmingham (1998) His research interests center on developing computational methods for analyzing biological and biophysical data, particularly through integration of omics-level datasets and leveraging public scientific databases. Key areas include metabolomics, systems biochemistry, structural biology, and data harmonization. His laboratory has produced numerous software tools for data analysis and database integration. The recent publications highlight a strong trend in developing computational frameworks for metabolite pathway prediction, database harmonization (particularly KEGG, Reactome, MetaCyc), and FAIR data principles. There is a consistent focus on methodological rigor, data quality, and software development for metabolomics data analysis, including tools for GPU utilization tracking, academic publication tracking, and metabolic database access. Dr. Moseley has mentored numerous students and collaborators who appear as co-authors on his publications. His lab has secured research support that enables collaborative work across disciplines, including environmental health, cancer research, and cardiovascular disease. He leads the Moseley Bioinformatics Lab, which develops and maintains several open-source software packages for the scientific community.

• Mechanical Engineering
• Manufacturing Engineering
• Finite Element Analysis
• +5 more

Ambarish Kulkarni is an Associate Professor at Swinburne University of Technology's School of Engineering, specializing in mechanical design, virtual/augmented reality (VR/AR), and electric vehicle (EV) technologies. His research focuses on product design, EV drivetrains, battery packaging, medical devices, and bushfire shelter design. He holds a PhD from Swinburne, a Master's from Queensland University of Technology, and a Bachelor's from the Indian Institute of Industrial Engineering. Research interests span finite element analysis, bio-mechanical modeling, and Industry 4.0 applications. Notable projects include Bombardier Tram development, therapeutic sleep systems, and smart manufacturing frameworks. He has supervised over 20 HDR students on topics ranging from predictive maintenance to extended reality in education. Awards include the Teaching Excellence Award (2016) and Premier's Design Awards for medical and safety innovations. He is a Fellow of the Institution of Engineers (Australia) and actively involved in professional bodies like SAE International. Grants funded projects on hydrogen generators, smart manufacturing systems, and graphene supercapacitors. His work bridges academia and industry through collaborations with firms like Bambach Wires and iMOVE Australia.

Qingping YangView profile

Associate Professor

• Measurement Systems
• Quality Engineering
• Smart Technologies
• +5 more

Dr. Qingping Yang is a Reader (Associate Professor) in the Department of Mechanical and Aerospace Engineering at Brunel University London, affiliated with the College of Engineering, Design and Physical Sciences. He directs the Brunel Quality Engineering and Smart Technology (QUEST) and Robotics and Automation Research Groups, focusing on sensor systems, AI, and industrial metrology. Education: PhD in Engineering, Brunel University London (1992) BEng in Instrumentation and Measurement Technology, Chengdu Aeronautical Polytechnic (1983) Research Interests: Dr. Yang integrates measurement systems, quality engineering, and smart technologies (AI/robotics). His work spans industrial metrology, IoT-driven manufacturing optimization, renewable energy forecasting, medical diagnostics, and autonomous inspection systems. Key methodologies include machine learning, Bayesian risk modeling, and non-destructive evaluation. Publication Trends: Recent articles emphasize AI applications in manufacturing (defect detection, robotic path planning), IoT-based monitoring (3D printing, building safety), and healthcare analytics (COVID-19 diagnosis). Methodological innovations include graph theory optimization, computer vision, and ontology-driven quality frameworks. Awards: Three Brunel University Performance Bonuses Marquis Who's Who in the World (1998) Marquis Who's Who in Science and Engineering (2000) Advising & Grants: Supervised 39+ PhD/MPhil students (23 as primary supervisor). Secured £2.7M as PI and £1.2M as Co-I across 18 projects (EU/UK industry/government-funded). Current PhD projects include AI for non-destructive testing and sustainable manufacturing. Leadership: Heads QUEST and Robotics research groups. Former EU research coordinator and MSc program director. Editor-in-Chief of the International Journal of Metrology and Quality Engineering .

• Digital Rights Management
• Multimedia Content Management
• Healthcare Information Systems
• +6 more

Jaime Delgado is a prominent researcher with over three decades of contributions to digital rights management, healthcare information systems, and security and privacy in eHealth. With an extensive publication record spanning from 1994 to 2025, Delgado has established themselves as a leading expert at the intersection of computer science and healthcare, developing practical frameworks that enhance security, privacy, and interoperability in medical systems. Delgado's research spans multiple critical domains: Digital Rights Management and Multimedia Content Security Healthcare Information Systems and eHealth Applications Security and Privacy in Medical Data Management Ontologies and Semantic Web Technologies for Healthcare Genomic Information Systems and FAIR Data Principles Trustworthy Media Systems and Provenance Tracking Analysis of recent publications (2021-2025) reveals a strategic shift toward healthcare applications, particularly focusing on security requirements for Internet of Medical Things (IoMT), privacy-enhancing techniques for medical data, and genomic information systems. Delgado's work demonstrates consistent development of practical architectures addressing real-world security challenges in healthcare settings, with increasing collaboration with medical professionals and participation in European health informatics initiatives like the MedSecurance Project. Delgado has received recognition for contributions to standardization efforts, particularly in developing frameworks for media trustworthiness and international standards for assessing trust in digital media. Their work on the JPEG Privacy and Security framework has significantly influenced industry practices. Through extensive collaboration with researchers like Silvia Llorente (43 joint publications), Eva Rodríguez (29 publications), and Rubén Tous (26 publications), Delgado has built a strong research network across European institutions. Their work consistently combines theoretical framework development with practical implementation considerations, addressing the critical balance between security requirements and clinical workflow usability. Delgado's laboratory work centers on developing secure frameworks for medical data management, with recent emphasis on genomic information systems, provenance tracking in eHealth, and security requirements for medical IoT devices. Their research group actively participates in European health informatics initiatives and contributes to international standards development, maintaining exceptional productivity with 4-7 publications annually in recent years.

Azim AhmadzadehView profile

Assistant Professor

• Machine Learning
• Space Weather Forecasting
• Solar Physics
• +4 more

Azim Ahmadzadeh serves as an Assistant Professor in the Department of Computer Science at the University of Missouri–St. Louis within the College of Arts and Sciences. Holding a Ph.D. in Computer Science from Georgia State University (2021), he maintains office hours in 329 ESH on Mondays and Wednesdays from 5:00-6:30 PM via Zoom or in person, with flexible scheduling options for students. Education: Ph.D. Computer Science, Georgia State University, 2021 Dr. Ahmadzadeh's research pioneers machine learning applications for space weather forecasting, specializing in solar flare prediction through innovative time series analysis and computer vision techniques. His work systematically addresses critical challenges including extreme class imbalance in solar datasets, temporal coherence requirements, and data scarcity through novel algorithmic developments. Key contributions include advanced similarity metrics for multivariate time series, synthetic data generation frameworks, and anomaly detection systems specifically designed for solar observations. His publication trajectory (2022-2025) reveals a strategic focus on operationalizing machine learning for heliophysics, with significant output in solar filament detection systems (Elements, MAGFILO), time series analysis innovations (Multiscale Dubuc, Ts-miou), and practical guides for scientific data annotation. This work bridges theoretical machine learning with real-world space weather forecasting needs, evidenced by roadmap documents for SEP monitoring and solar research cyberinfrastructure. Dr. Ahmadzadeh actively develops open resources for the solar physics community including manually annotated datasets, standardized annotation protocols, and ML-ready data pipelines. His research program demonstrates strong interdisciplinary collaboration potential with space agencies and observatories, particularly through contributions to white papers on solar research infrastructure and operational forecasting requirements.

• HPV-associated cancers
• Molecular virology
• Machine learning
• +6 more

Sara Arroyo Muhr is a Senior Research Specialist and Docent at the Karolinska Institutet , affiliated with the Department of Clinical Science, Intervention and Technology and the Center for Cervical Cancer Elimination . She serves as Scientific Lead at the International HPV Reference Center and coordinates global HPV diagnostic initiatives through the Global HPV LabNet . Education : PhD from Karolinska Institutet (2016), Docent (2025) Her research spans HPV-associated cancers , molecular virology, machine learning applications in cancer prevention, and microbiome interactions in cervical carcinogenesis. She leads Sweden’s cervical cancer elimination project and self-sampling programs in conflict zones like Ukraine. Her work integrates next-generation sequencing and bioinformatics to address diagnostic challenges in HPV testing. Recent publications highlight advancements in HPV genotyping software (HPV-KITE) , quality assurance for HPV DNA testing, microbiome analysis in cervical and anal cancers, and vaccine immunogenicity studies. Key collaborations include international proficiency trials for HPV diagnostics and large-scale registry-based cervical screening research. Teaching roles include lecturing in molecular diagnostics , genomics , and antiviral drugs at undergraduate and graduate levels, alongside PBL tutoring and supervision of five PhD students. She also develops online educational resources for the International HPV Reference Center.

Sara NourazariView profile

Associate Professor

• Operations Research
• Data Science
• Machine Learning
• +4 more

Sara Nourazari is an Associate Professor in the Department of Health Care Management within the College of Health & Human Services at California State University, Long Beach. She joined the department as an assistant professor in fall 2016 and has since been promoted to tenured Associate Professor, specializing in applying analytical methodologies to healthcare system optimization. Education: Ph.D. in Industrial Engineering with minor in Operations Research from Northeastern University, Boston, MA M.S. in Electrical Engineering B.S. in Electrical Engineering Research Focus: Dr. Nourazari's work centers on harnessing data science and operations research to enhance healthcare system efficiency through intelligent decision support. Her research specifically addresses system behavior patterns using machine learning for emergency department payment forecasting and adaptive queue management models for real-time access control. She investigates critical aspects of robustness, scalability, and sustainability in healthcare decision systems while accounting for uncertainty, variability, and human factors inherent in clinical environments. Teaching Expertise: As the department's primary faculty for operations management, she instructs HCA 320: Operations Management in Health Administration HCA 450: Quality Assurance in Health Care HCA 535: Quantitative Methods for Healthcare Administration

• Artificial Intelligence
• Machine Learning
• Industrial Machine Vision
• +7 more

Dr. Anas Abdelrazeq serves as Chief Engineer at the Chair of Intelligence in Quality Sensing , RWTH Aachen University. His work focuses on AI integration in manufacturing, machine vision technologies, and quality management innovation. Current research spans generative AI , reinforcement learning , and data quality optimization Key projects include AI-driven product development and MetaVision industrial metaverse studies Recent publications address: Smart measurement strategies through machine learning Generative AI for non-destructive testing Curiosity-driven AI for job shop scheduling Machine vision applications in SMEs He contributes to the Cluster of Excellence Internet of Production and leads initiatives in 3D metrology and AI in Manufacturing as part of RWTH AI Week. The chair actively engages in developing digital process platforms for future construction sites and industrial applications.

Mario Marques FreireView profile

Professor

• Computer Systems and Networks
• Cloud Computing
• Computer Security and Privacy
• +3 more

Mário Marques Freire is a Full Professor at the University of Beira Interior, where he serves as President of the Faculty of Engineering and Professor in the Department of Computer Science. He is also a Senior Researcher at Instituto de Telecomunicações, leading the Secure and Intelligent Networked Software Systems Lab. His academic qualifications include a Dr. habil. in Computer Science (2007) and Ph.D. in Electrical Engineering (2000) from the University of Beira Interior, complemented by an M.Sc. in Systems and Automation and B.Sc. in Electrical Engineering from the University of Coimbra. Freire's research spans Computer Systems and Networks, with specific expertise in Cloud Systems, Computer Networking, Security & Privacy, and AI applications. His work focuses on infrastructure virtualization, encrypted traffic classification, DDoS attack detection, and malware analysis. Recent publications demonstrate strong emphasis on cloud security, AI-enhanced defect prediction, and IoT security frameworks. He has received several scientific awards including multiple Conference Best Paper Awards and an ACM Certificate of Appreciation for his long-term contributions. Freire has supervised over 35 graduate students (10 PhD graduates) and led numerous research projects such as 'Towards the assurance of SECURity by dESIGN of the Internet of Things' (FCT/COMPETE/FEDER) and 'Cloud Computing Competence Center'. At the University of Beira Interior, Freire has held significant administrative roles including Vice-Rector (2020-2021), Director of Computer Science Services (2009-2013), and multiple terms as President of the Faculty of Engineering. He leads the Network Applications and Services research group at Instituto de Telecomunicações, focusing on secure networked systems.

• Construction Safety
• Mental Health in Construction
• Gender Diversity in Construction
• +5 more

Associate Professor Riza Yosia Sunindijo serves as Deputy Head of School (Research) at UNSW School of Built Environment, where he has been a full-time academic since 2013 after joining as sessional staff in 2009. A top 2% scientist according to Stanford University, he holds PhD and Master's degrees from UNSW and Petra Christian University, along with professional memberships in the Australian Institute of Building (MAIB) and Chartered Institute of Building (MCIOB). His career spans significant administrative roles including Undergraduate Coordinator (2014-2017) and Director of Postgraduate Research (2018-2020). Sunindijo's research focuses on construction safety, mental health, gender diversity, and disaster management—particularly in developing countries. His work examines psychosocial hazards, women's empowerment in construction, and health/safety integration in procurement processes. He has developed frameworks for positive mental health in construction workers and safety climate improvement in Indonesian contexts. Analysis of his recent publications reveals strong trends in construction mental health (35% of output), gender diversity (25%), and safety culture (20%), with growing emphasis on AI applications and pandemic-related stressors. His work spans global contexts but maintains strong focus on Indonesia and developing nations. Research, Development and Technology Professional Excellence award (AIB NSW Chapter, 2025) Social Impact Award for PsycheGuard project (UNSW Founders, 2024) Exemplary Teaching Practice Award (UNSW, 2022) Australian Institute of Building Teaching Excellence Award (2019) Built Environment Staff Excellence Award (2016, 2014) As Director of Postgraduate Research (2018-2020), Sunindijo supervised numerous HDR candidates while securing major grants including a $2.3M Department of Prime Minister and Cabinet project on women in construction and $140k from NSW WHS Centre for small business safety frameworks. His current research includes the PsycheGuard mental health initiative and Indigenous procurement policy evaluations. Through UNSW-Indonesia collaborations and fieldwork in Jakarta, Sunindijo leads projects addressing hospital disaster preparedness and construction safety in developing economies, maintaining strong industry connections through organizations like the Australian Institute of Building.