جست‌وجوی استاد و پژوهشگر

• Software Engineering
• Graph Transformation Systems
• Model-Based Development
• +۵ مورد دیگر

Reiko Heckel is a Professor of Software Engineering at the University of Leicester, serving as Director of Postgraduate Teaching for Computing degrees and Data Analytics Lead at the Leicester Innovation Hub. She previously held academic roles at the Technical Universities of Dresden and Berlin before joining Leicester in 2004. Her research focuses on graph transformation systems, model-based development, stochastic modeling, and formal methods in software engineering. She earned her PhD (Dr.-Ing.) in Computer Science from TU Berlin in 1998. Her research interests span software engineering pedagogy, formal specification techniques, and applications of graph grammars in system modeling. Recent work explores stochastic graph transformations for social networks, transparency engineering in AI systems, and blockchain-based smart contract frameworks. Her contributions bridge theoretical foundations with practical applications in cybersecurity, data integration, and human-centric systems design. Key contributions include advancements in automated test case generation via graph transformations, visual contracts for software reverse engineering, and formal methods for complex system analysis. Her work frequently intersects with industry through collaborations via the Leicester Innovation Hub, emphasizing data analytics and technology transfer. Education: MSc Computer Science, Technical University of Dresden PhD (Dr.-Ing.), Computer Science, TU Berlin (1998) Leadership Roles: Head of Department (2014-2018) Director of Postgraduate Teaching (Ongoing) Research Themes: Model-Based Development Stochastic Systems Analysis Graph Neural Networks Trustworthy AI Her publications reflect a focus on formal methods, with recent trends in applying graph transformation techniques to social network modeling, blockchain smart contracts, and educational pedagogy.

• Computer Learning
• Fuzzy Sets and Systems
• Decision Support Systems
• +۳ مورد دیگر

Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.

• Virology
• Molecular Pathology
• Host-Pathogen Interactions
• +۵ مورد دیگر

Dr. Richard Y. Zhao is a tenured Professor in the Department of Pathology and Microbiology-Immunology at the University of Maryland School of Medicine. His research combines molecular biology, fission yeast genetics, mammalian biology, and virology to study virus-host interactions, particularly for HIV and Zika virus. He previously held academic positions at Northwestern University and Columbia University and has contributed to over 120 peer-reviewed articles. B.S., China Oceanography University (1981) M.S., Oregon State University (1995) Ph.D., Oregon State University (1991) Postdoctoral Training, Columbia University (1991-1992) Dr. Zhao's research focuses on: Virus-host interactions and pathogenicity High-throughput drug screening for antivirals Role of viral proteins in neuroinflammation and cancer Translational genomics in precision medicine His recent publications highlight SARS-CoV-2 ORF3a, Zika envelope proteins, and HIV protease inhibitors, emphasizing host-pathogen mechanisms across species. He has served on NIH panels and editorial boards for journals like Cell Research and Retrovirology . Scientific awards include: Fellow, American Academy of Microbiology (2019) Bernard L Mirkin Endowed Chair (2001-2004) Honorary Director, Shandong Gallo Institute (2009) Distinguished Service from SCBA (2015) Outstanding Service from CBA-USA (2016) Dr. Zhao also contributes to clinical diagnostics and personalized medicine through molecular testing and pharmacogenetics programs.

• Software Engineering
• Reverse Engineering
• Program Understanding
• +۷ مورد دیگر

Ken Wong is an Associate Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. He also serves as Associate Chair within the same department. Holding a PhD in Computer Science from the University of Victoria (1999), his research focuses on software engineering challenges such as reverse engineering, program understanding, and software visualization. He emphasizes improving software evolution through tools like architecture recovery and root cause analysis, with applications in web/mobile platforms and diverse system understanding. Teaching highlights include developing Massive Open Online Courses (MOOCs) via Coursera, including the 'Software Product Management Specialization' and courses on Agile practices, client needs analysis, and software metrics. His recent publications (2023–2025) span AI-driven healthcare innovations (e.g., medical imaging, photoacoustic tomography) and advanced computer vision techniques (e.g., diffusion models, video inpainting). Notable collaborations include EVAREST studies on heart failure management and lung transplantation outcomes. His work bridges software engineering theory and practical applications in healthcare technology, with contributions to federated learning frameworks (e.g., FedLPPA) and AI-augmented clinical decision support systems. Research also extends to autonomous driving (DriveGPT4-V2) and 3D human avatar generation (DreamAvatar), showcasing interdisciplinary impact.

Lingming Zhangمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Machine Learning
• +۶ مورد دیگر

Lingming Zhang is an Associate Professor at the Department of Computer Science, University of Illinois Urbana-Champaign, affiliated with the Grainger College of Engineering. His research focuses on the intersection of Software Engineering, Programming Languages, and Machine Learning, with a particular emphasis on automated program repair, compiler testing, and large language model (LLM) applications in software engineering. He has published over 100 papers, achieving an h-index of 50+, and holds an ACM Distinguished Member status. Research Interests: LLM-based software testing, repair, and synthesis Fuzzing of deep-learning libraries and compilers Open-source code LLMs (e.g., StarCoder2, Magicoder) with over 1M downloads Automated program repair systems (e.g., AlphaRepair, ChatRepair, Agentless) Recent Contributions: Developed TitanFuzz for coverage-guided compiler fuzzing Released Agentless , an LLM-based coding tool adopted by OpenAI and DeepSeek Proposed SWE-RL to enhance LLM reasoning via reinforcement learning Service Roles: Program Co-Chair for ASE 2025 and LLM4Code 2025 Associate Chair for OOPSLA 2024 and Area Chair for ICSE 2025/2026 Recipient of NSF CAREER Award and ACM SIGSOFT Early Career Award Lab/Teams: Develops open-source tools like UniAPR for efficient patch validation Active in releasing industry-adopted LLM-based software engineering tools

Niels Henrik Mortensenمشاهده پروفایل

استاد

• Product Architecture
• Modularization
• Maintenance Performance
• +۳ مورد دیگر

Niels Henrik Mortensen is a Professor and Head of Section in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on engineering design and manufacturing systems, with emphasis on product architecture, modularization, maintenance performance, and AI-driven design solutions. He leads initiatives in engineer-to-order systems, lifecycle costing, and digital transformation in manufacturing. Key research interests include optimizing product architectures for modular systems, enhancing maintenance strategies through data analytics, and applying AI to improve CAD design reuse. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure, and sustainable energy systems. Supervisor for 5 active PhD projects focused on modular architectures, logistics services, and configuration systems Published 175+ peer-reviewed articles, including work on AI-based maintenance frameworks and configurator development Recipient of industry collaboration projects with offshore energy and manufacturing sectors Notable contributions include frameworks for maintenance performance diagnostics and adaptable configuration models. His team operates through MEK and CONSTRUCT research groups at DTU.

Ondrej Vaculinمشاهده پروفایل

استاد

• Passive Vehicle Safety
• Automated Driving
• Vehicle Dynamics
• +۳ مورد دیگر

Prof. Ondrej Vaculin, Ph.D., is a Professor at Technische Hochschule Ingolstadt (THI), specializing in passive vehicle safety, mechatronic systems, and automated driving. He joined THI in 2018 and previously held roles at TÜV SÜD Prague (2008–2018) as Vice President for Safety and Security in Automotive, and as a researcher at Czech Technical University (2005–2008) and DLR Oberpfaffenhofen (2000–2005). His research focuses on enhancing vehicle safety through advanced simulation, sensor integration, and machine learning applications. Education: Ph.D. in Mechanics of Solids, Deformable Bodies and Continua from Czech Technical University in Prague (2001), and a degree in Technical Cybernetics from the Faculty of Electrical Engineering at the same university (1991). His work bridges theoretical research and practical implementation, addressing challenges in automated driving systems, crash simulation, and human body diversity in safety design. Research interests include passive safety systems, autonomous vehicle dynamics, and infrastructure integration for safety enhancements. Recent publications emphasize collaborative smart infrastructure, sensor fusion for free space detection, and machine learning in crash detection. He actively contributes to FISITA, serving as a Council Delegate and member of technical committees. Awards/memberships: Active in FISITA, holding leadership roles in technical committees. No explicit awards listed, though his contributions to automotive safety standards are notable. Grants and advising: While no specific grants or students are detailed, his extensive industry and academic collaborations (e.g., IN2Lab testing field projects) highlight his role in applied research and development.

Pedro Orvalhoمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Automated Reasoning
• Formal Methods
• +۴ مورد دیگر

Pedro Orvalho is a Research Associate in the Department of Computer Science at the University of Oxford, working with Professor Marta Kwiatkowska on the FUN2MODEL ERC project. His research bridges theoretical computer science with practical applications in software engineering and programming education. His educational background includes: PhD in Computer Science and Engineering (2025) from Instituto Superior Técnico, Universidade de Lisboa MSc in Information Systems and Computer Engineering (2019) from Instituto Superior Técnico BSc in Information Systems and Computer Engineering (2017) from Instituto Superior Técnico Orvalho's research spans Artificial Intelligence, Automated Reasoning, Formal Methods, and Program Repair, with significant contributions to programming education tools. His work integrates formal methods with machine learning techniques to develop novel approaches for program verification and repair, particularly focused on introductory programming assignments. His scientific achievements have been recognized with prestigious awards: Vencer o Adamastor (VoA) - 3rd Edition (2025) ELISE Mobility Grant (2024) COST Travel Grant (2022) Excellence in Teaching IST Awards (2021 and 2024) ACM SIGSOFT Distinguished Paper Award (ESEC/FSE 2021) FCT PhD Scholarship (2020-2024) With five years of teaching experience at Instituto Superior Técnico, Orvalho has developed educational tools like GitSEED and MENTOR that bridge his research with practical classroom applications. His research has been supported by multiple grants including the ERC FUN2MODEL project and FCT PhD Scholarship, demonstrating both academic and practical impact. He maintains active collaborations with researchers from Czech Technical University in Prague, Carnegie Mellon University, and industry partners like OutSystems, contributing to an international research network focused on software reliability and educational technology.

Michael Wehmöllerمشاهده پروفایل

استاد

• Dental Technologies
• Medical Device Innovation
• Biomechanics
• +۵ مورد دیگر

Prof. Dr.-Ing. Michael Wehmöller is a full Professor at the Faculty of Engineering and Computer Science, Osnabrück University of Applied Sciences. His career spans roles as a technical director in medical device companies and interdisciplinary research leadership in DFG/EU-funded programs, integrating CAD/CAM, additive manufacturing, and biomechanics. Research interests focus on dental technology , medical device innovation , biomechanics , biomaterials , and 3D printing . His work bridges engineering precision with clinical applications , particularly in craniofacial reconstruction and selective laser melting for implants. The 15 most recent publications highlight trends in computer-aided implant design biodegradable materials testing automated surgical planning with a strong emphasis on clinical translation of engineering solutions. Scientific recognition includes Innovationspreis NRW (1996) Innovationspreis Ruhrgebiet (2002) and ongoing membership in VDI medical technology panels . He leads the Digitale Dentale Technologien lab, focusing on next-generation implant systems.

Alexis Kirkeمشاهده پروفایل

عضو هیئت علمی

• Music Technology
• Computational Music
• Human-Computer Interaction
• +۳ مورد دیگر

Dr Alexis Kirke is a Senior Research Fellow in Computer Music at the School of Art, Design and Architecture (Faculty of Arts, Humanities and Business) at the University of Plymouth. As a composer-in-residence, he specializes in interdisciplinary research at the intersection of music, computing, and healthcare. His work includes developing adaptive music systems like RadioMe for dementia care, applying quantum computing to music composition, and exploring affective computing through brain-computer interfaces. Teaching roles include associate lecturer positions in modules such as Collaborative Practice (BA Sound and Music Production), Psychology (BA Music), and MRes Computer Music. He has supervised five PhD students as a second supervisor and served as an internal PhD examiner. His research focuses on algorithmic composition, music technology for healthcare, quantum computing applications in music, and multi-agent systems inspired by natural phenomena like humpback whale song evolution. Recent projects include the Plymouth Marine Institute collaboration and the Cloud Chamber performance involving real-time interaction with subatomic particles. Key contributions include innovative systems like RadioMe, which combines adaptive radio with reminder systems for dementia patients, and Q-Muse, a quantum computer music system. His work bridges computational creativity with human-centric applications, emphasizing ethical and accessible technology. Grants & Awards: No specific awards listed, but active in collaborative research projects Lab/Teams: Plymouth Marine Institute, Cloud Chamber Project

Patrick Heymansمشاهده پروفایل

دانشیار

• Software Engineering
• Requirements Engineering
• Software Product Lines
• +۵ مورد دیگر

Dr. Patrick Heymans is an Associate Professor at the Faculty of Computer Science, University of Namur, Belgium. His research focuses on Software and Information Systems Engineering , with particular emphasis on Requirements Engineering, Software Product Lines, and Conceptual Modeling. Namur Digital Institute (NADI) research group Director of METADONE project - graphical environments for domain-specific modeling Research interests include: Formal Methods and Computer-Aided Software Engineering Software Evolution and Security Human-centric software configurators Recent publications examine: Variability-intensive systems analysis with RNNs (2024) Ontology-based product configuration (2022) User Experience of web configurators (2022) Scientific honors: Three Most Influential Paper Awards (2016-2024) Keynote speaker at major software engineering conferences Professional engagements: Member of multiple journal editorial boards Co-founder of VaMoS workshop on variability modeling Active in international conference program committees

• Computer Modelling and Simulation
• Operations Management
• Supply Chain Management
• +۳ مورد دیگر

Dr. Terrence Perera is a Teaching Professor in the Operations Management and Decision Sciences (OMDS) department at the University of Sheffield's Management School. With over 30 years of experience in teaching, research, and consultancy, he specializes in computer modeling/simulation, operations management, and supply chain management. He leads modules such as 'The Intelligent Organisation,' 'Internationalisation Challenge,' and 'Business Intelligence' in undergraduate and MBA programs. His work integrating Qlik into teaching earned him the 2025 Qlik Education Ambassador title, while his Internationalisation Challenge module was shortlisted for a postgraduate employability award by AGCAS. Education: BSc and PhD qualifications. Research Interests: Focus on Industry 4.0 integration, simulation in healthcare (e.g., neonatal unit analysis), supply chain data management, and sustainability initiatives. He has secured five EPSRC grants and managed Knowledge Transfer Partnership projects with firms like BAE Systems and Siemens. Professional Recognition: Recipient of the 2025 Qlik Education Ambassador award and AGCAS shortlist. His consultancy spans sectors including healthcare, manufacturing, and logistics. Teaching & Advising: Supervises student dissertations, develops case studies from industry collaboration. His modules emphasize real-world applications of analytics and modern technologies. Grants & Projects: Five EPSRC grants, multiple KTP projects focused on manufacturing systems and ERP. Collaborations include Sheffield Children’s Hospital and Fosters Bakery.

Giovanni Squilleroمشاهده پروفایل

استاد

• Artificial Intelligence
• Soft Computing
• Evolutionary Algorithms
• +۷ مورد دیگر

Giovanni Squillero is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He leads the CAD group (Electronic CAD & Reliability) and serves on Politecnico's Joint Committee for Teaching and Ph.D. Steering Committee (Pure and Applied Mathematics).

Robert Mandersonمشاهده پروفایل

مدرس ارشد

• Information Systems
• Business & Industry
• Education Technology
• +۷ مورد دیگر

Robert Manderson is a Senior Lecturer in the University of Roehampton Business School, specializing in information systems, project management, and business research. He holds a B.Sc., Dip.Sc., M.Sc., and is a Fellow of the Higher Education Academy and PRINCE2 Registered Practitioner. His career spans software engineering at BAE Systems and academic research roles at Lancaster University and Manchester University, funded by EPSRC and BT Plc. External Examiner roles at York Business School (2020–2024), Glyndwr University (2013–2016), and University of West London (2011–2015) Member of British Academy of Management and IEEE Research interests focus on ICT in business, Cloud computing, Big Data, education technology, and employability. He contributes to textbooks on Management Information Systems and regularly reviews conference papers. Current projects explore Fintech regulation, aerospace IT innovation, and social media's role in student employability. Key awards: Fellow of HEA, PRINCE2 Certifications Teaching areas include data analytics, PRINCE2/Agile methodologies, and Adobe Creative Cloud. He has advised on modules across computing and business programs, emphasizing ICT's role in organizational success.

Aydin Nassehiمشاهده پروفایل

استاد

• Smart Manufacturing Systems
• Agent-Based Manufacturing Planning and Control
• Artificial Intelligence in Manufacturing
• +۳ مورد دیگر

Professor Aydin Nassehi is Head of the School of Electrical, Electronic and Mechanical Engineering at the University of Bristol, UK. He holds the academic rank of Professor of Production Systems and actively contributes to research in smart manufacturing, agent-based modeling, and digital twins. Research interests include AI integration in manufacturing, generative design, and systems optimization. He has collaborated extensively with Dr. Ben Hicks on projects like ProtoTwinning and Designing the Future , focusing on digital twin applications and transdisciplinary engineering. His scholarly output spans over 150 publications, with recent work emphasizing explainable AI, sustainability in food supply chains, and biomedical manufacturing innovations. Publications demonstrate expertise in machine learning, digital twin cost modeling, and additive manufacturing optimization. His projects have received funding from EPSRC and other academic institutions. Current research explores Industry 5.0 challenges, balancing automation with human-centric approaches, and advancing interoperability in cloud manufacturing environments.