جست‌وجوی استاد و پژوهشگر

Moharram Challengerمشاهده پروفایل

استادیار

• Cyber-physical Systems
• Multi-agent Systems
• Domain-specific Modeling Languages
• +۵ مورد دیگر

Moharram Challenger is a tenure-track Assistant Professor in the Department of Computer Science at the University of Antwerp's Faculty of Sciences. Previously, he served as an assistant professor at Ege University (2017-2018) and as a post-doctoral researcher at the University of Antwerp (2019-2020) working on Flanders Make projects PACo and DTDesign. His academic journey includes R&D leadership roles at UNIT IT Ltd. (2012-2016), post-doctoral research at Wageningen University (2016-2017), and tenure-track faculty positions at IAU-Shabestar University (2005-2009). His research spans Cyber-physical Systems , Multi-agent Systems , and Domain-specific Modeling Languages , with recent publications focusing on quantum machine learning, digital twinning, and IoT optimization. Key projects include ITEA ModelWriter, ITEA Assume, and Flanders Make initiatives. His work demonstrates strong integration of model-driven engineering with emerging technologies like quantum computing and reinforcement learning. Challenger actively contributes to the academic community as a member of IEEE and ACM . His publication record shows consistent output across top venues, with 2025 featuring significant work in quantum-enhanced learning and CPS security. Current research emphasizes practical applications in drone energy modeling, medical diagnostics, and industrial IoT systems. His advising activities focus on cyber-physical systems and agent-based modeling, supported by grants from TUBITAK and Flanders Innovation & Entrepreneurship. Key collaborations include European ITEA projects and partnerships with industrial entities through UNIT IT Ltd. Challenger maintains active development through GitHub repositories related to code refactoring, model-driven engineering, and legacy system modernization, reflecting his commitment to practical software engineering solutions.

Stephan Schlöglمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Artificial Intelligence
• Interaction Design
• +۶ مورد دیگر

Stephan Schlögl is a Full Professor at MCI - The Entrepreneurial School in Austria, leading research and teaching in Human-Computer Interaction (HCI), Artificial Intelligence (AI), and Information Systems. He holds editorial roles at journals like the Springer Discover Artificial Intelligence Journal and MDPI Multimodal Technologies and Interaction Journal. His work spans over two decades, with key roles including Postdoctoral Research Fellow at Télécom ParisTech (2012–2013) and PhD Researcher at Trinity College Dublin (2008–2012). Schlögl’s research focuses on HCI, AI-driven conversational systems, and assistive technologies for aging populations. Education includes a PhD in Computer Science from Trinity College Dublin, an MSc in Human-Computer Interaction from University College London, and a Mag.(FH) in Applied Informatics & Management from MCI. His teaching spans Software Engineering, Business Intelligence, and Research Methods. Research interests emphasize natural language interfaces, AI ethics, and technology’s societal impact. Notable projects include the EU-funded EMPATHIC initiative (2017–2021), developing an empathic virtual coach for elderly care, and the CRYSTAL project (2024–present) on conversational systems for emotional support. Schlögl has supervised numerous theses on AI applications, chatbots, and UX design. He co-organized major conferences like CUI (Conversational User Interfaces) and received awards for best papers in AI-HCI and CHIRA. His work bridges academia and industry, addressing challenges in AI adoption, digital well-being, and ethical technology design.

• Robotics
• Autonomous Systems
• Mobile Robotics
• +۶ مورد دیگر

Markus Bader is a PostDoc Researcher at the Technische Universität Wien's Faculty of Informatics, Department of Automation Systems. He holds roles as Curriculum Coordinator for Master's programs in Automation Systems and Mobile Robotics, and serves on multiple academic committees including the Faculty Council and Curriculum Commissions for Informatics and Computer Engineering. He earned his Diplom-Ingenieur (2006) and Doctor Technica (Dr.techn.) from TU Wien. His research focuses on autonomous systems, mobile robotics, and control systems, with notable work on multi-robot coordination, path planning algorithms, and real-time navigation in human environments. Key projects include TransportBuddy (2018), exploring navigation in human spaces, and the Formula Student Driverless race car design (2017). Bader has led or contributed to funded projects such as the Austrian Research Promotion Agency (FFG)-supported Green Facade Digital Twin (2025–2027), Independent Wheel Offset Steering (2016–2017), and MPCv1 (2015–2017), emphasizing model predictive control and sensor integration. Research Highlights : Prioritized multi-robot route planning (MRRP), human motion prediction for autonomous navigation, and sensor fusion for vehicle localization. Grants : FFG-funded projects totaling over €2.5M, including autonomous vehicle coordination and mobile robotics tool development. He advises students on topics like ROS2-based route planning and independent steering systems, with 7+ supervised theses documented. Bader's work bridges theoretical robotics research with practical applications in industrial automation and autonomous vehicle systems.

Naeha Sharifمشاهده پروفایل

مدرس

• Computer Vision
• Natural Language Processing
• Medical Image Analysis
• +۵ مورد دیگر

Dr. Naeha Sharif is a Lecturer in Computer Science & Software Engineering at The University of Western Australia (UWA), specializing in Computer Vision (CV) and Natural Language Processing (NLP). She holds a PhD from UWA (2021) focused on AI-driven image captioning and received the prestigious ACS 1962 Medal for outstanding IT/CS research. Her work bridges AI with healthcare, including automated medical assessment via spine scans (DXA) for abdominal aortic calcification analysis and AI-driven medical report generation for fundus imaging. Education: PhD in Computer Science (UWA 2021), Master of Engineering in Biomedical Engineering (Kyung Hee University, 2013). Previous roles include Postdoctoral Fellow at Edith Cowan University (2021–2022). Research Interests: Vision-language models, medical image analysis, captioning metrics, multimodal learning, and AI applications in healthcare. Active in UN SDGs related to health and innovation. Teaching: Unit Coordinator for Computer Graphics & Animation (CITS3003, 2022–2023) Computational Thinking with Python (CITS1401, 2023) Grants: Lead investigator on the 'Generative AI for Screening of Depressive Disorders' project (2024). Awards: Recognized for student learning contributions (2025), best paper awards (2024/2020), and academic excellence honors (2021/2020). Labs/Teams: Member of UWA Natural & Technical Language Processing Group and IEEE Signal Processing Society.

• Blockchain
• Internet of Things (IoT)
• Edge computing
• +۹ مورد دیگر

Abdelhakim HAFID is a Full Professor at the University of Montreal , affiliated with the Faculty of Arts and Science and the Department of Computer Science and Operations Research . He leads the LRC — Laboratoire de recherche en réseaux de communication and is a member of several research centers including CIRRELT (interuniversity research center on enterprise networks, logistics, and transportation), the Cyberjustice Lab , and talents (AI for cybersecurity lab). His research focuses on Blockchain security , IoT , edge and fog computing , intelligent transport systems , and network resource management . He has supervised over 30 graduate students and led/co-led numerous research projects funded by agencies like NSERC , FRQNT , and MITACS . Notable projects include Blockchain Evolution: Quantum-Resistant Security (2025–2031) and Design and Management of Fog Networks (2019–2026). His work spans vehicular networks , mobile cloud computing , and machine learning for network optimization . He actively contributes to cybersecurity initiatives, including IoT authentication frameworks and AI-driven solutions for judicial systems (e.g., Cyberjustice ). Key Projects : Quantum-Resistant Blockchain Security (2025–2031) IoT Authentication via Blockchain and Intelligent SIM (2022–2026) Fog Network Design (2019–2026) Grants : NSERC Discovery Grants MITACS Acceleration Fellowships FRQNT Team Research Grants His lab collaborations include CIRRELT (logistics & transport) and Cyberjustice (digital law), reflecting interdisciplinary strengths in both technical and societal domains.

Laura Pozziمشاهده پروفایل

استاد

• Embedded Systems
• Compiler Techniques
• Coarse-Grain Reconfigurable Architectures
• +۳ مورد دیگر

Laura Pozzi is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), Switzerland, since 2015. She previously held positions as Associate Professor (2011–2015) and Assistant Professor (2005–2011) at USI. Prior to joining USI, she was a postdoctoral researcher at EPFL's Processor Architecture Laboratory (2001–2005), a research engineer at STMicroelectronics (2000), and an Industrial Visitor at UC Berkeley (2000). Education: MS and PhD in Computer Engineering from Politecnico di Milano, Italy (1996–2000). Her research focuses on the interaction between compiler and architecture design, particularly in embedded systems , with key areas including approximate computing , coarse-grained reconfigurable arrays (CGRAs) , high-level synthesis (HLS) , and fuzz testing . She has led projects on automated design space exploration, compiler optimizations for reconfigurable architectures, and error estimation in approximate circuits. Recent Publications span topics like SAT-based mapping for CGRAs , grammar-based fuzzing of shell interpreters , and approximate logic synthesis , reflecting her interdisciplinary work bridging hardware/software co-design and software verification. Scientific Awards: Credit Swiss Best Teaching Award IEEE DAC Best Paper Award Leadership Roles: Co-Program Chair, IEEE Symposium on Application Specific Processors (SASP) Editorial Board Member, IEEE Design and Test Students: Current: Rodrigo Otoni (Postdoc), Morteza Rezaalipour (PhD), Riccardo Felici (PhD), Cristian Tirelli (PhD) Alumni: Ilaria Scarabottolo (PhD/Postdoc), Lorenzo Ferretti (PhD/Postdoc), Georgios Zacharopoulos (PhD), Giovanni Ansaloni (PhD/Postdoc), Paolo Bonzini (PhD)

Bowen Xuمشاهده پروفایل

استادیار

• Software Engineering
• Machine Learning
• Program Analysis
• +۱۲ مورد دیگر

Bowen Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University (NC State), College of Engineering. His research focuses on software engineering, machine learning, and program analysis, particularly in securing AI models and improving code quality. He holds a PhD from Singapore Management University (SMU), where he also conducted postdoctoral research. Education: PhD in Computer Science, Singapore Management University (SMU) Postdoctoral Researcher, SMU School of Computing and Information Systems Research Interests: AI for Code, Backdoor Attacks on Code Models, Vulnerability Detection Code Representation Learning, Model Compression, Safety of AI Systems Chatbot Development for Developers, Automatic Code Review Key Contributions: Developed PTM4Tag+, a Stack Overflow tag recommendation system using pre-trained models Explored stealthy backdoor attacks in code and reinforcement learning systems Pioneered work on automatic vulnerability repair using LLMs and broader input analysis Awards: 2022: Honorable Mention Award (ACSAC) 2018: Highly Commended Full Paper Award (ESEM) Service Roles: Editorial Board Member, Empirical Software Engineering Journal Program Committee Co-chair for ICSE/FSE Research Tracks Organized workshops like FORGE, MaLTeSQuE, and SEA4DQ Labs & Teams: Leads the Softmax Lab at NC State, advising 12+ students across PhD, Master's, and undergraduate levels. Alumni include industry professionals at Microsoft, Barclays, and Marvell Semiconductor.

Tao Xieمشاهده پروفایل

استاد

• Software Analytics
• Software Security
• System Software
• +۴ مورد دیگر

Tao Xie is a Chair Professor at the School of Computer Science, Peking University, and serves as Vice Director of the Key Lab of High Confidence Software Technologies under the Ministry of Education, China. Previously, he held tenured positions at the University of Illinois at Urbana-Champaign and North Carolina State University, advancing from Assistant to Full Professor. His research focuses on software analytics , software security , system software , trustworthy AI , and intelligent software engineering , aiming to enhance software quality and reliability. He has contributed to foundational work in software testing and mining software repositories. Notable honors include: ACM Fellow (2021) AAAS Fellow (2019) IEEE Fellow (2018) NSF CAREER Award (2009) Xie actively serves in academic leadership roles, including Program Co-Chair for ICSE 2021 and Vice Chair of the China Computer Federation Technical Committee on Software Engineering. He also contributes as Co-Editor-in-Chief for the Wiley Journal of Software Testing, Verification and Reliability.

Sven Scheweمشاهده پروفایل

استاد

• Automata Theory
• Game Theory
• Formal Verification
• +۱۲ مورد دیگر

Sven Schewe is a Professor in the Department of Computer Science at the University of Liverpool, affiliated with the School of Electrical Engineering, Electronics and Computer Science. He leads the AI Section and is a founding member and former leader of the Verification Group. He also has secondary affiliations with the Algorithms, Complexity Theory and Optimisation Group and the Institute for Risk and Uncertainty. Research Interests: His research centers on automata theory and game theory, particularly their applications in the verification and synthesis of reactive and safety-critical systems. He investigates infinite-duration games, automata over infinite words and trees, and develops algorithms and tools for automated verification, synthesis, and learning of optimal control strategies. His work extends to reinforcement learning with formal guarantees, cyber-physical systems, and AI safety. Recent Research Trends: His recent publications demonstrate a strong integration of formal methods with machine learning, particularly in adversarial training, neural network robustness, and model-free reinforcement learning under omega-regular objectives. He also applies formal reasoning to interdisciplinary domains such as chemical space exploration and materials science. Scientific Awards: Finalist for the ERCIM Cor Baayen Award 2010 Dr. Eduard Martin Preis 2009 GI Dissertation Award 2008 Advising and Grants: He actively supervises numerous PhD students and postdoctoral researchers. He is Principal Investigator (PI) or Co-Investigator (CI) on multiple major grants, including EPSRC Programme Grants, Royal Society Fellowships, and Horizon Europe projects. His funded research spans topics such as game theory, verification, synthesis, reinforcement learning, and risk analysis. He has hosted visiting researchers and collaborated internationally with institutions in Germany, France, India, Taiwan, and the US. Labs and Teams: He co-founded and led the Verification Group and previously led the AI Section at the University of Liverpool. These groups focus on formal methods, automata, games, and their applications in AI and safety-critical systems.

• Robust Statistics
• Econometrics
• Robust Estimation
• +۷ مورد دیگر

Mikhail Zhelonkin is an Associate Professor in the Department of Econometrics at the Erasmus School of Economics, Erasmus University Rotterdam. His work bridges econometrics and robust statistical methodology, with a strong emphasis on developing reliable inference methods under model misspecification and endogeneity. Research Interests: His research focuses on robust statistics , particularly in econometric models. Key areas include robust estimation and testing in probit models, sample selection models, and risk measurement. He investigates the influence function and robustness properties of estimators under violations of distributional assumptions. His methodological contributions aim to improve the reliability of statistical analysis in empirical economics and finance. Publication Trends: His recent work demonstrates a consistent focus on robust methods in econometric modeling, especially addressing endogeneity and selection bias. He combines theoretical developments with practical implementation, as seen in his development of the R package ssmrob . The publications span top-tier journals in statistics and econometrics, reflecting strong methodological rigor and interdisciplinary relevance. Scientific Awards: No awards listed in the provided text. Advising and Grants: One supervised work is listed, indicating student or research supervision, though specific names and grant funding are not mentioned. He actively contributes to the academic community through organizing workshops and conferences in data science and robust statistics. Labs and Teams: No specific lab or research team is mentioned in the text. However, his collaborations with researchers like Elvezio Ronchetti and Marc Genton suggest active participation in international research networks focused on robust statistical methods.

Donald Yeungمشاهده پروفایل

استاد

• Computer Architecture
• Computer Engineering
• Memory Systems
• +۵ مورد دیگر

Donald Yeung is a Professor and Associate Chair for Undergraduate Education in the Department of Electrical and Computer Engineering at the University of Maryland , with an additional appointment as Affiliate Professor in the Department of Computer Science . His research focuses on Computer Architecture , particularly in memory systems , 3D integration , energy-efficient processors , and parallel processing . He leads projects like Monolithic 3D Integration of CPU and Main Memory and Approximate Computing . Recent work emphasizes ReRAM-based memory architectures , extreme-scale processor design , and micro-fluidic cooling solutions for 3D CPUs. His teaching includes courses like ENE 646: Computer Architecture and ENE 150: Intermediate Programming Concepts . Key achievements include the Best Paper Award at MULTIPROG-2017 and contributions to IEEE Micro and ACM Transactions . His research spans cache optimization , reuse distance analysis , and directory coherence protocols . Current grants include funding for heterogeneous microprocessor parallelism and low-power system design . Advises graduate students Yinuo Wang and Hung-Yu Yeh, and collaborates with teams like the UMIACS Technical Report Group . His lab focuses on memory-centric computing and scalable multicore systems .

Sándor Ádányمشاهده پروفایل

استاد

• Structural Engineering
• Computational Mechanics
• Finite Element Modeling
• +۳ مورد دیگر

Sándor Ádány is a Professor at the Department of Structural Mechanics , Budapest University of Technology and Economics. His work focuses on advanced structural analysis of thin-walled members and systems-based design methodologies. Research Interests: Specializes in buckling behavior of thin-walled structures, finite element modeling, cold-formed steel stability, and modal decomposition techniques. Key areas include Lateral-torsional buckling Displacement mapping in constrained FEM Stiffener optimization in plate structures Combined loading stability of tubular members Prebuckling deformation effects Fourier-based numerical methods Article Trends (2023-2025): Recent publications emphasize elastic stability analysis of thin-walled beams and tubular structures under complex loading conditions, with particular attention to prebuckling deflections, torsional rigidity effects, and numerical validation of analytical models. Innovations include Fourier-series displacement approximations and constrained finite element methodologies.

Nate Fosterمشاهده پروفایل

استاد

• Programming Languages
• Networking
• Formal Verification
• +۳ مورد دیگر

Nate Foster is a Professor of Computer Science at Cornell University and a Visiting Researcher at Jane Street . During the 2023-24 academic year, he served as a Visiting Professor at EPFL in the Data Center Systems Laboratory. His research bridges Programming Languages and Networking , focusing on formal verification, data plane programming, and language design for networked systems. His recent work includes developing symbolic automata for network verification (e.g., Active Learning of Symbolic NetKAT Automata , StacKAT ), creating efficient verifiers like KATch , and advancing type safety in data plane programming (e.g., SafeP4 ). These efforts span formal methods, algorithm optimization, and practical networked systems. Notable scientific awards include: NSF CAREER Award Sloan Research Fellowship ACM SIGCOMM Rising Star Award ACM SIGPLAN Robin Milner Award He actively contributes to PLDI, POPL, OOPSLA, and ICFP, serving as author, editor, and committee member. His GitHub repositories include tools for academic website templates and programming language research codebases.

Hossam H. H. Mousaمشاهده پروفایل

پژوهشگر

• Electrical Power Engineering
• Renewable Energy Systems
• Power Systems
• +۳ مورد دیگر

Hossam H. H. Mousa is a Doctoral Researcher at Aalto University's Department of Electrical Engineering and Automation, School of Electrical Engineering. He also serves as an Assistant Lecturer at South Valley University's Department of Electrical Engineering since 2020. B.Sc. in Electrical Engineering (2017), South Valley University M.Sc. in Electrical Power and Machines Engineering (2020), South Valley University His research focuses on electrical power engineering, including maximum power point tracking (MPPT) for renewable energy, power systems analysis, energy management, and machine learning applications in grid optimization. He has published extensively on topics like hosting capacity estimation, unbalanced microgrids, and hydrogen storage integration. The 15 most recent articles emphasize modern power systems optimization through machine learning (2025), smart inverter applications in renewable integration (2025), and hydrogen storage's role in cold climate energy management (2025). Earlier works include best practice studies on capacitor allocation (2024) and photovoltaic system controls (2024), earning him the 2024 Best Paper Award in the International Journal of Electrical Power & Energy Systems. Best Paper Award (2024), International Journal of Electrical Power & Energy Systems His scholarly activities span energy conversion, microgrid stability, and applied machine learning, contributing to sustainable energy transition solutions. He has collaborated on international research books addressing distribution network hosting capacity (2025) and future energy systems challenges.

Yanja Dajsurenمشاهده پروفایل

استادیار

• Software Architecture
• Model-Driven Development
• Component-Based Software Engineering
• +۶ مورد دیگر

Yanja Dajsuren is an Assistant Professor and Program Director of the PDEng Software Technology program at Eindhoven University of Technology's Department of Mathematics and Computer Science. Her work bridges academic research and industry applications in software engineering and mobility systems. Education: PhD in Computer Science (2015), TU/e PDEng in Software Technology (2005), TU/e MBA (2002), Maastricht School of Management Research Focus: Yanja specializes in software architecture for autonomous and cooperative driving systems, with a focus on model-driven development, functional safety, and system modularity. Her work contributes to Cooperative Intelligent Transport Systems (C-ITS) and aligns with UN Sustainable Development Goals related to smart cities and innovation. Projects: Current projects include i-CAVE (Project #6) and Horizon 2020 C-MobILE, addressing challenges in automotive software integration and cooperative driving systems. Past projects at Philips Research, NXP Semiconductors, and CWI demonstrate her long-term expertise in industrial software development. Academic Contributions: She co-founded the International Workshop on Automotive Software Architectures (WASA) and launched the Journal of Automotive Software Engineering (JASE). Her collaborations span academia and industry, including partnerships with ASML, Philips Hue, and international research teams.