جست‌وجوی استاد و پژوهشگر

• Empirical Software Engineering
• Requirements Engineering
• Applied Natural Language Processing
• +۷ مورد دیگر

Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Deakin University's School of Information Technology, part of the Faculty of Science Engineering and Built Environment. He holds a PhD from the University of Luxembourg where he received the best PhD thesis award in the ICT domain. His research focuses on applied Artificial Intelligence in Software Engineering, with particular emphasis on Empirical Software Engineering, Requirements Engineering, and Applied Natural Language Processing. PhD in Computer Science from University of Luxembourg Masters in Software Engineering from Technische Universitat Kaiserslautern (Germany) Bachelors in Engineering (CS) from Thapar University (India) Arora's research interests center on the intersection of AI and Software Engineering, particularly how machine learning and natural language processing can enhance software development processes. His work explores requirements engineering, test automation, software trustworthiness, and human-centric software development. He investigates how large language models can be effectively deployed for tasks like test case generation, requirements analysis, and traceability. His recent publications reveal a strong focus on practical applications of AI in software engineering, with numerous studies examining the real-world implementation challenges and benefits. His publication record shows significant activity in top software engineering venues, with a notable emphasis on AI applications in software engineering processes. His recent work demonstrates expertise in retrieval-augmented generation systems, requirements-driven testing, and human-centric software development approaches. The publications collectively highlight his focus on bridging theoretical AI advancements with practical software engineering challenges. Best Ph.D. thesis award in the ICT domain at University of Luxembourg Arora actively supervises doctoral students working on cutting-edge topics including satellite communication systems, extended reality applications, and human-centered AI requirements engineering. His industry collaborations include work with Department of Defence on projects like Contextually Situated Anomaly Detection and Planning and Optimisation of Resources in Defence Satellite Communication Systems. He previously worked at SES Satellites on applied AI for IoT and Satcom, and as an FNR-PPP research fellow at the University of Luxembourg in software quality assurance. His laboratory work focuses on developing practical AI solutions for software engineering challenges, particularly in requirements engineering and test automation. Current projects involve multi-orbit satellite constellation optimization, dynamic radio resource management, and extended reality enabled human-centric requirements engineering.

Francesco Ragusaمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۵ مورد دیگر

Francesco Ragusa is a Research Fellow at the University of Catania, Italy, holding an Industrial Doctorate in Computer Science (2021). He spent part of his PhD at the University of Hertfordshire, UK. His work focuses on First Person (Egocentric) Vision, including Human-Object Interaction, Industrial Applications, and Augmented Reality. He co-founded NEXT VISION s.r.l., an academic spin-off from the University of Catania since 2021. Key projects include the MECCANO dataset for industrial human-object interactions and the EGO-EXO4D initiative analyzing skilled human activity from multi-perspective views. Research interests span Computer Vision, Pattern Recognition, and Machine Learning. He contributed to seminal datasets like MECCANO and ENIGMA-51, advancing understanding of human behavior in industrial settings. His work emphasizes practical applications, such as wearable assistive systems and visual navigation solutions. Ragusa has delivered tutorials at major conferences (e.g., ICIAP, VISIGRAPP) on First Person Vision’s history, challenges, and trends. He actively promotes industrial collaborations and has secured grants including PNRR MUR (Code E63C22001940006) and EU funding under Next Generation EU. His teaching and professional activities include organizing workshops on egocentric vision for AI-driven assistants and industrial safety systems. Current research directions involve multimodal synthetic data utilization, gaze-based interaction analysis, and cross-modal fusion for human-robot collaboration.

Liming Zhuمشاهده پروفایل

استاد

• Software Architecture
• Software Engineering
• Distributed Systems
• +۷ مورد دیگر

Dr. Liming Zhu serves as Research Director at CSIRO's Data61 and conjoint full professor at the University of New South Wales (UNSW), where he leads research in AI/ML infrastructure, responsible AI, and software engineering. He chairs Standards Australia's blockchain committee and contributes to AI trustworthiness initiatives through the National AI Center's Responsible AI think tank. His research interests span software architecture , responsible/ethical AI , blockchain , quantum software , and cybersecurity . Recent work focuses on reference architectures for foundation model systems, guardrail frameworks for AI safety, and vulnerability analysis tools. His publications demonstrate strong emphasis on bridging ethical principles with practical implementation in AI systems. His recent publications (2024-2025) reveal concentrated research on generative AI safety frameworks, architectural patterns for foundation model agents, and blockchain applications for software supply chain security. Key themes include multi-layered AI safety mechanisms, human-AI collaboration models, and vulnerability tracing methodologies. Professional contributions include: Chairperson of Standards Australia's blockchain committee Member of AI trustworthiness-related committees Member of Responsible AI think tank at National AI Center Steering Committee Member for AIware 2025 Dr. Zhu has supervised over 20 PhD students and taught software architecture courses at UNSW and University of Sydney. His leadership extends to conference organization, serving as General Chair for ICSSP 2023 and Steering Committee Member for multiple conferences including AIware, CAIN, and ICSA.

• Machine Learning
• Computer Science
• Recommender Systems
• +۴ مورد دیگر

Xiangyang Li is a Professor at the University of Science and Technology of China, School of Computer Science and Technology. His work spans interdisciplinary domains including computer science, machine learning, and geoscience. Research Focus: Machine Learning, Recommender Systems, Blockchain, and Computer Vision. Key Contributions: Development of novel algorithms for UWB positioning, code information retrieval benchmarks, and vision-language models. Recent publications highlight trends in large language model (LLM) integration for recommendation systems, quantum-inspired optimization, and cross-chain consensus models. His 2025 work includes collaborations on semantic-driven inference, prompt tuning, and hybrid BFT consensus for blockchain scalability.

Stefanos Papadakisمشاهده پروفایل

مدرس

• Software Defined Radio
• Cognitive Radios
• Radio Resource Management
• +۵ مورد دیگر

Stefanos Papadakis serves as a Research Staff Scientist at the Telecommunications and Networks Laboratory (TNL) of the Institute of Computer Science at Foundation for Research and Technology-Hellas (FORTH) and holds an Adjunct Lecturer position in the Department of Computer Science at the University of Crete. Since 2001, he has pioneered hardware and software prototyping at TNL-FORTH, currently leading the Software Defined Radio (SDR) group he established to drive vertical integration from physical layer design to application development. His educational foundation includes a Physics degree (2001) and M.Sc. (2004) and Ph.D. (2009) in Computer Science, all earned at the University of Crete. Teaching responsibilities encompass core courses CS-330: Introduction to Telecommunication Systems Theory and CS-435: Network Technology & Programming. Papadakis' research spans wireless innovation frontiers including software-defined/cognitive radios, spectrum sharing, heterogeneous networking, position location, radio propagation modeling, and emergency communications. His work emphasizes practical implementation, yielding functional prototypes across the entire communications stack. Notable contributions include GPU-accelerated SDR frameworks, robust spectrum virtualization techniques, and emergency response communication systems validated through international competitions. Analysis of his 15 most recent publications (2010-2016) reveals dominant themes in SDR optimization for IoT and critical communications, with significant focus on GPU parallelization, interference management in dense networks, and real-time spectrum sharing mechanisms. His experimental approach consistently bridges theoretical models with hardware validation, particularly in emergency response and heterogeneous network scenarios. Key recognitions include: Ericsson Award of Excellence in Telecommunications for position location research First place in PENED doctoral proposal competition Fourth place in IEEE DySPAN 2015 5G Spectrum Challenge Second place in Virginia Tech ShaRC 2016 with the 'Skynet' cognitive radio system Mentorship spans 16 undergraduate projects (11 completed), 8 M.Sc. students (3 completed theses), and 1 Ph.D. candidate. His research is sustained through major EU and national projects including REDComm (emergency communications), EU-MESH (metropolitan networks), RERUM (IoT security), and Heraklion smart city initiatives. The SDR group maintains critical infrastructure like the Heraklion metropolitan wireless network, FORTH campus network, and specialized mobile emergency nodes equipped with multi-radio SDR platforms, satellite transceivers, and high-performance computing resources.

Lajos Hanzoمشاهده پروفایل

استاد

• Wireless Communications
• Optical Wireless Systems
• Signal Processing
• +۵ مورد دیگر

Lajos Hanzo is a distinguished Professor at the University of Southampton's School of Electronics and Computer Science (ECS), where he has established himself as a leading authority in wireless communications and signal processing. His academic profile showcases extensive contributions to the field with over 1400 publications and significant recognition through multiple prestigious fellowships. Dr. Hanzo received his degree in electronics in 1976 and his doctorate in 1983, followed by an honorary doctorate in 2009. His educational background laid the foundation for a career that has continually evolved with communication technologies from early wireless systems through to contemporary 6G research and quantum communications. Hanzo's research spans wireless communications, optical wireless systems, MIMO technologies, and increasingly intersects with artificial intelligence applications for next-generation networks. His work demonstrates remarkable synergy between theoretical foundations and practical implementations, addressing challenges in spectral efficiency, channel capacity, and reliable transmission across diverse communication scenarios. He has made seminal contributions to space-time coding, non-orthogonal multiple access (NOMA), and index modulation techniques that have influenced multiple generations of wireless standards. Analysis of his recent publications reveals a clear progression toward more complex communication paradigms, with increasing focus on 6G technologies, integration of deep learning with traditional communication theory, and exploration of quantum-inspired communication approaches. His work consistently addresses the tension between theoretical capacity limits and practical implementation constraints, with recent papers demonstrating particular interest in millimeter-wave communications, visible light communication, and massive connectivity solutions for IoT applications. FREng (Fellow of the Royal Academy of Engineering) FIEEE (Fellow of the IEEE) FIET (Fellow of the Institution of Engineering and Technology) Fellow of EURASIP (European Association for Signal Processing) DSc (Doctor of Science) While specific details of his advising activities aren't prominently featured in the provided materials, Hanzo's extensive publication record spanning multiple decades suggests significant mentorship of graduate students and postdoctoral researchers. His research has clearly attracted substantial funding to support investigations across wireless communications, with particular emphasis on coding theory, MIMO systems, and next-generation network architectures. The collaborative nature of his recent work indicates ongoing engagement with international research consortia addressing 5G evolution and 6G standardization.

• Agent-Based Modeling
• Network Diffusion
• Public Engagement
• +۳ مورد دیگر

Dr Jennifer Badham is an Assistant Professor in the Department of Sociology at Durham University, affiliated with the Faculty of Social Sciences and Health. She serves as the Director of MA Social Research Methods and Programme Lead for the MDS (Health Data Science) at the Durham Research Methods Centre. Her research focuses on computational methods for complex systems, network diffusion, public engagement, and social network structure. Education: PhD in Computational Social Science (Durham University) Prior roles: Postdoctoral positions at University of Surrey, Queen's University Belfast, and Durham University; Senior Health Policy Advisor in Australia Dr Badham's research explores how social structures influence the spread of ideas, diseases, and behaviors. She employs and extends methods from complexity science, including agent-based modeling and network analysis, with a particular interest in the role of models in policy processes and public engagement. Her recent publications highlight trends in agent-based modeling for health policy, network analysis for behavior interventions, and participatory methods in qualitative research. She emphasizes synthetic network generation, simulation of diffusion processes, and interdisciplinary modeling frameworks. Scientific Awards Fellow, Wolfson Research Institute for Health and Wellbeing (Durham University) Dr Badham supervises postgraduate research students, including Tengpeng Zhang . Her current projects include a major MRC-funded grant ( £528,850 ) to develop socially realistic synthetic networks for health and epidemic modeling. She has contributed to environmental modeling frameworks and health communication through computational approaches.

Chunyang Chenمشاهده پروفایل

استاد

• Software Engineering
• Applied Data Analysis
• Deep Learning
• +۵ مورد دیگر

Chunyang Chen is a Professor at the School of CIT, Technical University of Munich (TUM), Germany. He maintains an active research profile in software engineering with a focus on applying data analysis and artificial intelligence techniques to software development processes. His primary research interests include Software Engineering , Applied Data Analysis , Deep Learning , and Human-Computer Interaction . Dr. Chen is particularly known for his work in applying data analysis to automated software development and mining software repositories, with significant contributions in mobile application testing, GUI testing, and leveraging Large Language Models for software engineering tasks. His recent publications (2024-2026) demonstrate a strong focus on integrating Large Language Models with software testing methodologies, particularly for mobile applications. The research trends show increasing sophistication in using multimodal LLMs, dynamic memory techniques, and retrieval augmentation to improve automated testing capabilities. Dr. Chen maintains an active presence in the software engineering research community, serving on program committees for major conferences including ASE, ICSE, and ESEC/FSE. He has also delivered keynote speeches on mobile application testing with Large Language Models, highlighting his thought leadership in this emerging area.

John Ewerمشاهده پروفایل

دانشیار

• Fire Safety Engineering
• Computational Fluid Dynamics (CFD)
• Building Information Modelling (BIM)
• +۵ مورد دیگر

Dr John Ewer is an Associate Professor in Applied Fire Safety Engineering at the University of Greenwich's School of Computing and Mathematical Sciences, part of the Faculty of Engineering and Science. He leads the Fire Research Team for fire modelling and SMARTFIRE software development in the Fire Safety Engineering Group (FSEG). His work focuses on fire dynamics, CFD simulations, BIM integration, and public health risk modelling. He holds a Gold/HEA Fellowship (2021) and has contributed to impactful research in fire safety and maritime safety. Education: PhD (University of Greenwich, 2020) in re-engineering CFD codes; MSc (Scientific and Engineering Software Technology, 1991); BSc (Physics, Reading University, 1989). Research interests include: CFD-based fire and aerosol dispersion modelling Fire safety in maritime and aviation environments BIM standards for fire engineering data sharing Public health risk assessment during disease outbreaks Naval platform survivability and damage control Evacuation simulation for high-risk environments Key activities: Co-ordinator of the annual 'Principles and Practice of Fire Modelling' CPD course Consultancy reviewer for third-party fire strategy submissions Led software engineering module COMP1714 and undergraduate/postgraduate project supervision Contributed to three successful FSEG REF submissions (2008, 2014, 2021) Current projects include: EU Horizon Healthy Sailing Project (2022–ongoing) ISSAC naval survivability tool for Australian DSTG Covid-related indoor aerosol dispersion modelling

• Wireless Communication
• 6G and Beyond Networks
• Visible Light Communication (LiFi)
• +۴ مورد دیگر

Dr. Dushyantha A Basnayaka is an Assistant Professor at the School of Electronic Engineering, Dublin City University. His research focuses on advanced wireless communication systems, including mediumband technology, visible light communication (LiFi), and MIMO systems. He explores next-generation 6G networks, Doppler effect applications, and interference mitigation strategies. His work addresses challenges in signal propagation, channel engineering, and system optimization in dynamic environments. Key research themes include: Mediumband spectrum utilization for future networks LiFi uplink transmission and infrared-based communication Doppler-assisted interference mitigation techniques MIMO systems and spatial modulation His recent publications emphasize performance analysis of mediumband systems, channel engineering methods, and multi-user communication in challenging interference scenarios. Dr. Basnayaka’s contributions span theoretical frameworks and practical implementations, aiming to enhance spectral efficiency and network reliability. He is actively involved in the Glasnevin Campus, contributing to academic and research activities in electronic engineering.

Yanqi Suمشاهده پروفایل

پژوهشگر ارشد

• Software Engineering
• Artificial Intelligence
• Automated Testing
• +۳ مورد دیگر

Yanqi Su is a postdoctoral researcher at the TUM School of Computation, Information and Technology (CIT) at the Technical University of Munich, affiliated with the Chair of Software Engineering & AI . She will soon complete her Doctorate at The Australian National University under Prof. Zhenchang Xing, following academic training at Nanjing University of Aeronautics and Astronautics. Education : PhD (in progress, ANU), Master’s/Bachelor’s in Computer Science and Technology (Nanjing University of Aeronautics and Astronautics) Research Focus : Her work centers on enhancing exploratory testing through Knowledge Graphs and Large Language Models (LLMs) , with notable contributions to test scenario generation , automated exploratory testing , and bug-component triaging . She has discovered ~300 bugs in applications like Firefox (desktop/Android), many resolved in collaboration with developers. Publication Trends : Her research spans LLM applications for GUI/code analysis , automated security testing , and AI ethics . Key subfields include model context protocols , vulnerability detection , code optimization , and human-AI collaboration in software development. Scientific Recognition : Recipient of the Distinguished Paper Award at ASE 2021 , her work appears in top-tier venues (ICSE, ASE, TSE, TOSEM).

Pietro Amentaمشاهده پروفایل

دانشیار

• Statistics
• Multivariate Analysis
• Transport Systems
• +۲ مورد دیگر

Pietro Amenta is an Associate Professor at the University of Sannio, affiliated with the Department of Law, Economics, Management and Quantitative Methods (DEMM). His academic work focuses on statistical methods, multivariate analysis, and transport systems optimization. Position: Associate Professor Department: DEMM Research: Statistics & Transport Systems Contact: amenta@unisannio.it Dr. Amenta's research interests center on Co-Inertia Analysis , Ordinal Data Handling , and Dimensionality Reduction Techniques . He has developed novel scaling methods for categorical variables and explored applications in transportation planning and social data analysis. His publications reveal trends in Transport Systems (2018-2024), Statistical Methodology (1991-2020), and Data Analysis Techniques (1994-2015). Recent work emphasizes non-negotiable group decisions in transport policy and sustainable mobility frameworks.

• Mobile and Wireless Communications
• Satellite Communications
• Underwater Communications
• +۷ مورد دیگر

Professor Jinhong Yuan is a distinguished academic serving as Professor of Telecommunications and Head of Telecommunications at the School of Electrical Engineering and Telecommunications, University of New South Wales (UNSW), Sydney, Australia. He received his B.E. and Ph.D. degrees in Electronics Engineering in 1991 and 1997, respectively. After serving as a Research Fellow at the University of Sydney from 1997 to 1999, he joined UNSW in 2000 where he has continued his academic career. Professor Yuan's extensive research portfolio spans multiple cutting-edge areas in telecommunications, with particular expertise in Mobile and Wireless Communications, Satellite Communications, Underwater Communications, and Integrated Communications and Sensing (ICAS). His work addresses critical challenges in IoT, Millimeter Waves, Information Theory and Error Control Coding, Turbo Coding and Iterative Processing, as well as Space-Time Coding, Processing and MIMO Techniques. His recent publications demonstrate significant contributions to Wideband CDMA, OFDM, and particularly to Orthogonal Time Frequency Space (OTFS) modulation systems which have emerged as promising technologies for 5G/6G communications and high-mobility scenarios. Analysis of Professor Yuan's recent publications reveals a strong trend toward addressing the challenges of high-mobility communications, particularly through OTFS modulation techniques. His work spans theoretical foundations in channel coding and information theory to practical implementations in satellite, underwater, and terrestrial wireless systems. The research demonstrates increasing integration of communications and sensing capabilities, reflecting the growing importance of Integrated Sensing and Communications (ISAC) in next-generation wireless networks. His publications consistently appear in top IEEE journals including IEEE Transactions on Communications and IEEE Transactions on Wireless Communications. Best Paper Award of IEEE Wireless Communications and Networking Conference (WCNC), Cancun, Mexico (2011) Best Paper Award of IEEE International Symposium on Wireless Communications Systems (ISWCS), Trondheim, Norway (2007) Four additional Best Paper Awards across various conferences One Best Poster Award Professor Yuan serves as the IEEE NSW Chair of the joint Communications/Signal Processing/Ocean Engineering Chapter and holds editorial positions as Associate Editor for both IEEE Transactions on Communications and IEEE Transactions on Wireless Communications. His research has resulted in over 300 journal and conference publications, two books, two book chapters, and 40 industrial reports. He is also a co-inventor of one patent on MIMO systems and two patents on low-density-parity-check (LDPC) codes, demonstrating the practical impact of his theoretical work.

Arjan Markusمشاهده پروفایل

استادیار

• Collaboration Networks
• Innovation Ecosystems
• Econometrics
• +۳ مورد دیگر

Dr. Arjan Markus is a tenured Assistant Professor at the Eindhoven University of Technology (TU/e) in the Department of Industrial Engineering and Innovation Sciences , specifically the Innovation, Technology Entrepreneurship & Marketing (ITEM) group. His research focuses on how collaboration networks and ecosystems influence innovation, using methods like econometrics , network analysis , and design science to examine dynamics from intraorganizational to multi-stakeholder levels. His work appears in journals such as Strategic Management Journal , Research Policy , and Social Networks . Ph.D. in Economics and Management, Copenhagen Business School Postdoctoral visitor, Wharton School, University of Pennsylvania Former Assistant Professor, Tilburg University He investigates innovation ecosystems across agrifood and R&I systems, including network symmetry in knowledge structures and patent approval dynamics . Current projects like REWIRE and COOPERATE address collaboration in circular agriculture and interregional knowledge ecosystems . Focus on Sustainable Development Goals (SDGs) related to zero emissions and smart cities Co-supervisor of seven Ph.D. candidates Scientific Awards : Best Reviewer Award, Academy of Management (2021) Code Re-farm Grant (2020) Diversity Fund TU/e (2019) ZonMW Sportinnovator Fase 1 (2020) He co-secures large-scale grants from Horizon Europe and NWO for projects like CUES and REWIRE , emphasizing collaboration improvement and ecosystem development . As an educator, he leads courses such as Strategic Management of Technology and Entrepreneurship in Action , having supervised over 40 master's theses and bachelor's projects.

Jan Martin Zepterمشاهده پروفایل

پژوهشگر ارشد

• Distributed Energy Resources
• Electric Vehicles
• Battery Energy Storage
• +۶ مورد دیگر

Jan Martin Zepter is a Postdoctoral Researcher at DTU's Department of Wind and Energy Systems, specializing in distributed energy resource modeling with emphasis on electric vehicle-grid integration and renewable energy systems. His work directly supports European decarbonization initiatives through projects like EV4EU and INSULAE. His academic journey includes: Ph.D. in Wind and Energy Systems, Technical University of Denmark (2019-2023) M.Sc. in Sustainable Energy Systems, Norwegian University of Science and Technology (2016-2019) Dual M.Sc. in Industrial Engineering (Electrical Engineering focus), Technical University of Berlin (2016-2019) B.Sc. in Industrial Engineering, Technical University of Berlin (2013-2017) Dr. Zepter's research bridges technical and economic domains, developing advanced models for virtual power plants , degradation-aware battery operation , and local flexibility markets . His fingerprint reveals dominant expertise in Electric Vehicle Engineering (100%), Energy Engineering (52%), and Battery Systems (46%), with growing contributions to DC Microgrids and Photovoltaics integration. He pioneers methodologies combining receding horizon optimization with real-world market constraints to enable high renewable penetration. His 15 most recent publications (2024-2025) demonstrate three critical trends: (1) Techno-economic analysis of PV-powered EV charging infrastructure, (2) Degradation-cost integration in battery market participation, and (3) Local flexibility market designs for distribution networks. These works establish novel frameworks for consumer-centric energy markets while addressing grid stability challenges through distributed resources. As an active supervisor, Dr. Zepter guides four PhD candidates—D. M. Santos (degradation-aware V2G), M. Ledro (battery-hybrid systems), A. Malkova (EV-powered plants), and X. Cao (EV management)—across European projects with combined funding exceeding €15M. His research directly contributes to UN Sustainable Development Goals 7 (Affordable Clean Energy) and 13 (Climate Action) through practical solutions for island energy systems and transport electrification. Based at DTU's Wind and Energy Systems department, he collaborates with industry partners on real-world demonstrations including Bornholm Island's virtual power plant and Madeira's replication initiatives, focusing on scalable solutions for renewable integration in constrained grids.