جست‌وجوی استاد و پژوهشگر

Shyh Wei Tengمشاهده پروفایل

دانشیار

• Image Processing
• Machine Learning
• Bioinformatics
• +۳ مورد دیگر

Assoc Prof Shyh Wei Teng is an Associate Professor and Deputy Dean at Federation University Australia's Institute of Innovation, Science and Sustainability (IISS). He holds a Bachelor of Computing (First-class Honours) and PhD in Information Technology from Monash University (2004), and a Graduate Certificate in Higher Education (2008). His research focuses on image processing, machine learning, bioinformatics, and computer vision, with notable contributions to LiDAR-based building extraction, SIFT algorithm optimization, and multimodal image registration. He has secured significant grants, including an Australian Research Council (ARC) Discovery Project (2013). Prof Teng has supervised numerous PhD and master’s students, contributing to advancements in image retrieval, clustering algorithms, and biomedical applications. His work has been published in top-tier journals like Pattern Recognition and Neurocomputing , and he actively reviews for IEEE conferences. He taught courses in database systems, project management, and systems analysis, receiving teaching and community engagement nominations. Research interests span computational techniques for medical imaging, contour-based corner detection, and machine learning applications in remote sensing. His labs and collaborations include projects on augmented reality for education and ecological data analysis.

Rebecca Frankمشاهده پروفایل

استادیار

• Digital Curation
• Digital Preservation
• Digital Repositories
• +۶ مورد دیگر

Rebecca Frank (she/her) is an Assistant Professor at the University of Michigan School of Information and holds affiliations with the Einstein Center Digital Future (Berlin) and the Inter-university Consortium for Political and Social Research. Her research examines how risk is socially constructed in digital repository certification processes, focusing on open data, digital preservation, and ethical information management. She teaches graduate courses in digital curation and preservation. PhD, University of Michigan School of Information (2018) MSI, University of Michigan (2012) BA, Organizational Studies, University of Michigan (2010) Her work addresses social and ethical barriers to digital information preservation, sharing, and reuse through projects like SCoR-TDR (Social Construction of Risk in Trustworthy Digital Repositories) and Citizen-Based Monitoring for Peace & Security (analyzing satellite imagery for conflict verification). Current research with the InfraLab Berlin investigates risk perception in public infrastructure data work. Recent publications (2024-2025) explore CoreTrustSeal certification, satellite image analysis for citizen monitoring, and qualitative method reporting standards. Her 2024 Journal of Documentation article develops frameworks for repository risk assessment, while 2025 conference papers examine feminist data approaches and collaborative syllabus development. Supported by grants from the National Science Foundation (US), German Foundation for Peace Research, Einstein Center Digital Future, and Australian Academy of Science, Frank collaborates with international institutions including Princeton University, Berliner Hochschule für Technik, and Humboldt-Universität zu Berlin. She organizes workshops on data feminism and digital preservation ethics.

Nelson Villoriaمشاهده پروفایل

دانشیار

• International Trade
• Agricultural Policy Analysis
• Global Land Use
• +۴ مورد دیگر

Nelson B. Villoria is an Associate Professor in the Department of Agricultural Economics at Kansas State University . His research focuses on the intersections of international trade, development, and environmental sustainability, particularly addressing climate impacts on global agricultural systems and land-use policy. He holds a B.S. in Agronomist from Universidad Central de Venezuela (1995), M.S. in Agricultural Economics from Cornell University (2000), and Ph.D. from Purdue University (2009). Major research areas include climate-driven cropland changes, trade frictions and food price stability, and policies to mitigate deforestation. His work emphasizes spatially explicit data analysis, leveraging tools like GTAPShape and FlexAgg2.0 for geospatial modeling. Recent studies explore how technological progress and trade policies influence global land-use patterns and food security. Publications highlight themes such as yield variability under climate change, land supply elasticity, and the leverage of trade agreements (e.g., EU policies on Brazilian deforestation). His contributions bridge theoretical frameworks with applied policy analysis, often using computable general equilibrium (CGE) models and geospatial data infrastructure. Villoria has held roles like Associate Director for Educational Outreach at Purdue’s Center for Global Trade Analysis. His research consistently addresses global sustainability challenges through interdisciplinary approaches, integrating economics, environmental science, and geospatial technologies.

Bala Venkateshمشاهده پروفایل

استاد

• Power Systems Analysis
• Optimization
• Fuzzy Optimization
• +۴ مورد دیگر

Dr. Bala Venkatesh is a Professor in the Department of Electrical and Computer Engineering and Academic Director of the Centre of Urban Energy at Toronto Metropolitan University. He has held academic positions at institutions including Ryerson University (2008–present), the University of New Brunswick (2005–2007), Multimedia University, Malaysia (2001–2004), and Anna University, India (1994–2000). His research focuses on Power Systems Analysis, Fuzzy Optimization, and renewable energy integration. He has authored over 100 refereed papers and secured research grants exceeding $10 million. Dr. Venkatesh is a Senior Member of IEEE and a registered Professional Engineer in Ontario. Education and Professional Experience: Postdoctoral work at Crompton Greaves, Mumbai (1993) Lecturer, Anna University, India (1994–2000) Associate Professor, Multimedia University, Malaysia (2001–2004) Associate Professor, University of New Brunswick (2005–2007) Research Interests: Dr. Venkatesh specializes in fuzzy optimization applications to power systems, distribution network analysis, and energy storage integration. His work emphasizes practical solutions for grid stability, renewable energy utilization, and transactive energy systems. Recent projects include DER aggregation models, smart grid optimization, and fault diagnosis in microgrids. Grants and Recognition: He leads the Power and Energy Analysis Research Lab at Toronto Met and has secured substantial funding for projects in smart grids and energy systems. Notable awards include IEEE Senior Membership and Professional Engineer licensure in Ontario. His work has been applied in consulting projects across India and Canada.

Heidi Webberمشاهده پروفایل

استاد

• Climate Risk Assessment
• Crop Modeling
• Plant Stress Physiology
• +۳ مورد دیگر

Prof. Heidi Webber is a leading agricultural scientist at the Leibniz Centre for Agricultural Landscape Research (ZALF), serving as Co-Head of Program Area 3 'Agricultural Landscape Systems' and Head of the 'Integrated Crop Production Systems Analysis' working group. Her research focuses on climate risk assessment, crop stress modeling, and sustainable agronomic systems. She holds a Diplom-Agraringenieurin degree and has extensive experience in interdisciplinary studies combining biophysical and socio-economic analyses. Her expertise includes modeling plant growth under abiotic stresses and developing resource-efficient cultivation strategies. Notable contributions involve the AgMIP-Wheat initiative, high-yielding trait experiments, and climate-resilient crop systems in diverse regions like West Africa, South Korea, and Europe. She co-leads international projects addressing climate change impacts on agriculture and leads modeling efforts for crop diversification and adaptation strategies. Key research themes include: Climate risk assessment frameworks Multi-model ensemble approaches for crop yield prediction Abiotic stress tolerance mechanisms in cereals Climate-smart agricultural practices Agroecological transition in smallholder farming systems Her work bridges field experiments with advanced computational models, emphasizing data-driven solutions for sustainable intensification. Current projects explore index-based crop insurance, soil carbon dynamics, and the transformation of farming systems toward silicon-enhanced resilience.

Reda BELLAFQIRAمشاهده پروفایل

پژوهشگر

• Federated Learning
• Homomorphic Encryption
• Data Security
• +۳ مورد دیگر

Reda BELLAFQIRA is an Enseignant Chercheur (Researcher) at IMT Atlantique's Data Science Department, based in Brest. His work focuses on securing sensitive data processing in distributed systems, combining cryptography with machine learning techniques. Key areas include federated learning, homomorphic encryption, and watermarking for intellectual property protection. He has contributed to privacy-preserving frameworks in healthcare and IoT applications, emphasizing secure collaborative data analysis without compromising confidentiality. Research Interests: Secure federated learning architectures and robustness against adversarial attacks Cryptography applications in AI, including homomorphic encryption for encrypted data processing Watermarking techniques for model integrity and ownership in distributed environments Privacy-preserving methods for healthcare data (e.g., EHRs, genomics) IoT cybersecurity and embedded system security for medical devices Key Contributions: His 2025 work on blockchain-enhanced watermarking for federated learning and 2023 research on automated EHR de-identification exemplify his focus on practical security solutions. Recent trends show increasing emphasis on interdisciplinary approaches merging cryptography with healthcare informatics and IoT systems. Labs/Teams: Active in IMT Atlantique's Data Science Department research groups, collaborating on EU-funded projects related to federated learning in healthcare and secure IoT ecosystems.

Zebang Shenمشاهده پروفایل

مدرس

• Optimization
• Machine Learning
• Data Science
• +۳ مورد دیگر

Dr. Zebang Shen serves as a Lecturer in the Department of Computer Science at ETH Zurich, affiliated with the Institute for Machine Learning (Institut für Maschinelles Lernen). His research activities are centered at Andreasstrasse 5, 8092 Zürich, Switzerland, with teaching responsibilities confirmed for the Autumn Semester 2025. His primary research domains include Optimization, Machine Learning, and Data Science, with specialized focus on Federated Learning, Stochastic Optimization, and Reinforcement Learning. Shen develops algorithmic solutions for projection-free optimization, minimax problems, and diffusion model applications, emphasizing theoretical guarantees alongside practical implementations in distributed learning environments. Analysis of his 2021-2025 publications reveals consistent innovation in optimization frameworks for machine learning, particularly in federated settings where privacy-utility tradeoffs and straggler resilience are addressed. His work bridges mathematical rigor (e.g., Poincaré inequalities, McKean-Vlasov equations) with scalable algorithms for real-world data science challenges. No scientific awards were documented in the available sources. While the sources confirm his faculty role and publication record, specific details regarding student advising, grant funding, or laboratory leadership were not provided. His current teaching activities indicate ongoing academic engagement at ETH Zurich. Shen operates within ETH Zurich's Institute for Machine Learning, contributing to the Department of Computer Science's research ecosystem focused on advancing machine learning theory and applications.

• Edge Computing
• Internet of Things
• Vehicular Networks
• +۵ مورد دیگر

Muhammad Bilal is an Associate Professor at Zhejiang University's School of Computer Science, Department of Computer Science and Technology. His research spans multiple cutting-edge domains in computer science and engineering, with a particular focus on edge computing, Internet of Things, and vehicular networks. His research interests include Edge Computing , Internet of Things , Vehicular Networks , Federated Learning , Digital Twins , and Cloud Computing . His work addresses critical challenges in resource allocation, latency optimization, privacy preservation, and intelligent decision-making in distributed computing environments. He has made significant contributions to developing novel frameworks for service caching, computation offloading, and secure data processing in next-generation networks. His recent publications reveal a strong trend toward integrating artificial intelligence with edge and cloud infrastructure, particularly focusing on privacy-preserving techniques and resource-efficient algorithms. His work spans applications from intelligent transportation systems to healthcare monitoring and meteorological services, demonstrating the versatility and real-world impact of his research. Dr. Bilal has established a prolific publication record with numerous high-impact papers in top-tier journals and conferences, reflecting his active engagement in the academic community. His collaborative approach is evident through extensive co-authorship networks, particularly with researchers in China, Pakistan, and internationally.

• Blockchain Technology
• Edge Computing
• Federated Learning
• +۴ مورد دیگر

Pubudu N. Pathirana is a Professor at the University of Melbourne's College of Engineering, specializing in Blockchain Technology, Edge Computing, Federated Learning, and Machine Learning for Healthcare . His work bridges theoretical advancements with practical applications in smart cities, cyber-physical systems, and medical diagnostics. Education : PhD in Electrical Engineering, Monash University His research focuses on privacy-preserving machine learning and blockchain integration with edge networks , demonstrated through collaborations with Dinh C. Nguyen, Minh K. Quan, and Bipasha Kashyap. Key contributions include quantum-enhanced models for acoustic classification and federated learning frameworks for IoT environments. Recent publications (2025) highlight advancements in spatio-temporal traffic modeling , adaptive privacy clipping , and secure client aggregation . Earlier work (2021-2024) explored applications in Covid-19 detection , Friedreich Ataxia severity classification , and entropy-based cerebellar ataxia analysis . He mentors students like Ali Reza Sattarzadeh and Kanishka Ranaweera, with grants supporting projects on blockchain-enhanced federated learning and quantum-inspired edge computing . His lab collaborates with institutions such as Monash University and the Florey Institute of Neuroscience.

• Conflict Resolution
• Environmental Policy
• Climate Change
• +۷ مورد دیگر

Keith Hipel is an Adjunct Professor at the University of Waterloo's Department of Systems Design Engineering, within the Faculty of Engineering. His work focuses on systems analysis, conflict resolution methodologies, and environmental policy. He specializes in applying the Graph Model for Conflict Resolution to real-world disputes involving water resources, climate change impacts, and resource management. Research interests include: Development of conflict resolution frameworks Climate change adaptation strategies Multi-stakeholder decision-making systems Environmental policy design Systems thinking applications Recent publications emphasize: strategic analysis of water allocation disputes, climate policy equity, wildfire management, and aggregate mining conflicts. His work often combines game theory, multi-criteria decision analysis, and fuzzy logic to address complex socio-technical systems. Notable projects include analyzing the Cauvery River dispute, Alberta wildfire management strategies, and Ontario's aggregate mining controversies. Hipel collaborates internationally on issues like Himalayan glacier melt impacts and transboundary water governance. His methodologies bridge engineering and social sciences, focusing on creating practical tools for resolving conflicts in environmental and infrastructure domains through structured decision-making processes.

Martin Klapezمشاهده پروفایل

استادیار

• Computer Networking
• Vehicular Communication Systems
• 5G Networks
• +۴ مورد دیگر

Martin Klapez is an Assistant Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Engineering Enzo Ferrari. He holds an M.S. in Theoretical Computer Science from the University of Bologna and a Ph.D. in Information and Communication Technologies (ICT) from the University of Modena and Reggio Emilia. His primary research focuses on computer networking, particularly safety-related V2X communications, public safety networks, and energy-efficient 5G architectures. He leads the UNIMORE Networking Lab and is involved in experimental evaluations of protocols like IEEE 802.11p for vehicular networks, TCP performance optimization over wireless, and green 5G design. Key research contributions include studies on TCP congestion control algorithms, energy footprint analysis of multi-RAT cellular systems, and field trials for safety-critical applications. His work bridges theoretical networking principles with practical implementations, including experiments in data visualization and smart infrastructure testing. Klapez has taught advanced courses on SDN, network emulation, and ns-3 tool usage at the university. He collaborates actively with international conferences and publishes widely in IEEE journals and forums. His technical expertise spans network softwarization, resource pooling in SDN, and middleware development for mission-critical networks. Current projects include LTE-V2X field tests for vulnerable road user safety and optimizing TCP modules like BBR and Small Queues for wireless environments. He contributes to standardization efforts through practical validation tools like Earthcloud for IoT seismic alerts.

KOUNTOURIS Mariosمشاهده پروفایل

استاد

• Communication Theory
• Machine Learning for Wireless Communications
• Low Latency Networking
• +۳ مورد دیگر

Marios Kountouris is a Professor at EURECOM in the Department of Communication Systems. He holds a Ph.D. in Electrical Engineering from Telecom ParisTech (France), an M.S. from Telecom ParisTech, and a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (Greece). His career includes roles as Principal Scientist at Huawei Technologies (France), Assistant/Associate Professor at CentraleSupélec (France), Adjunct Professor at Yonsei University (South Korea), and Post-doctoral researcher at the University of Texas at Austin (USA). His research focuses on communication theory, machine learning for wireless communications, low latency networking, and stochastic modeling. Notable contributions include work on ultra-reliable low-latency communication (URLLC), network densification, and semantic communication frameworks. Distinctions: IEEE Communication Society Young Author Best Paper Award 2020 2016 IEEE ComSoc Communication Theory Technical Committee Early Achievement Award 2013 IEEE ComSoc Outstanding Young Researcher Award (EMEA Region) Recent research trends emphasize semantic-aware resource allocation, federated learning in wireless networks, and next-generation waveforms like AFDM. His articles explore optimization frameworks, real-time systems, and AI-driven telecom innovations.

Alireza Furutanpeyمشاهده پروفایل

پژوهشگر

• Edge Computing
• Edge Intelligence
• Distributed Inference
• +۳ مورد دیگر

Alireza Furutanpey is a University Assistant (PreDoc Researcher) at TU Wien's Distributed Systems Group within the Institute of Information Systems Engineering, holding a Master's degree with distinction. His academic role combines research in distributed systems with teaching responsibilities for core computer science courses. His educational background includes: Bachelor of Science (BSc) Master of Science (Dipl.-Ing.) with distinction Furutanpey's research centers on Edge Computing and Edge Intelligence, specializing in Distributed Inference, Neural Data Compression, and AI-Systems integration. He pioneers techniques for neural feature compression in satellite/edge environments and develops frameworks for federated learning orchestration under communication constraints. His work bridges theoretical AI with practical system implementation, focusing on resource-constrained scenarios where bandwidth and computational efficiency are critical. Analysis of his 15+ publications reveals dominant trends in neural compression for distributed systems (60%), federated learning optimization (25%), and serverless edge frameworks (15%). Key contributions include solving satellite downlink bottlenecks through feature compression and enabling adaptive inference in heterogeneous edge networks, with methodologies increasingly incorporating generative modeling and robustness against adversarial attacks. Scientific Awards: None documented in available sources. He actively supervises master's theses, guiding students on adversarial machine learning, neural compression, and image retrieval systems. His research is supported through major projects: AloTwin (2023-2025) focusing on edge intelligence, INTEND (2024-2026) on industrial IoT, and TEADAL (2022-2025) on federated learning. He serves as a reviewer for 15+ IEEE/ACM venues including IEEE Transactions on Mobile Computing and ICDCS. Furutanpey operates within TU Wien's Distributed Systems Group, which specializes in edge-cloud continuum research. The team develops tools like faas-sim for serverless edge simulation and explores quantum-classical hybrid architectures, maintaining strong industry collaborations in industrial IoT and satellite communications.

Emilia Urbanekمشاهده پروفایل

مدرس ارشد

• Soil Science
• Climate Change Mitigation
• Soil Carbon Dynamics
• +۳ مورد دیگر

Dr. Emilia Urbanek is a Senior Lecturer in the School of Biosciences, Geography and Physics at Swansea University. A Polish-born soil scientist, she focuses on the role of soils in climate change mitigation, particularly studying soil water repellency and its impact on carbon cycling after fires or droughts. Education: MSc in Environmental Protection (2002) from Lublin University of Technology, PhD in Soil Science (2006) from University of Kiel, Germany Research Expertise: Soil water repellency, CO2 emissions from soil, fire-affected soils, climate change mitigation strategies Her research explores how water availability interacts with soil carbon dynamics, emphasizing hydrophobic soil behavior post-disturbance. Recent work includes interdisciplinary collaborations on consumer sustainability decisions and climate emergency education tools. She has supervised PhD projects on vegetation flammability, enhanced rock weathering, and peatland restoration, often partnering with experts like Prof Stefan Doerr and Prof Bernd Kulessa. Scientific Honors: Royal Society Dorothy Hodgkin Fellowship (2012-2018, £450k) Royal Society Research Grant 'MetFlux' (2013-2016, £105k) Leverhulme Trust Early Career Fellowship (2012) Royal Society Enhancement Award (2017, £14.5k) Dr. Urbanek actively engages in public outreach as a co-organizer of Swansea Soapbox Science and through school collaborations like the Royal Society-funded 'Soils are great!' project. She teaches modules including Introduction to Earth Systems and Sustainable Land Management , integrating fieldwork and data analysis into her pedagogy.

Neoptolemos Johnمشاهده پروفایل

استاد

• Pancreatic Cancer
• Surgical Oncology
• Genetics of Pancreatic Diseases
• +۳ مورد دیگر

Professor Neoptolemos John is a world-leading pancreatic cancer specialist and Professor of Surgery at the University of Heidelberg since 2017. Previously, he held the Chair of Surgery at the University of Liverpool from 1996, serving as Head of Department and leading major research initiatives. His expertise spans clinical and translational research in pancreatic cancer, acute/chronic pancreatitis genetics, and surgical innovation. Current Position: Professor of Surgery, Department of General, Visceral and Transplantation Surgery, University of Heidelberg Past Positions: Director of Cancer Research UK Liverpool Centre (2009), Scientific Director NIHR Pancreas Biomedical Research Unit (2007), and multiple leadership roles in clinical trials and cancer centers. His research focuses on optimizing pancreatic cancer treatment through adjuvant/neoadjuvant therapies, biomarker discovery (e.g., hENT1), and minimally invasive surgical techniques. He pioneered the ESPAC trials, which established global treatment guidelines for resectable pancreatic cancer. Awards include the Henry Lynch Award (2018), Lifetime Achievement Award from the European Pancreatic Club (2013), and honorary professorships at Nanjing Medical University. He has secured £55M in grants and authored over 289 invited lectures. Grants: NIH Senior Investigator, Department of Health Platinum Award (2004) Leadership: Clinical Lead for Pancreas Cancer Guidelines, Medical Advisory Board member for Pancreas Cancer UK He collaborates internationally, including roles at Nanjing Medical School and University as a Specially Appointed Professor.