جست‌وجوی استاد و پژوهشگر

• Computer Networks
• Network Reliability
• Wireless Mesh Network
• +۳ مورد دیگر

Dr. Sie Teng Soh is an Associate Professor at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences. With qualifications including a PhD from Louisiana State University, he specializes in computer networks, wireless systems, and algorithm design. Research focuses on: Network topology optimization for UAV systems Energy-efficient IoT task scheduling Reliable wireless communication protocols Game-theoretic network management Green computing in software-defined networks Publication trends show advancing work in UAV network optimization, with recent articles addressing max-min rate optimization, energy harvesting in IIoT, and machine learning approaches for coverage prediction. His research consistently addresses practical challenges in wireless network deployment under real-world constraints. Teaching areas include advanced courses in network reliability and traffic engineering. Professional service includes editorial roles for IEEE Transactions on Parallel and Distributed Systems and program committee memberships for major conferences including FAST and EuroSys.

Ehsan Pashajavidمشاهده پروفایل

مدرس ارشد

• Stochastic modeling/optimisation
• Microgrids/Smartgrid
• Renewable Energy Resources
• +۳ مورد دیگر

Dr. Ehsan Pashajavid is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences, within the Faculty of Science and Engineering. His research focuses on stochastic optimization, renewable energy integration, microgrid control, and electric vehicle systems. Research interests include: Microgrid and smart grid control algorithms Renewable energy resource management Power system stability and operation Energy storage optimization Electric vehicle-grid integration His publications demonstrate significant contributions to power system resilience, with recent work emphasizing battery storage economics, fault-tolerant converters, and model predictive control for grid stability. Article trends show strong focus on renewable integration challenges and optimization techniques for modern energy systems. Awards include Senior Member status in IEEE and its Power & Energy, Industrial Applications, and Power Electronics societies. Teaching responsibilities encompass graduate courses in Renewable Power Generation Systems, Smart Grid Control, and Renewable Energy Principles.

Haoran Zuoمشاهده پروفایل

پژوهشگر ارشد

• Structural Engineering
• Structural Dynamics
• Structural Vibration Control
• +۳ مورد دیگر

Dr. Haoran Zuo is a Research Fellow and ARC DECRA Fellow at Curtin University's School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He holds a PhD (2019) and has held postdoctoral and research roles at Curtin and The Hong Kong Polytechnic University. His research focuses on structural dynamics, vibration control of offshore wind turbines, and seismic response analysis. He has secured prestigious fellowships including ARC DECRA (2024) and Marie Curie (2025). Education: PhD in Civil Engineering, Curtin University (2019) Research Interests: Structural dynamics and vibration mitigation Offshore wind energy systems Seismic response analysis Energy-harvesting control technologies Key Research Trends (2022-2025): Focused on advanced vibration control solutions for offshore wind turbines, including novel damper technologies (e.g., TTMD, KDamper), metamaterial applications, and fatigue analysis under multi-hazard conditions. His work combines experimental validation, numerical modeling, and innovative control system design. Awards: ARC DECRA Fellowship (2024-2028) Marie Skłodowska-Curie Fellowship (2025) Highly Cited Paper in Engineering (2024) Best Paper Awards (2024) Grants & Advising: Sole CI on ARC DECRA grant for hybrid wind-wave energy systems. Advises on projects involving floating platforms and structural resilience. Active in collaborative research with industry and international institutions. Labs/Teams: Part of the Curtin Research Centre for Infrastructural Monitoring & Protection, focusing on structural health monitoring and resilient infrastructure design.

Nate Apathyمشاهده پروفایل

استادیار

• Health Policy
• Health Services Research
• Health Informatics
• +۳ مورد دیگر

Nate Apathy is an Assistant Professor of Health Policy & Management at the University of Maryland School of Public Health and an Affiliated Research Scientist at the Regenstrief Institute. He holds a PhD in Health Policy & Management from Indiana University (2020) and completed a postdoctoral fellowship in health services research at the University of Pennsylvania (2022). His research focuses on health information technology's role in healthcare delivery reform, regulatory impacts on health IT innovation, and the use of EHR metadata to assess care quality. He examines organizational strategies to reduce IT-based burdens, particularly in primary care and specialty settings. His work bridges health policy, services research, and informatics, with emphasis on EHR documentation dynamics, clinician workflows, and interoperability challenges. Notable studies include analyses of physician EHR time allocation, telemedicine integration, and the impact of team-based documentation tools. He has contributed to national discussions on electronic health record legal settlements, opioid prescribing guidelines, and nursing home post-acute care specialization. Nate’s research has been published in journals such as Health Affairs , Annals of Internal Medicine , and Journal of the American Medical Informatics Association . He collaborates with institutions like the Leonard Davis Institute of Health Economics and focuses on translating informatics insights into actionable policy recommendations.

Abdulrahman Takiddinمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Cyber-Physical Systems
• +۳ مورد دیگر

Abdulrahman Takiddin is an Assistant Professor in the Department of Electrical & Computer Engineering at the Florida A&M University–Florida State University College of Engineering. He holds a Ph.D. in Electrical Engineering from Texas A&M University (2023), an M.S. in Data Analytics from Hamad Bin Khalifa University (2020), and a B.Sc. in Information Systems from Carnegie Mellon University (2014). His research focuses on cybersecurity in smart grids and cyber-physical systems, leveraging machine learning and graph neural networks to detect adversarial attacks such as false data injection and electricity theft. Key areas include resilient power systems, adversarial evasion attack mitigation, and spatio-temporal analysis of power distribution networks. Recent work emphasizes graph-based approaches for enhancing cyber resilience, including eigenvector centrality-enhanced networks and transfer learning solutions for small data scenarios. His publications address both foundational cybersecurity challenges and applied solutions for electrified transportation systems and smart grid infrastructure. Notable trends in his articles include advancements in unsupervised learning for voltage stability protection and recurrent graph networks for replay attack detection. His research also intersects with bioinformatics and artificial intelligence applications in healthcare, though the majority of his work centers on energy systems and cybersecurity.

Nidhi Hegdeمشاهده پروفایل

دانشیار

• Privacy-Preserving Machine Learning
• Algorithmic Fairness
• Distributed Systems
• +۲ مورد دیگر

Dr. Nidhi Hegde is an Associate Professor in the Department of Computing Science at the University of Alberta and a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute (Amii). Her research focuses on privacy-preserving machine learning, algorithmic fairness, and robust algorithm design for networked systems. Dr. Hegde's current research investigates differential privacy in bandit algorithms, debiasing frameworks for language models, and long-term fairness guarantees for minority groups. Her work combines theoretical foundations with practical applications in distributed systems and multi-agent learning environments. Recent publications address covariate shift effects in optimization, private matroid optimization, and reinforcement learning with functional noise. She teaches graduate courses on Responsible AI and Ethical Issues in Data Analytics, covering topics including data privacy, fairness in algorithms, interpretability, and accountability. Dr. Hegde maintains active research collaborations and previously led privacy research at Borealis AI (RBC's research institute).

Lei Liuمشاهده پروفایل

استاد

• Biostatistics
• Data Science
• Survival Analysis
• +۵ مورد دیگر

Lei Liu, PhD, is a Professor of Biostatistics, Medicine, and Statistics and Data Science at Washington University in St. Louis. He holds positions in the Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS), the Institute for Informatics, Data Science and Biostatistics (I2DB), and the Center for Biostatistics and Data Science (CBDS). His research focuses on biostatistical and data science methods, including survival analysis, longitudinal data modeling, and machine learning applications in healthcare. He collaborates with clinicians across disciplines like cardiology, ophthalmology, and addiction medicine. Dr. Liu’s work emphasizes high-dimensional omics data analysis, medical cost modeling, and joint multi-outcome models. He is an Associate Editor of Biometrics and a former member of the NIH Biostatistical Methods and Research Design Study Section. He mentors underrepresented minority researchers through the NHLBI PRIDE program.

• Evolutionary Biology
• Genetics
• Zoology
• +۹ مورد دیگر

Alfried Vogler is a Professor of Molecular Systematics with a joint appointment at Imperial College London's Department of Life Sciences (Silwood Park) and the Natural History Museum, London. His research focuses on the evolutionary and genetic mechanisms underlying insect biodiversity, particularly in beetles (Coleoptera), using advanced genomic techniques like metagenomics and environmental DNA (eDNA). He has held academic positions since 1995, becoming a Full Professor in 2006. Vogler is affiliated with the Georgina Mace Centre for the Living Planet, the Grantham Institute, and the Microbiome Network, contributing to interdisciplinary projects in ecology and conservation. Education: PhD in Bacterial Genetics (1988), University of Osnabrück, Germany MSc in Taxonomy and Biodiversity Biology degree (1984), University of Regensburg, Germany Research Interests: Vogler combines phylogenetics, population genomics, and bioinformatics to study species diversity across hierarchical levels (populations to insect orders). He explores community dynamics in complex environments, including tropical rainforests and soil ecosystems, using cutting-edge methods like metabarcoding and qPCR. His work emphasizes understanding trait evolution, dispersal constraints, and ecological interactions in biodiversity hotspots. Recent projects investigate the role of mitochondrial metagenomics in reconstructing evolutionary histories and predicting climate change impacts on communities. Academic Leadership: Since 1996, Vogler has directed the MSc in Taxonomy and Biodiversity and the MRes in Biosystematics programs, overseeing academic content and student research supervision. He also contributes to the Biodiversity, Evolution and Conservation MRes (UCL/NHM) and has been a module organizer for courses like Tree-of-Life and molecular systematics. Labs & Collaborations: Vogler leads the Molecular Systematics research group at the Natural History Museum, collaborating with Imperial College's Silwood Park campus. His work integrates with the SITE-100 project, aiming to build a global genomic framework for biodiversity synthesis. He also participates in DNAqua-Net, advancing genetic tools for aquatic ecosystem assessment.

• Machine Learning
• Data Mining
• Computer Vision
• +۳ مورد دیگر

Professor Xue Li is a faculty member in the School of Electrical Engineering and Computer Science at the University of Queensland. His research focuses on machine learning, data mining, and their applications in healthcare, materials science, and computer vision. He has authored over 300 publications, including seminal works on knowledge graph completion, video quality enhancement, and alloy design using machine learning. His work bridges theoretical advancements with real-world applications, such as clinical diagnosis andTinyML systems. Key research interests include graph representation learning, medical informatics, and efficient algorithms for multimedia data. Notable contributions include developing commonsense-enhanced relation extraction models and frameworks for compressed video reconstruction. His research also addresses challenges in federated learning and privacy-preserving genomics. Prof. Li has collaborated extensively with industry and academia, contributing to projects in RFID systems, electronic nose pattern recognition, and cybersecurity. His work is published in top-tier venues like IEEE Transactions and ACM conferences. Despite no listed awards, his prolific output underscores academic impact.

Alexander Budzierمشاهده پروفایل

پژوهشگر ارشد

• Project Management
• IT-enabled Change
• Risk Management
• +۵ مورد دیگر

Alexander Budzier is a Research Fellow in the Department of Technology and Operations Management at Saïd Business School, University of Oxford. He specializes in managing projects across IT, infrastructure, energy, and mega-events, with a focus on risk mitigation and systems thinking. His roles include teaching on the MSc for Major Programme Management, MBA, and the Major Project Leadership Academy. Education: PhD from Saïd Business School (2014). Prior experience includes roles at T-Mobile International and McKinsey's Business Technology Office in Düsseldorf and Chicago, advising on IT and operations strategy. Research interests center on IT-enabled change, project setups, and risk analysis. Notable contributions include work on cost overruns in IT projects, the uniqueness trap in project management, and sustainable development via mega-events like the Olympics. Publications span journals like Harvard Business Review , iScience , and Event Management , with a focus on megaprojects, risk, and digital transformation. He has advised governments and corporations on infrastructure investments and project governance, emphasizing evidence-based decision-making.

Amiya Nayakمشاهده پروفایل

استاد

• Fault-Tolerant Computing
• Distributed Systems
• Ad hoc and Sensor Networks
• +۷ مورد دیگر

Amiya Nayak is a Professor at the School of Electrical Engineering and Computer Science of the University of Ottawa. His research focuses on Fault-Tolerant Computing , Distributed Systems , and Ad hoc and Sensor Networks . He specializes in cybersecurity, IoT security, blockchain integration, and machine learning applications in healthcare and vehicular networks. His work addresses challenges in secure communication protocols, distributed learning frameworks, and energy-efficient network designs. Notable research areas include: IoT Security : Developing frameworks for threat detection, privacy-preserving systems, and blockchain-empowered IoT defenses. Federated Learning : Enhancing healthcare predictions and IoT management through decentralized, privacy-aware machine learning. Vehicular Networks : Securing Vehicle-to-Everything (V2X) communication and optimizing QoS in cooperative internet of vehicles (IoV). Network Optimization : Leveraging deep reinforcement learning and graph neural networks for WDM network restoration and edge computing. His publications (2020–2025) highlight contributions to: Secure authentication protocols in medical sensor networks. AI-driven metaverse security solutions. Decentralized energy trading using NFTs. Energy-efficient sleep scheduling in wireless body area networks (WBANs). Nayak holds a Ph.D. and is a P.Eng. (Professional Engineer). His work bridges theoretical computer science with practical applications in telecommunications and healthcare systems.

Gualbert Oude Essinkمشاهده پروفایل

دانشیار

• Hydrogeology
• Coastal Groundwater Systems
• Saltwater Intrusion
• +۶ مورد دیگر

Dr. Gualbert Oude Essink is an Associate Professor at the Faculty of Geosciences , Department of Physical Geography at Utrecht University . He is also a senior hydrogeologist at Deltares, specializing in coastal groundwater systems, saltwater intrusion, and delta sustainability. His work focuses on improving freshwater availability in vulnerable coastal zones under climate change, subsidence, and anthropogenic pressures. Dr. Essink holds a PhD in Civil Engineering from Delft University of Technology and has extensive experience in applied hydrogeology. He leads research projects globally, including in the Netherlands, Egypt (Nile Delta), Bangladesh (Kulna region), Singapore, and Vietnam (Mekong Delta). Key initiatives include GO-FRESH (Aquifer Storage and Recovery) and Rise and Fall (Mekong Delta subsidence strategies). His research integrates modeling, geophysical surveys, and stakeholder engagement. Notable areas include variable-density groundwater flow, airborne electromagnetic surveys for salinity mapping, and sustainable groundwater management. He supervises multiple PhD candidates and teaches at IHE Delft, contributing to global water education. Dr. Essink has authored over 100 peer-reviewed articles, focusing on delta sustainability, climate impacts, and groundwater systems. His work bridges academia and practice, addressing freshwater security challenges in coastal regions through innovative solutions like managed aquifer recharge and saltwater intrusion mitigation.

Rajeev Sahayمشاهده پروفایل

استاد آموزشی

• Machine Learning
• Wireless Communications
• Networking
• +۴ مورد دیگر

Rajeev Sahay is an Assistant Teaching Professor in the Department of Electrical and Computer Engineering at the University of California San Diego (UCSD), affiliated with the Jacobs School of Engineering. He holds a Ph.D. and M.S. from Purdue University (2022 and 2021) and a B.S. from the University of Utah (2018). Prior to UCSD, he worked as a Senior Machine Learning Software Engineer at Saab, Inc., and taught courses at Purdue, earning the Purdue Engineering Dean’s Teaching Fellow award in 2021. His research bridges machine learning and networking, focusing on social learning networks (SLNs) for personalized education and robust wireless communications in adversarial environments. Key areas include federated learning for privacy preservation, adversarial attack mitigation, and next-generation 6G wireless systems. His work emphasizes data-driven methodologies to enhance learning outcomes and secure communication networks against vulnerabilities. Dr. Sahay’s teaching spans undergraduate and graduate courses in machine learning, data science, and programming languages (C/C++/Python), with a passion for tailoring curricula to student needs. His publications reflect expertise in federated learning, adversarial defense mechanisms, and signal processing, with recent contributions to AI-assisted education and robust wireless systems. Scientific Awards: Purdue Engineering Dean’s Teaching Fellow (2021) Teaching and Research Interests: Machine Learning Pedagogy Adversarial Robustness in ML Systems Federated Learning Applications Social Learning Network Analysis 6G Wireless Communication Security

• Artificial Intelligence
• Machine Learning
• Game Theory
• +۷ مورد دیگر

Prof. Tansu Alpcan is a Professor and Reader in the Department of Electrical and Electronic Engineering at The University of Melbourne, Australia. He holds a PhD from the University of Illinois at Urbana-Champaign (UIUC) and has held academic positions at Technical University Berlin and Deutsche Telekom Laboratories. His research focuses on AI/ML applications in engineering, game theory, cybersecurity, Industry 4.0, quantum machine learning, smart grids, and communication networks. Education: PhD in Electrical and Computer Engineering (UIUC, 2006); MSc (UIUC, 2003); BEng (Bogazici University, 1999). Research interests include adversarial machine learning, cybersecurity games, quantum computing, and renewable energy systems. Authored over 200 papers and two books, including Network Security: A Decision and Game Theoretic Approach (Cambridge, 2011). Recipient of IEEE Senior Membership (2012) and multiple best paper awards. He leads the WILAB and has secured grants such as the ARC Training Centre in Optimisation Technologies. Current projects include quantum machine learning, adversarial reinforcement learning, and smart grid modeling. Supervised 17 PhD and 3 Master’s students.

Kenneth Edwin Barkerمشاهده پروفایل

استاد

• Privacy Preserving Data Repositories
• Database Management Systems
• Data Privacy and Security
• +۴ مورد دیگر

Dr. Kenneth Edwin Barker is a Professor in the Department of Computer Science within the Faculty of Science at the University of Calgary, where he also serves as Director of the Institute for Security, Privacy and Information Assurance (ISPIA). His academic career spans several decades with significant contributions to database systems and privacy research. Dr. Barker earned his B.S. and M.S. in Computer Science from the University of Calgary in 1982 and 1984 respectively, followed by a Ph.D. in Computer Science from the University of Alberta in 1990. His educational background established the foundation for his extensive research career in database systems and information security. His primary research interests focus on Privacy Preserving Data Repositories , with specific attention to protecting privacy in mobile applications, understanding privacy's impact on data analytics, and architecting database management systems that inherently respect user privacy. His work also extends to distributed database environments, integration of legacy systems, and multidatabase environments. Dr. Barker's research bridges theoretical foundations with practical applications, making significant contributions to how privacy is implemented in real-world systems. An analysis of his recent publications reveals a strong trend toward practical privacy-preserving techniques for cloud data, social networks, and location-based services. His work consistently addresses the tension between data utility and privacy protection, developing innovative methods to maintain data value while safeguarding personal information. The publications span multiple subfields including encrypted search, graph privacy, high-dimensional data privacy, and privacy metrics. Best Paper Award at DBSec 2012 Best Paper Award at CODASPY 2012 Best Paper at BNCOD 2009 Dr. Barker has been instrumental in establishing privacy research infrastructure at the University of Calgary through his leadership of ISPIA. His research has attracted significant funding from various sources supporting privacy and security initiatives. While specific grant details aren't provided in the text, his extensive publication record indicates sustained research funding throughout his career. He has collaborated extensively with researchers both within and outside the University of Calgary, particularly with R. Alhajj and other colleagues on numerous projects. As Director of ISPIA, Dr. Barker oversees a research environment focused on advancing security and privacy technologies. The institute serves as a hub for interdisciplinary research, bringing together computer scientists, social scientists, and legal experts to address complex privacy challenges. His leadership has positioned the University of Calgary as a significant player in privacy research within Canada.