جستجوی استاد راهنمای دانشگاهی

• Energy Systems Modelling
• Multi-energy Systems Integration
• Renewable Energy Integration
• +۴ مورد دیگر

Goran Strbac is a Professor of Energy Systems at Imperial College London's Faculty of Engineering, holding the Chair in Electrical Energy Systems. He leads the Department of Electrical and Electronic Engineering and directs the joint Imperial-Tsinghua Research Centre on Intelligent Power and Energy Systems. His roles include IPCC WG 3 Leading Author, OFGEM RIIO-2 Challenging Group Member, and member of multiple EU energy platforms. Strbac's research focuses on multi-energy systems integration, energy market design, renewable integration, distributed energy resources, and grid resilience. Notable contributions include whole-energy system modeling across operation and investment scales, market mechanisms for flexibility services, and security assessments for low-carbon infrastructure. His work emphasizes resilience and decarbonization, with over 500 publications and 4 co-authored books. He advises governments and regulatory bodies on energy policy, including contributions to UK Smart System Forum and European Technology and Innovation Platforms. His recent articles explore AI-driven grid optimization, hydrogen integration, and transactive energy systems. Strbac leads major initiatives like the UK Centre for Grid Scale Energy Storage and chairs resilience-focused research clusters. His research bridges academia and industry, informing policy through rigorous systems analysis and innovative modeling frameworks.

Michael C.L. CHAUمشاهده پروفایل

استاد

• Business Analytics
• Artificial Intelligence
• Web Mining and Social Media
• +۸ مورد دیگر

Professor Michael C.L. CHAU serves as Professor and Deputy Area Head of Innovation and Information Management at The University of Hong Kong's Faculty of Business and Economics. He also holds the position of Associate Director at the HKU HKJC Centre for Suicide Research and Prevention, and serves on the HKU Senate and Court. His academic journey includes a Ph.D. in Management Information Systems from the University of Arizona and a B.Sc. in Computer Science (Information Systems) from the University of Hong Kong. Dr. Chau's research spans business analytics, artificial intelligence, web mining, fintech, smart health, and security informatics. His work focuses on applying data/text/web mining techniques to business, education, and social domains. He leads the Artificial Intelligence Research Group at HKU Business School, which has secured significant funding from the Hong Kong Research Grants Council, Food and Health Bureau, and other agencies for projects including 'The Invisible Hand in Crowdfunding' and 'Factors Moderating the Predictive Power of Social Media Sentiment on Stock Returns'. His publication portfolio includes over 150 articles in premier journals like MIS Quarterly, JMIS, and IEEE Transactions, with recent work exploring large language models, hate speech detection, and disaster-related social media analysis. His research demonstrates strong interdisciplinary connections across computer science, information systems, and business applications. INFORMS ISS Design Science Award (2020) IEEE ITSS Leadership Award in Intelligence and Security Informatics (2020) AIS Sandra Slaughter Service Award (2016) HKU Outstanding Young Researcher Award (2014) Faculty Research Postgraduate Supervision Award (2020 & 2025) Cited over 9,400 times (h-index = 47) Dr. Chau actively mentors doctoral students and has supervised numerous PhD graduates who now hold academic positions at institutions including Fudan University, Xi'an Jiaotong-Liverpool University, and the University of Maryland. His research grants portfolio demonstrates sustained funding success across diverse areas including blockchain, mental health applications, and social media analytics. The Artificial Intelligence Research Group he leads maintains strong industry connections through projects with Hong Kong Red Cross and the Hospital Authority.

• Secure Decentralized Systems
• Blockchain Technology
• Systems Security
• +۳ مورد دیگر

Prof. Bryan Ford leads the Decentralized/Distributed Systems (DEDIS) lab at EPFL. He focuses on secure decentralized systems, including blockchain technology, privacy, and systems security. He earned his Ph.D. from MIT and held faculty positions at Yale University and EPFL. His work spans distributed consensus protocols, peer-to-peer networking, and privacy-preserving systems. Key projects include QuePaxa (timeout-free consensus), UIA (global connectivity for mobile devices), and MedCo (secure healthcare data sharing). He advises numerous PhD students and contributes to open-source projects like Bitcoin collective signing and privacy networks like Riffle. Education: Ph.D., MIT; Postdoctoral work at Yale Research interests include blockchain scalability, consensus algorithms, and cryptographic privacy. His lab develops systems like TRIP for coercion-resistant voting and F3B to mitigate blockchain front-running. His work on NAT traversal and peer-to-peer protocols (e.g., STUN/ICE) remains foundational in network architecture. He emphasizes practical, auditable security solutions such as CertiKOS and atomic cross-chain transactions (Atom). Notable contributions: CoSi (collective signing), OmniLedger (sharded blockchain), and privacy-preserving protocols like PURBs (Protected Unsealable Recursive Boxes). His lab collaborates with Swiss Post to audit e-voting systems and designs democratic cryptocurrencies like PoPCoin.

• Computer Science
• Networking
• Telecommunications
• +۴ مورد دیگر

Prof. Liam Murphy is a Full Professor of Computer Science & Informatics at University College Dublin (UCD) and Director of the Performance Engineering Laboratory. He holds a B.E. from UCD, M.Sc. and Ph.D. from UC Berkeley. His research focuses on performance engineering of networks, software systems, and multimedia transmissions. He has published over 150 peer-reviewed papers and is an IEEE member and Fellow of the Irish Computer Society. Education: B.E. in Electrical Engineering, UCD (1985) M.Sc. & Ph.D. in Electrical Engineering & Computer Sciences, UC Berkeley (1988, 1992) Research Interests: Dynamic resource allocation in networks Cloud computing efficiency Software performance engineering Wireless multimedia systems Quality of Service (QoS) optimization Recent work emphasizes energy-efficient cloud workflows, multi-objective data center optimization, and decentralized traffic simulation. Grants & Awards: Fellow of the Irish Computer Society (2007) Conference Paper Awards (2004, 2002, 2001) Principal Investigator in multiple funded projects (e.g., EU-funded traffic simulation, cloud resource allocation) Advising & Labs: Directed 24 Ph.D. and 8 M.Sc. students. Leads the Performance Engineering Laboratory (PEL), focusing on distributed systems, cloud efficiency, and network performance. Collaborates on industry-relevant projects like crovan (UCD/DCU campus company). Teaching: Coordinates courses on computer science fundamentals, distributed systems performance, and software engineering at UCD.

• Smart Grids
• Distributed Control Systems
• Renewable Energy Integration
• +۶ مورد دیگر

Geert Deconinck is a full professor at KU Leuven , leading the Electrical Energy Systems and Applications (ELECTA) research group within the Department of Electrical Engineering (ESAT). He also serves as scientific leader of the EnergyVille research center's algorithms domain, focusing on smart electrical networks and thermal systems. M.Sc. and Ph.D. from KU Leuven Head of ELECTA since 2012 (10 professors, 8 postdocs, 70+ PhDs) Over 8 million EUR research budget in last 5 years 44 completed PhDs and 10 current advisees IEEE Transactions editorial board member His research spans smart grid architectures , distributed control , and cyber-physical security , with recent focus on EV-grid integration , renewable energy democratization , and multi-carrier energy systems . Current projects include: Smart Charging - E-Mobility meets Renewable Energy Early Detection and Defense Systems for Smart Grids Open-source P2P energy sharing platforms Microgrid control strategies for PV-battery systems Awarded IET Fellow and IEEE Senior Member status, his work combines machine learning with power systems engineering through both theoretical modeling and experimental validation . He has contributed over 575 publications with 9800+ Google Scholar citations.

• Electric Power Systems
• Renewable Energy Integration
• Power System Stability and Control
• +۳ مورد دیگر

Xiaozhe Wang is an Associate Professor in the Department of Electrical and Computer Engineering at McGill University, holding the Canada Research Chair (Tier II) in Resilient and Stable Zero-Emission Electric Power Grids and the Rubin & So Foundation Faculty Scholar. He joined McGill in 2016 after a postdoctoral fellowship at MIT under Prof. Konstantin Turitsyn. He earned his Ph.D. from Cornell University (2015), with a minor in Applied Mathematics, and holds degrees from Zhejiang University (B.S., 2010) and Cornell (M.Eng., 2011). His research focuses on resilient power grids, data-driven methodologies, and cybersecurity in energy systems. Key areas include electric vehicle integration, stability assessment, and control strategies for renewable energy systems. He develops advanced techniques for uncertainty quantification, wide-area monitoring, and adversarial attack detection. Notable achievements include pioneering work on polynomial chaos expansion for probabilistic assessment and sparse identification for nonlinear dynamics. His articles explore topics like microgrid control, false data injection attacks, and decentralized energy trading. Awards: Canada Research Chair (Tier II), Rubin & So Foundation Scholar Grants/Projects: Focus on resilience, cybersecurity, and renewable integration funded via NSERC, Mitacs, and industry partnerships. He advises students through fellowships like Mitacs Elevate and Banting Postdoctoral Fellowships. His lab emphasizes interdisciplinary approaches to modern grid challenges, including lab experiments and field trials.

Rajkumar Buyyaمشاهده پروفایل

استاد

• Cluster computing
• Grid computing
• Software systems
• +۷ مورد دیگر

Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor at the University of Melbourne and Founder & CEO of Manjrasoft , a spin-off commercializing cloud innovations. He has held visiting roles at Imperial College London , University of Birmingham , and Tsinghua University . Research Interests : His work spans Cloud Computing , Edge Computing , Grid Systems , and Energy-Efficient Computing , focusing on utility-driven resource allocation, simulation tools, and scalable IoT application frameworks. He pioneered the CloudSim toolkit and Aneka Cloud technologies. Scientific Awards : IEEE Fellow (2015), Web of Science Highly Cited Researcher (2016-2021) Khwarizmi International Award (2020), Scopus Researcher of the Year (2017) Frost & Sullivan New Product Innovation Award (2010), IEEE TCSC Medal (2009) Impact : Authored over 850 publications, including the widely adopted textbook Mastering Cloud Computing . Graduated 54 PhD students now in leadership roles at institutions like Newcastle University and companies such as IBM , Google , and Amazon . His research has driven global adoption of cloud/edge technologies in 50+ countries.

Vasilis Kostakisمشاهده پروفایل

استاد

• Technology Governance
• Sustainability
• Peer Production Systems
• +۷ مورد دیگر

Vasilis Kostakis is a Professor of Technology Governance and Sustainability at Tallinn University of Technology (TalTech), Estonia, and a Faculty Associate at Harvard University's Berkman Klein Center. He is also the founder of the P2P Lab, a global initiative exploring peer-to-peer production systems, and a founding member of the 'Tzoumakers' rural makerspace and CommonEn energy cooperative in Greece. Research Interests : Kostakis focuses on technology governance, sustainability, and commons-based systems. His work critiques traditional economic models and advocates for decentralized, community-driven approaches to energy, production, and knowledge-sharing. Key themes include post-growth economics, cosmolocal scalability, and the intersection of digital technology with local initiatives. Key Contributions : He has pioneered frameworks like 'cosmolocalism' (balancing local and global systems) and 'design global, manufacture local' (Dgml), emphasizing localized production using global digital designs. His projects, such as TheOtherSchool.art and the P2P Lab, aim to democratize access to technology and knowledge. Labs & Collaborations : The P2P Lab acts as a hub for global commons research, while his hometown initiatives in Ioannina, Greece, exemplify grassroots sustainability. Collaborations span academia, civil society, and policy-making to reimagine socio-technical systems.

Wenjing Zhangمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Dr. Wenjing Zhang is an Assistant Professor in the School of Computer Science at the University of Guelph, Canada. She holds a Ph.D. in Computer Science from the University of Guelph (2024) and was a visiting research scholar at the University of Arizona's Department of Electrical and Computer Engineering (2016–2018). Her research focuses on cybersecurity in AI/ML, including security threats to models, privacy-preserving techniques, and data privacy in generative AI. She leads projects on robust defenses against adversarial attacks, secure federated learning, and privacy-preserving prompt engineering for LLMs. Dr. Zhang’s research areas include: Security in AI/ML (e.g., poisoning, evasion, prompt injection attacks) Model Privacy (protection of internal parameters) Data Privacy (synthetic data generation, privacy-preserving prompt engineering) She has secured a five-year NSERC Discovery Grant (2025–2030) for her research on enhancing security, privacy, and fairness in generative AI. Her work has been published in top-tier venues such as NeurIPS, IEEE Transactions on Information Forensics and Security, and IEEE Transactions on Communications. She is a recipient of the 2022 Westin Scholar Award and serves on technical committees for IEEE conferences including CNS 2025 and ICC 2025. Her team collaborates on interdisciplinary projects involving federated learning, information theory, and reinforcement learning. She actively seeks partnerships in security, privacy, and generative AI applications.

Ciarán Mac an Bhairdمشاهده پروفایل

دانشیار

• Resourcing Small Firms
• Enterprise Policy
• Entrepreneurial Finance
• +۷ مورد دیگر

Ciarán Mac an Bhaird is an Associate Professor of Business and Management at Dublin City University (DCU), within the Fiontar & Scoil na Gaeilge department. He holds a PhD from Trinity College Dublin, a B.Comm and LL.B from NUI Galway, and an M.Sc. in Finance from DCU. His academic role includes teaching and supervising PhD students focusing on enterprise policy, high-growth firm financing, and entrepreneurship education. Research interests span resourcing small firms, capital structure, alternative finance, and public policy for SMEs. He authored Resourcing Small and Medium Sized Enterprises (Springer-Verlag, 2010), launched by the Irish Minister for Enterprise. His work has been published in journals like Small Business Economics and Venture Capital . He chairs the Entrepreneurial Finance track at the Institute of Small Business and Entrepreneurship Conference and serves as an associate editor for Research in International Business and Finance . Current PhD advisees include Simon Bridge, Nouf Alnasser, Batoul Batoulbanjar, and Sean O Reilly. Professional activities include contributions to policy reports for Enterprise Ireland and the Irish League of Credit Unions, and participation in the U.S. State Department’s International Visitor Leadership Programme.

Nour Moustafaمشاهده پروفایل

دانشیار

• Cyber Security
• Computer System Security
• Networking and Communications
• +۷ مورد دیگر

Dr. Nour Moustafa is an Associate Professor and ARC DECRA Fellow at the School of Systems & Computing (SysCom) , University of New South Wales (UNSW) Canberra , Australia. He leads the Intelligent Security Group and focuses on developing AI/ML-driven cybersecurity frameworks for smart systems. Educated at Helwan University (BSc/MSc in Information Systems) and UNSW (PhD in Cybersecurity). Research Interests include intrusion detection, threat intelligence, privacy preservation, digital forensics, and cyber resilience, with methodologies spanning statistical analysis , machine learning , and deep learning applied to IoT , Edge/Cloud , and Industrial IoT environments. His work emphasizes federated learning for privacy preservation, blockchain for secure AI, and digital twins for network self-healing. Notable contributions include the TON-IoT , Bot-IoT , and UNSW-NB15 datasets for cybersecurity evaluation. Scientific Awards : 2020 Spitfire Memorial Defence Fellowship ACM Distinguished Speaker IEEE Senior Member He has served as guest associate editor for IEEE Transactions journals and held leadership roles in conferences like IEEE TrustCom . His research bridges academia and industry, with over 75 publications in top-tier venues.

Emin Gun Sirerمشاهده پروفایل

دانشیار

• Operating Systems
• Networking
• Distributed Systems
• +۳ مورد دیگر

Emin Gün Sirer is an Associate Professor at the Department of Computer Science , College of Engineering , Cornell University . He co-directs the Initiative for Cryptocurrencies and Smart Contracts and leads the Meridian and HyperDex projects. Research in operating systems, networking, and distributed systems Focus on secure operating systems, high-performance cloud infrastructure, and peer-to-peer networks Developed systems like Nexus (secure OS), OpenReplica (Paxos implementation), and Trickles (stateless network protocol) Prominent Projects : Meridian - Lightweight network location service without virtual coordinates Cubit - Decentralized peer-to-peer search Kimera - Network-centric Java verification SPIN - Extensible microkernel for application-specific services Scientific Contributions : Leading work in blockchain security and peer-to-peer systems Patents in executable content rewriting and distributed virtual machines Advising & Collaborations : Advises projects in network positioning and content distribution Collaborates with institutions like Usenix , SIGCOMM , and NSDI Personal Background : Ph.D. and M.S. in Computer Science from the University of Washington B.S.E. in Computer Science from Princeton University High school at Robert College

Yuning Jiangمشاهده پروفایل

استاد مهمان

• Optimal Control
• Model Predictive Control
• Power Systems
• +۴ مورد دیگر

Yuning Jiang is a Visiting Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Automatic Control Laboratory (LA3) within the School of Engineering (STI). He teaches the doctoral course Optimal Control for Dynamic Systems and contributes to research in distributed optimization, model predictive control (MPC), and smart grid technologies. His work bridges theoretical advancements in control systems with practical applications in power networks and autonomous systems. Current research emphasizes scalable solutions for AC optimal power flow, real-time MPC for embedded systems, and robust optimization under uncertainty. His research interests span Optimal Control , Power Systems , Smart Grids , and Federated Learning . Notable contributions include distributed algorithms for large-scale power systems and privacy-preserving co-simulation frameworks. Recent publications focus on microservice deployment in satellite-terrestrial networks and real-time pricing mechanisms for vehicle-to-grid (V2G) integration. Yuning holds a position in the EDEE-ENS unit under EPFL’s Academic Affairs division (VPA-AVP-DLE), reflecting his role in academic administration and teaching infrastructure. His lab, the Automatic Control Laboratory, focuses on cutting-edge research in control theory and its interdisciplinary applications.

Mostafa Ammarمشاهده پروفایل

استاد

• Network Architectures
• Protocols and Services
• Multicast Communication
• +۱۷ مورد دیگر

Mostafa Ammar is a Regents' Professor and Interim Chair at the School of Computer Science , Georgia Institute of Technology. He holds a Ph.D. from the University of Waterloo and degrees (S.B., S.M.) from MIT. His career spans academia, industry collaboration, and leadership in networking research. Research Interests : Network architectures, protocols, and services; multicast communication; multimedia streaming; content distribution networks; disruption-tolerant networks; mobile cloud computing; network virtualization; HTTP adaptive streaming; video quality of experience (QoE); encrypted traffic analysis; vehicular networks; peer-to-peer systems; overlay networks. Funding : Supported by NSF, DARPA, AFOSR, CISCO, IBM, Intel, BellSouth, Sprint, and others. His research focuses on video QoE estimation using network measurements, mobile cloud computing , and network agility through virtualization. Recent work includes machine learning approaches for encrypted traffic analysis and scalable techniques for network performance. Key scientific awards include: IBM Faculty Partnership Award (1996), Best Paper at WWW '98, IEEE Fellow (2002), ACM Fellow (2003), GT Outstanding Doctoral Thesis Advisor (2006), IEEE TCCC Service Award (2010), ACM Mobihoc Best Paper (2012), College of Computing Awards (2015, 2018), IFIP Best Paper (2018), and multiple teaching excellence awards (2013-2017, 2022 CIOS Award). Dr. Ammar has advised 39 PhD students , many of whom hold prominent positions at institutions like UC Santa Barbara, Emory University, and companies including Google, Microsoft, and Facebook. His editorial leadership includes Editor-in-Chief of IEEE/ACM Transactions on Networking (1999-2003) and roles in conference committees.

• Algorithms
• Algorithmics
• Big Data
• +۷ مورد دیگر

Stephen Alstrup is a Professor in the Algorithms and Complexity section at the Department of Computer Science (DIKU), University of Copenhagen, Faculty of Science. His research bridges theoretical computer science with practical applications in modern computational challenges. His primary research interests include: Algorithm design and analysis Graph algorithms and data structures Big Data processing techniques Streaming algorithms and Internet distribution Theoretical foundations with practical implementations Alstrup's work demonstrates how theoretical algorithm research can lead to real-world applications, as evidenced by his development of Octoshape technology for large-scale Internet streaming. His research spans from fundamental theoretical problems to applications in Big Data, cloud computing, and information retrieval systems. He has published extensively with 93 research outputs including journal articles, conference proceedings, and books. His recent work focuses on graph spanners, semantic hashing, recommendation systems, and universal graph structures, showing continued productivity in theoretical computer science. Alstrup actively engages with industry and media, contributing to discussions about Big Data applications, technology innovation, and how businesses can collaborate with universities to access cutting-edge knowledge and funding opportunities. His work has been featured in 10 media contributions discussing practical applications of algorithms in education, municipal IT projects, and business innovation.