جست‌وجوی استاد و پژوهشگر

Cristina Nita-Rotaruمشاهده پروفایل

استاد

• Cybersecurity
• Distributed Systems
• Computer Networks
• +۵ مورد دیگر

Cristina Nita-Rotaru is a tenured Professor of Computer Science at Northeastern University's Khoury College of Computer Sciences , where she leads the Network and Distributed Systems Security Laboratory (NDS2) and is a founding member of the Cybersecurity and Privacy Institute . Previously, she was a faculty member at Purdue University from 2003 to 2015. Education: Ph.D. in Computer Science from Johns Hopkins University M.S. in Computer Science from Politehnica University of Bucharest , Romania Research Focus: Her research lies at the intersection of cybersecurity , distributed systems , and computer networks . She designs and builds resilient distributed systems and network protocols that maintain security, availability, and performance despite faults, misconfigurations, and attacks. Her work integrates formal methods , adversarial testing , blockchain security , and trustworthy AI . Funding & Impact: Her research has been supported by NSF , DARPA , ONR , Google , Ethereum Foundation , and others. She has received numerous awards, including the NSF CAREER Award (2006) and multiple best paper awards at top venues like NDSS , ACM CCS , and IEEE S&P . Scientific Awards: NSF CAREER Award (2006) NETYS 2023 Best Paper Award ACM SACMAT 2022 Best Paper & Test-of-Time Awards IEEE SafeThings 2019 Best Paper Award NDSS 2018 Best Paper Award ISSRE 2017 Best Paper Award DSN 2015 Best Paper Award IETF/IRTF Applied Networking Research Prize (2016, 2018, 2025) Purdue College of Science Research Award (2013) Purdue Excellence in Research Award (2012) Purdue College of Science Leadership Award (2012) Purdue College of Science Undergraduate Advising Award (2008) Purdue Teaching for Tomorrow Award (2007) Advising & Students: She has advised over 30 PhD and MS students at Northeastern and Purdue. Notable former students include Reza Curtmola (NJIT Professor) , Endadul Hoque (Syracuse University Assistant Professor) , and Max von Hippel (Bencify founding partner) . Labs & Teams: She directs the NDS2 Lab , focusing on network and distributed systems security, with projects spanning blockchain protocols , SDN security , IoT and connected cars , and formal verification of protocols .

Andrea Fumagalliمشاهده پروفایل

استاد

• Optical Networking
• Photonic Slot Routing
• Wavelength Routing and Protection
• +۷ مورد دیگر

Andrea Fumagalli is a Professor in the Department of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science , The University of Texas at Dallas. He earned his Ph.D. (1992) and Laurea (1987) in Electrical Engineering from Politecnico di Torino, Italy. Research Interests: All-Optical Network Architectures, Photonic Slot Routing, Wavelength Routing and Protection, Sensor Networks, Cooperative Wireless Networks, Network Optimization, Next Generation Internet (NGI), and Multi-hop Optical Networks. Education: Ph.D., Electrical Engineering, Politecnico di Torino (1992) Laurea, Electrical Engineering, Politecnico di Torino (1987) Key Research Trends: His recent publications focus on 5G networking, optical network automation, elastic optical networks, network reliability, and cross-layer optimization. He explores FPGA acceleration in 5G Low-PHY functions, live migration of containerized network components, and spectral fragmentation mitigation in EONs. Scientific Awards: Best Teaching Award, Electrical Engineering, UTD (2002) Best Thesis Award for Ph.D. Advisee Isabella Cerutti (2002) IEEE ComSoc Distinguished Lecturer Tour (2000) Best Paper Award (1999): 'An Optimal Design Algorithm for Photonic Slot Routing Networks Migrating to Optical Packet Switching' Advising and Grants: He advised Ph.D. student Isabella Cerutti. In 2001, he secured a $300,000 grant from FUNDACAO CPqD for optical network reliability research. He leads the Optical Networking Advanced Research (OpNeAR) Lab at UTD, collaborating on international projects like the Italian government-funded grid computing initiative (2002) and the OMEGA Test-bed for differentiated reliability. Laboratories and Teams: He directs the OpNeAR Lab , which develops tools for optical network emulation and reliability testing. His projects involve partnerships with institutions in Brazil (Unicamp), Sweden (KTH), Italy (Politecnico di Torino, Scuola Superiore Sant'Anna), and CNR/CNIT.

Flavio Espositoمشاهده پروفایل

دانشیار

• Cyber-physical Systems
• Networked Systems
• Network Virtualization
• +۵ مورد دیگر

Flavio Esposito is an Associate Professor in the Computer Science Department at Saint Louis University's School of Engineering. He also serves as a Research Institute Fellow and CS Graduate Coordinator. His office is located in ISE 234D at 3450 Lindell Blvd, St. Louis, MO. Dr. Esposito's research focuses on cyber-physical systems and networked systems, including network virtualization, network management, Software-Defined Networks (SDN), network architectures, and wireless networks. He has a strong interest in interdisciplinary applications of these technologies to medicine and agriculture. His work bridges theoretical networking concepts with practical implementations. His publications span key areas in networking research, with recent work focusing on congestion control algorithms, virtual network embedding, recursive network architectures, and edge computing applications. The research trends show a progression from foundational networking protocols toward more sophisticated applications integrating machine learning, edge computing, and cyber-physical systems, with increasing emphasis on real-world applications in diverse domains. Outstanding Graduate Mentoring Faculty Award from the School of Engineering (2021) Finalist for the Undergraduate Mentoring Award in the College of Arts and Sciences Multiple NSF research awards including US Ignite, ICE-T, CNS Core, CC* Integration, CPS:TTP, and ModernCARE projects COMCAST Innovation Fund Award (January 2020) International Center for Responsible Gaming (ICRG) Award ($150K) Dr. Esposito actively mentors PhD and MS students, with numerous current and past students who have gone on to positions at major tech companies, universities, and research institutions. He has been a Principal Investigator on multiple significant research grants totaling millions of dollars. He co-founded Spaghetti Code Labs with former PhD student Alessandro Sangiorgi, whose cybersecurity educational app WeeNet has achieved 5.7M+ downloads. He leads several research labs and teams focused on cyber-physical systems, with current openings for PhD students, visiting researchers, and postdocs working on networks, learning, edge computing, and applications to medicine and agriculture. His teams have developed numerous software systems including Software Mutant, Neighborhood Method Prototype, VINEA, ProtoRINA, and BUtorrent.

Lisa Yanمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• Computing Ethics
• Teaching Assistant Training
• +۲ مورد دیگر

Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement. Her academic credentials include: PhD in Electrical Engineering from Stanford University (2019) MS in Electrical Engineering from Stanford University (2015) BS in Electrical Engineering and Computer Science from UC Berkeley (2013) Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education. Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses. She received recognition through: The Faculty Award for Outstanding Mentorship of GSIs (2024) Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations. Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.

• 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.

Marius Portmannمشاهده پروفایل

استاد

• Cybersecurity
• Computer Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Professor Marius Portmann is the UQ-Cisco Chair of Network Security at the School of Electrical Engineering and Computer Science (EECS), University of Queensland. His expertise spans Cybersecurity, IoT, and Applied AI. He holds a PhD from ETH Zurich (2003) and has led research in Software Defined Networking (SDN), blockchain, and energy-harvesting IoT systems. Education: PhD in Electrical Engineering from Swiss Federal Institute of Technology (ETH Zurich), 2003. Research focuses on securing IoT networks, AI-driven intrusion detection, and sustainable sensor systems. He has pioneered self-powered IoT systems using energy harvesters and developed frameworks like FlowTransformer for network analysis. His work bridges theoretical advancements with practical applications in smart tourism, energy efficiency, and edge computing. Recent publications highlight innovations in DDoS detection (P4-Secure), sensor-based environmental monitoring (EcoShower), and graph-based anomaly detection (XG-BoT). His datasets (e.g., NF-ToN-IoT-v3) are widely used in ML-based cybersecurity research. Collaborations include industry partners like Cisco and institutions like RMIT. Grants and leadership roles in interdisciplinary projects underscore his impact. He advises on IoT security standards and contributes to open-source tools for network research. Current projects explore edge-AI integration and sustainable sensor networks.

Hyejin Kuمشاهده پروفایل

استاد

• Mathematical Finance
• Machine Learning
• Risk Management
• +۴ مورد دیگر

Hyejin Ku is a Full Professor in the Department of Mathematics and Statistics at York University's Faculty of Science. Her research focuses on the intersection of Mathematical Finance and Machine Learning, addressing challenges in risk measurement, portfolio optimization, and quantitative finance. She develops advanced mathematical models to enhance decision-making through reinforcement learning and data analytics. Notable projects include novel algorithms for credit rating prediction using neural networks and sequence-based clustering for credit risk assessment. Her work integrates applied mathematics with real-world financial applications, such as systemic risk reduction in multi-layer networks and option pricing under liquidity constraints. She holds a prominent position in mathematical finance, contributing to both theoretical advancements and practical solutions for financial markets. Her research trends emphasize interdisciplinary approaches, combining machine learning techniques with financial modeling to solve complex problems in risk management and asset valuation. Her publications span over two decades, showcasing contributions to portfolio optimization, derivatives pricing, and computational finance. Dr. Ku is affiliated with York University’s Department of Mathematics and Statistics, where she contributes to academic leadership and research mentorship. Her office is located in DB 2025, and she can be reached at hku@yorku.ca.

Xi Zhangمشاهده پروفایل

استاد

• Wireless Networks
• Quality of Service (QoS) Theory
• 6G/Next-Generation Mobile Networks
• +۷ مورد دیگر

Xi Zhang is a Full Professor in the Department of Electrical and Computer Engineering at Texas A&M University . He is also the Founding Director of the Networking and Information Systems Laboratory. His academic career includes research fellowships at the University of Technology Sydney and James Cook University, as well as prior roles at AT&T Bell Laboratories and AT&T Laboratories Research. Education: B.S. and M.S. in Electrical Engineering & Computer Science, Xidian University, China M.S. in Electrical Engineering & Computer Science, Lehigh University, USA Ph.D. in Electrical Engineering-Systems, University of Michigan, USA Research Interests: His work focuses on Quality-of-Service (QoS) theory, 6G/Next-Generation Wireless Networks , Massive MIMO , Integrated Sensing and Communications (ISAC) , and Network Function Virtualization (NFV) . He has pioneered advancements in statistical delay/error-rate bounded QoS , AI-driven 6G architectures , and mURLLC (massive ultra-reliable low-latency communications) . Awards & Honors: IEEE Fellow (2014) for contributions to QoS theory in mobile wireless networks NSF Early Career Award (2004) Multiple Best Paper Awards (IEEE GLOBECOM, WCNC, ICC) Outstanding Faculty Award from Texas A&M (2020) Leadership Roles: He has held key positions as Technical Program Committee (TPC) Chair for major conferences (e.g., IEEE GLOBECOM 2011, IEEE ICDCS 2026) and serves as Editor for top-tier journals like IEEE Transactions on Communications and IEEE Transactions on Wireless Communications . Labs & Teams: He leads the Networking and Information Systems Laboratory , focusing on 6G mobile networks, ISAC systems, and AI-driven network architectures.

Martin Nordal Petersenمشاهده پروفایل

دانشیار

• Internet of Things
• Optical Networking
• Wireless Communication
• +۳ مورد دیگر

Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

• Multi-access Edge Computing
• High-Performance Networks
• Cognitive IoT Systems
• +۷ مورد دیگر

Prof. Ahmed Al-Dubai is a Professor at the School of Computing, Engineering and the Built Environment, Edinburgh Napier University, where he leads the IoT and Networked Systems Research Group and serves as Cybersecurity and Cyber Physical Systems Research Lead. His interdisciplinary research spans Multi-access Edge Computing, High-Performance Networks, Cognitive IoT Systems, VANETs, AI, E-Health, Smart Cities, and Security . He earned his PhD in Computing Science from the University of Glasgow in 2004. His recent publications focus on edge computing architectures, digital twin security, Arabic NLP, wireless energy harvesting, and vehicular communication . His work has been recognized with IEEE Outstanding Service Award, Best Paper Awards at IEEE IUCC 2015 and ACM MoMM 2013 , and fellowships like Senior IEEE Member and British Higher Education Academy Fellow . He supervises 20+ PhD students and has served on 60+ IEEE/ACM conference committees. Current projects include AI-driven fish identification (Innovate UK £265K) , secure IoT protocols (Royal Society £12K) , and COG-MHEAR (EPSRC £3.26M) . He has held visiting professorships at Universite de Valenciennes, University of Sydney, and University of Shenyang.

• Network Performance
• Computer Networks
• Cloud Computing
• +۷ مورد دیگر

Dr. Theophilus A. Benson is a Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU) and CMU-Africa. His research focuses on improving network performance and availability in data centers, clouds, and edge networks. He leads projects addressing the digital divide in Africa through initiatives like the African Internet Observatory (AIO), which analyzes connectivity challenges and infrastructure resilience. His work spans programmable networks (eBPF/P4), CDN optimizations, and network management frameworks. Education: B.S. from Tufts University, Ph.D. from University of Wisconsin-Madison, Postdoc at Princeton University. Research Interests: Network state management, programmable substrates, digital equity, measurement systems, and network security. His group develops tools like NetEdit (eBPF management), JSBench (mobile web performance), and the African Internet Observatory's probe network. Recent Trends: Publications emphasize eBPF management frameworks, African network analysis, and data-driven CDN improvements. Key projects include subsea cable impact studies, QUIC protocol analysis, and deploying measurement probes across Africa. Awards: NSF CAREER Award, Google/FA Faculty Awards, SIGCOMM Test of Time Award, and DARPA ISAT membership. Advising & Grants: Active in mentoring MS/PhD students and postdocs. Current grants include NSF funding for data-driven web performance and IoT security. Collaborations with Meta and industry partners enhance real-world system deployments. Labs & Teams: Leads the AIO initiative with local African stakeholders. Research group includes collaborators from National Taiwan University and partnerships with institutions like TU Delft (keynote on eBPF).

• Wireless Communications
• Network Security
• Quality of Experience (QoE)
• +۷ مورد دیگر

Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.

Eric TOTELمشاهده پروفایل

استاد

• Network Security
• Intrusion Detection Systems
• Data Confidentiality
• +۳ مورد دیگر

Eric TOTEL is a Professor at Telecom SudParis, specializing in cybersecurity and network security. His research focuses on intrusion detection systems, graph-based anomaly detection, machine learning applications in security, and data confidentiality in distributed systems. He has contributed to projects such as DAMS (DDoS mitigation using deep reinforcement learning), Sec2Graph (novelty detection on graph-structured data), and DAEMON (dynamic autoencoder-based anomaly detection). His work emphasizes scalable solutions for multi-step attack detection and privacy-preserving infrastructure for encrypted DNS logs. Key contributions include developing correlation engines for distributed systems, formalizing invariant-based attack detection in web applications, and exploring static analysis for information flow control. He has authored over 50 peer-reviewed publications and served on program committees for conferences like RAID, CRiSIS, and EuroS&P. His HDR (2012) formalized error-detection techniques applied to intrusion detection. Advising and grants: He collaborates on projects funded by French national research agencies and has mentored students in cybersecurity, AI for defense (CAID conferences), and cloud infrastructure security. His research often bridges theoretical models and practical implementations, with tools like STARLORD for 3D graph visualization of security data.

Srinivas Narayanaمشاهده پروفایل

استادیار

• Computer Networks
• Formal Verification
• Compilers
• +۴ مورد دیگر

Srinivas Narayana is an Assistant Professor in the Department of Computer Science at Rutgers University, specializing in programmable networking, formal verification, and systems research. He holds a PhD from Princeton University and a B.Tech from IIT Madras, with postdoctoral work at MIT. His research focuses on building safe, high-performance networks through optimizing compilers, verified programming, and distributed system monitoring. He has received NSF grants, the CGO 2022 Distinguished Paper Award, and the 2017 SIGCOMM Best Paper Award. Education: PhD and MA in Computer Science, Princeton University (2016) B.Tech in Computer Science, IIT Madras (2010) Postdoctoral Research, MIT (2018) Research Interests: His work bridges networking and systems with a focus on compilers, formal methods, and programmable hardware. Notable projects include K2 compiler for eBPF, the eBPF verifier soundness work, and congestion control mechanisms like CCP. He explores parallel packet processing, privacy-preserving analytics, and load balancing strategies. Grants & Awards: NSF Awards #2422076, #1910796, #2019302 eBPF Foundation Grant Facebook Networking Research Award Network Programming Initiative (NPI) Funding Lab & Teams: Leads the NetSys group at Rutgers, collaborating with teams on projects like the eBPF verifier, verified packet processing, and network monitoring tools like Marple. His lab emphasizes open-source contributions and industry collaboration.

Suryadipta Majumdarمشاهده پروفایل

دانشیار

• Cloud Computing Security and Privacy
• Internet of Things (IoT) Security and Privacy
• Software-Defined Network (SDN) Security
• +۳ مورد دیگر

Suryadipta Majumdar is an Associate Professor at the Concordia Institute for Information Systems Engineering (CIISE), part of Concordia University. His primary research interests focus on Cloud Computing Security and Privacy, Internet of Things (IoT) Security and Privacy, and Software-Defined Network (SDN) Security. He has contributed extensively to proactive security measures in containerized systems and Kubernetes environments, alongside developing tools like ACE-WARP and PerfSPEC to address real-time threats. In terms of education, he holds a PhD in a relevant field, though specific details about his academic background (e.g., institutions, thesis topics) are not explicitly mentioned in the provided text. His work bridges theoretical cybersecurity frameworks with practical implementations, emphasizing automated translation, differential privacy, and compliance auditing across cloud and IoT ecosystems. Majumdar’s research trends highlight a focus on layered security analysis, anomaly detection in IoT networks, and mitigating vulnerabilities in network functions virtualization (NFV). He has explored topics such as resilient in-band OpenFlow networks, runtime security policy enforcement in OpenStack, and privacy-preserving network data anonymization via tools like SegGuard. His recent publications reflect collaboration with international conferences and workshops, including contributions to Digital Forensics and Applied Cryptography. No scientific awards are explicitly mentioned in the text. His advising activities and grant history remain unlisted, though he has developed notable security frameworks and tools. He is affiliated with CIISE and likely contributes to its research initiatives in emerging technologies like 5G and edge-core environments.