Thomas Dreibholz is a Chief Research Engineer at Simula Metropolitan's Center for Resilient Networks and Applications. He specializes in cyber sovereignty, network security, and internet testbeds, with extensive work on distributed systems, cloud computing, and 5G networks. Affiliation: Simula Metropolitan, Oslo, Norway Research Focus: Multi-path transport protocols, network resilience, and privacy-preserving frameworks His research explores the intersection of network security, cloud/fog computing, and next-generation communication protocols. Recent work includes HiPerConTracer for network analysis, privacy-aware fog platforms , and multi-layered federated learning security . He contributes to testbed development, including the NorNet infrastructure for real-world multi-path transport research. Publications reflect expertise in multi-path TCP , 5G network optimization , and cloud/fog security . He has delivered invited talks at institutions like Hainan University and Princeton University, emphasizing open-source testbed deployment and educational outreach.
Dr. Ahmed Doha is an Associate Professor at the Sprott School of Business, Carleton University, specializing in Supply Chain Management. He holds a PhD in Operations Management and Information Systems from York University, Canada, and MSc/BSc degrees in Electrical and Computer Engineering from Queen’s University and Mansoura University, respectively. Education: PhD (York), MSc (Queen’s), BSc (Mansoura) Current sabbatical status Contact: 5036 Nicol Hall, Carleton University, Ottawa, ON K1S 5B6 His research focuses on applying emerging technologies like artificial intelligence (AI) and the Internet of Things (IoT) for business model innovation and value creation. Key areas include: Generative AI and Large Language Models (LLMs) in organizational and personal AI assistants E-commerce, recommendation systems, and crowdsourcing applications Semantic ontologies and knowledge bases integration Combating corruption through AI-enabled business models Research methodology follows full-cycle design science principles, from problem identification to field experimentation. Funded by SSHRC, NSERC, CANARIE, and industry partners. Scientific awards: NSERC Alexander Graham Bell Canada Graduate Scholarship Teaching: PhD-level AI research methods, applied AI, technology management, and supply chain fundamentals
Lee Keel is a Professor in the Department of Electrical and Computer Engineering at Tennessee State University's College of Engineering, where he has been faculty since 1986. He also serves as an Adjunct Professor in Vanderbilt University's Mechanical Engineering Department since 1991 and previously directed Tennessee State's Center for Systems Science Research from 1997-2007. Dr. Keel earned his Ph.D. in Electrical Engineering from Texas A&M University in 1986, following an M.S. from the same institution in 1982 and a B.S. in Electronics Engineering from Korea University in 1978. His academic journey began with engineering experience at LG Telecommunications R&D in Korea before transitioning to academia. His research expertise spans Linear Systems Theory, Robust Control, and Networked Control Systems, with recent focus on developing data-based control design techniques that eliminate reliance on analytical models. His work has been continuously funded by NSF, NASA centers (Ames, Langley, Goddard, Marshall), DoD, and industry partners including Boeing, with over $20 million in research grants throughout his career. Analysis of his publication record shows consistent contributions to robust control theory, particularly in interval systems stability, parametric robustness, and measurement-based controller design. His recent work increasingly addresses cyber-physical security applications for power grids and multi-agent systems. Full Academic Scholarship, Gold-Star Yonam Foundation (1971-1972, 1976-78) Eta Kappa Nu Phi Kappa Phi Distinguished Researcher Award, Tennessee State University (1996) Professor Keel has supervised numerous graduate students through thesis research and has served in leadership roles for major conferences including as Publication Chair for multiple American Control Conferences. His research group maintains strong connections with NASA laboratories and defense contractors, providing students with opportunities to work on problems with real-world impact in aerospace and critical infrastructure domains.
Justine Sherry is the A. Nico Habermann Associate Professor of Computer Science at Carnegie Mellon University (CMU). Her research focuses on networked systems across software and hardware layers, particularly middleboxes, congestion control, FPGA-based acceleration, and Internet fairness. Affiliations: Computer Science Department (CSD) , CyLab , SNAP Lab . Academic Rank: Associate Professor Her recent work explores radical shifts in datacenter architectures via SmartNICs, hardware-software co-design for network functions, and database proxy innovation using eBPF. She leads research on Internet fairness , denial-of-service mitigation , and high-speed intrusion detection through systems like Pigasus. Key scientific contributions span 15 recent publications at venues like SIGCOMM, OSDI, and VLDB, addressing topics such as: Mathematical fairness in congestion control KERNEL bypass strategies in FPGA SmartNICs BBR algorithmic unfairness Wireless latency optimization (Zhuge) Heterogeneous hardware performance analysis Open-source security infrastructure Major awards include: Sloan Research Fellowship VMWare Systems Award NSF grants Intel Outstanding Researcher Award Early Career Diamond from UW Engineering She mentors students in systems research, including Ranysha Ware , Nirav Atre , and Hugo Sadok , while collaborating with institutions like Google, Facebook, and DARPA.
Weina Wang is an Assistant Professor in the Computer Science Department at Carnegie Mellon University, joining in Fall 2018. Her research lies at the intersection of applied probability , stochastic systems , and reinforcement learning , focusing on decision-making in large-scale systems with applications to computing resource orchestration, data privacy, and graph statistics. She has received prestigious awards including the NSF CAREER Award (2022) , ACM MobiHoc Best Paper (2022) , and ACM SIGMETRICS Rising Star Research Award (2023) . PhD in Electrical Engineering, Arizona State University (2016) Bachelor’s in Electronic Engineering, Tsinghua University (2009) Her recent publications span restless bandits , queueing theory , and attributed graph alignment , reflecting her dual focus on fundamental limits and algorithmic solutions. Notable collaborations include work on privacy-preserving data routing , phase-aware scheduling , and erasure-coded servers for heterogeneous traffic. She has advised PhD students Jalani Williams , Tuhinangshu Choudhury , and Yige Hong . Her research has been recognized with best paper awards and grants like the NSF CAREER . She also contributes to professional societies, recently joining the INFORMS Applied Probability Society council . Her teaching includes courses like Probability and Computing and Fundamentals of MDPs and Reinforcement Learning .
Sang-Hoon Kim is an Associate Professor in the Department of Software and Computer Engineering and Department of Artificial Intelligence at Ajou University, South Korea. He leads the Systems Software Lab (Paldal Hall 1004-2) and maintains active collaborations with Virginia Tech as a Visiting Scholar since August 2024. His academic journey includes a Ph.D. in Computer Science from KAIST (2016) under advisors Seungryoul Maeng and Jin-Soo Kim, and a B.S. in Computer Science from KAIST (2002). His research spans operating systems, memory management, and storage systems with focus on mobile platforms, heterogeneous architectures, and SSD technologies. Key interests include memory fragmentation control , distributed thread execution , key-value storage optimization , and resource disaggregation . His work bridges theoretical innovation with practical system implementations, particularly for mobile and datacenter environments. Kim's publication portfolio shows consistent output in top-tier venues including USENIX FAST, VLDB, ICDCS, and ASPLOS. His research demonstrates evolution from mobile memory management (2015-2017) toward distributed systems and hardware-aware software (2019-present), with recent emphasis on resource-disaggregated environments and heterogeneous-ISA computing. The 2024 Best Paper Award at USENIX FAST highlights his impact in storage systems research. Best Paper Award at USENIX FAST'24 Multiple patents including US-9588912B2 for memory control He directs significant research projects funded by ETRI, NRF, and US ONR, including current work on memory-centric computing systems (2020-2023) and disaggregated non-volatile memory systems using RDMA (2018-2020). His Systems Software Lab maintains strong industry partnerships with Samsung Electronics and NHN, with prior projects improving Android memory management and developing SSD-based storage systems for large-scale internet services.
Prashant Krishnamurthy is a Professor at the University of Pittsburgh's School of Computing and Information , where he teaches foundational and advanced courses in wireless networks and cryptography. As a cofounder of the national Center of Academic Excellence (CAE) in Information Assurance Education and Research, he has driven curriculum development and secured over $5 million in grants from the National Science Foundation and the Commonwealth of Pennsylvania. Research Focus: Wireless network security, location-based systems, spectrum policy, and privacy-preserving technologies Grants: Served as PI/co-PI for major NSF and state-funded initiatives Labs: Cofounder of the Laboratory for Education and Research in Security Assured Information Systems (LERSAIS) His work bridges technical innovation with policy implications, including spectrum virtualization, secure IoT frameworks, and combating decentralized finance (DeFi) vulnerabilities. Recent publications highlight interests in quantum network routing, digital twins for smart homes, and machine learning applications in network design. The most recent 15 articles reveal expertise in quantum networking , DeFi security , IoT privacy , and resilient wireless architectures . Topics span zero-trust frameworks, spectrum sharing, and dynamic task assignment in smart environments. While no specific scientific awards are listed, his grants and lab leadership underscore significant contributions to cybersecurity education and research.
Professor Wojciech Kabaciński is a distinguished academic at the Poznań University of Technology, where he serves in the Faculty of Computer Science and Telecommunications within the Institute of Teleinformatics Networks. With the title of 'prof. dr hab. inż.', he holds the position of full professor with habilitation in engineering. His academic profile is marked by extensive research contributions and active supervision of doctoral students in the field of optical networking. Professor Kabaciński's research interests center on optical networks, with particular expertise in elastic optical switching, wavelength-space-wavelength switching architectures, network routing algorithms, and non-blocking network design. His work spans both theoretical foundations and practical implementations for telecommunications infrastructure and data center applications. He has made significant contributions to understanding WSW1 and WSW2 switching architectures, defragmentation algorithms, and control mechanisms for elastic optical networks. Analysis of Professor Kabaciński's recent publications (2017-2025) reveals a consistent focus on optimizing optical switching networks, with increasing emphasis on elastic optical networks and flexible switching architectures. His research demonstrates a progression from fundamental network theory to practical implementations addressing contemporary challenges in telecommunications. The trend shows growing complexity in network architectures and more sophisticated algorithms for resource allocation and connection management. Professor Kabaciński has supervised five doctoral dissertations and has been active in reviewing academic work. His research output includes 56 scientific articles, 60 book chapters, 3 books, and 14 research reports, demonstrating sustained scholarly productivity throughout his career. As an academic supervisor, Professor Kabaciński has guided doctoral students through research on simultaneous connections routing, non-blocking switching fabrics, multiplane banyan networks, self-controlling switching fields, and broadcast-capable switching architectures. His supervision reflects a commitment to advancing knowledge in optical networking while developing the next generation of researchers in the field. His current research continues to push boundaries in optical networking, with recent publications addressing cutting-edge challenges in rearrangeable wavelength-space-wavelength switches and flexible optical network architectures, positioning him at the forefront of developments in telecommunications infrastructure.
Buğra Çaşkurlu is an Assistant Professor in the Department of Artificial Intelligence Engineering at TOBB University of Economics and Technology, where he has been affiliated since 2014. Previously, he served as a Postdoctoral Research Associate at West Virginia University (2010-2013). He holds a PhD and MS in Computer Science from Rensselaer Polytechnic Institute, and a BS from Bilkent University. His research spans algorithmic game theory , graph theory , and approximation algorithms , with applications in network design, operations research, and computer security. Key focus areas include equilibrium computation, coalition formation, resource allocation, and optimization in networked systems. His publications demonstrate consistent focus on game-theoretic modeling and algorithmic solutions, with recent work exploring Nash equilibria, social coalition structures, and security-aware systems. Earlier contributions address combinatorial optimization and network coding challenges.
Vincent Weaver is an Associate Professor in the Electrical and Computer Engineering Department at the University of Maine's College of Engineering. He leads the VMW Research Group, focusing on low-level systems research including hardware performance counters, computer architecture, and operating systems. Weaver received his BS in Electrical Engineering from the University of Maryland College Park in December 2000, followed by MS (January 2009) and PhD (May 2010) degrees in Electrical and Computer Engineering from Cornell University. He joined the University of Maine faculty in July 2012 as an Assistant Professor and earned tenure and promotion to Associate Professor in September 2018. His research centers on hardware performance analysis, architectural simulation, and systems programming with emphasis on Linux kernel development and embedded systems. Weaver's work bridges theoretical computer architecture with practical systems implementation, often resulting in open-source tools that advance the field. His publications reveal a consistent focus on performance analysis techniques, code optimization, and security through low-level system understanding. Weaver maintains an active teaching schedule including courses in embedded systems, operating systems, and network engineering. He values students with strong programming skills and encourages open source contributions as part of the learning process. His research group provides hands-on experience with cutting-edge processor architectures and performance analysis tools.
Dr. Zhong Ling is an Assistant Professor of Economics at Cheung Kong Graduate School of Business (CKGSB). She holds a Ph.D. in Economics from Yale University and a B.A. in Mathematics and Economics from Swarthmore College (graduated with High Honors). Her primary affiliations include research roles at CKGSB where she focuses on labor dynamics, education economics, and workforce analysis. Her research interests center on three interconnected domains: Labor Economics : Examining wage structures, skill demands, and gender disparities in employment Economics of Education : Investigating returns on educational investment and policy impacts Personnel Economics : Analyzing employer-employee relationships and workplace organization Recent publications demonstrate a strong focus on pandemic-related economic impacts, including labor market transformations during COVID-19, epidemiological modeling for public policy, and resource allocation strategies during health crises. Her work frequently employs advanced statistical modeling and interdisciplinary approaches. Awards & Fellowships: University Dissertation Fellowship, Yale University (2018-2019) Carl Arvid Anderson Prize Fellowship (2017) Phi Beta Kappa induction (2013) Multiple Yale scholarships including Fan Family Fellowship and Daniel Lathrop Lawton Scholarship Media engagements include expert commentary for CGTN on China's birth rate policies and workforce involution trends, showcasing her public policy relevance.
Hamed Hamzeh serves as Lecturer in Data Science at the School of Computer Science and Engineering, University of Westminster, and is affiliated with the Centre for Parallel Computing. His academic credentials include a Ph.D. in Cloud Computing from Bournemouth University and an MSc in Data Science from Istanbul Sehir University, Turkey. Dr. Hamzeh's research centers on cloud-native resource management, computer networks, and multi-agent systems, with groundbreaking work on fairness in cloud resource allocation. He developed novel algorithms including H-FFMRA and MRFS that address multi-resource scheduling in heterogeneous environments. His expertise spans AWS, Kubernetes, Python, and optimization techniques, bridging theoretical cloud computing with industrial applications in orchestration and resource management. Analysis of his 11 publications (2017-2023) reveals an evolving research trajectory: beginning with network bandwidth allocation (2017), advancing to cloud resource fairness (2018-2021), and culminating in cloud-to-things continuum orchestration (2023). This progression demonstrates increasing system complexity while maintaining core focus on fairness metrics across distributed environments. Dr. Hamzeh actively contributes to the academic community as technical committee member for IEEE ICCCS and Distributed AI conferences, and as reviewer for Springer's Journal of Grid Computing and Journal of Supercomputing. His service reflects recognition within cloud computing research circles. Prospective students receive supervision in Cloud Computing, Artificial Intelligence, Machine Learning, Software Engineering, and Computer Networks. Current research opportunities emphasize practical implementation of resource allocation algorithms in cloud-native environments through the Centre for Parallel Computing.
