Sudhakar Ganti is an Associate Professor in the Department of Computer Science at the University of Victoria, part of the Faculty of Engineering and Computer Science. He holds a PhD from the University of Ottawa. His research focuses on cloud computing resource management, software-defined networking (SDN), traffic management, quality-of-service optimization, and performance evaluation through queueing theory. His work bridges theoretical frameworks with practical applications in network efficiency and distributed systems. Dr. Ganti’s expertise includes optimizing resource allocation in fog-cloud systems, enhancing telehealth IoT energy efficiency, and developing dynamic defense frameworks for SDN security. His contributions span network traffic prediction, large file transport protocols, and formal verification of networking systems. He has published extensively in top-tier conferences and journals, addressing challenges in distributed computing, cyber security, and edge computing. His research trends emphasize leveraging reinforcement learning for fog-cloud resource allocation, multi-objective optimization in IoT, and SDN-driven network security. Earlier work includes foundational studies on optical router bypass, cloud workload characterization, and conversational agents for smart environments. Despite his prolific output, no academic awards or grants are explicitly mentioned in his profile.
Associate Professor Archie Chapman is an Associate Professor in Computer Science and Deputy Director (Teaching and Learning) at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on applying artificial intelligence, game theory, optimization, and machine learning to address challenges in future power systems, including renewable energy integration and battery storage optimization. Prior to UQ, he held roles as a Research Fellow in Smart Grids at the University of Sydney (2011-2019) and a postdoc at the University of Southampton (2009-2010), where he completed his PhD in 2004. Research interests include: - Large-scale optimization for energy systems - Demand response and peer-to-peer energy trading - Renewable energy integration and grid stability - Battery storage strategies for smart grids - Algorithmic game theory for energy market design Notable projects: - Bruny Island battery trial for network congestion management - Analysis of tariff impacts on solar households - Development of decentralized energy management frameworks Publications span over 100 articles, with recent work focusing on: - Prosumer battery systems and capacity firming (2025) - Unbalanced optimal power flow benchmarks (2024) - P2P energy trading mechanisms (2021-2023) Expertise includes: - Techno-economic analysis of energy systems - Distributed optimization algorithms - Policy and market design for renewable integration
Ashish Cherukuri is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Optimization and Decision Systems group. His research focuses on optimization-based control, game theory, and multi-agent systems applied to energy, transportation, and robotics. He holds a Ph.D. from UC San Diego and postdoctoral experience at ETH Zurich. Education: Ph.D., University of California, San Diego (2012–2017) M.Sc., ETH Zurich (2008–2010) B.Tech, Indian Institute of Technology Delhi (2004–2008) Research Interests: Data-driven optimization, distributed algorithms, networked cyber-physical systems, and uncertainty handling in energy and transportation systems. Recent work emphasizes stochastic optimization, game-theoretic routing, and risk-aware control. Awards: Robert E. Skelton Dissertation Award (2017) Outstanding Graduate Student Award (2016) Focht-Powell Fellowship (2012–2015) Grants & Service: Editor for the IEEE Control Systems Society, organizer of Energy-Open 2019, and member of professional societies (IEEE, INFORMS, SIAM). Active in conference organization and academic leadership roles. Labs/Teams: Part of the Jan C. Willems Center for Systems and Control and the Engineering and Technology Institute Groningen (ENTEG). Research integrates theoretical advancements with practical applications in energy networks and smart systems.
Professor Frank Kelly holds the Professor of the Mathematics of Systems at the University of Cambridge , affiliated with the Department of Pure Mathematics and Mathematical Statistics (DPMMS). His work bridges theoretical insights with practical applications in random processes , networks , and optimization . Academic Rank: Professor Department: DPMMS Research Themes: Stochastic systems, network resource allocation, mathematical modeling Kelly’s research focuses on stochastic networks , including congestion control in communication systems, fair bandwidth sharing , and electricity grid optimization . His work often incorporates proportional fairness principles and Markov models to analyze complex systems. Recent publications reveal a trajectory in network dynamics and resource allocation , with applications to electric vehicles, satellite routing, and virtualized networks. His work shows interdisciplinary impact across computer science , telecommunications , and energy systems . Kelly has contributed foundational works like Stochastic Networks (2014) and pioneered models for loss networks and congestion control . He maintains active collaborations and has advised on policy matters, including spectrum auctions and network regulation.
Professor Mohammed Salamah is a distinguished faculty member in the Computer Engineering Department at Eastern Mediterranean University's Faculty of Engineering. He maintains an office in room 114 and can be contacted at +90 392 630 1149/1334 or via email at muhammed.salamah@emu.edu.tr. His academic website provides additional resources for students and colleagues. Dr. Salamah earned his BS, MS, and PhD degrees in Electrical and Electronics Engineering from Middle East Technical University in 1988, 1990, and 1996 respectively, establishing a strong foundation for his career in network communications and wireless systems. His research interests span multiple critical areas in modern networking, with particular expertise in Wireless Sensor Networks, Internet of Things (IoT) security, Mobile Communications, and Energy Efficiency in network protocols. Professor Salamah has made significant contributions to the understanding of network security mechanisms, trust management systems, and optimization of wireless communication protocols. An analysis of his recent scholarly output reveals a strong focus on security challenges in IoT communication systems, controller placement optimization in software-defined wireless sensor networks, and trust-based malicious node detection schemes. His work demonstrates consistent attention to practical network performance issues while addressing emerging challenges in next-generation communication technologies. Throughout his academic career, Professor Salamah has demonstrated exceptional commitment to student mentorship, supervising numerous graduate students through their research journey. His administrative contributions include service as an associate editor, reviewer, and session chair for academic conferences. His laboratory work focuses on practical implementations of wireless communication protocols, with emphasis on energy efficiency, security mechanisms, and performance optimization for various network architectures including cellular networks, cognitive radio systems, and wireless sensor networks.
Britta Peis is a Professor of Management Science at RWTH Aachen University since September 2013. She studied Mathematics and Sports Sciences at the University of Cologne and German Sport University Cologne, respectively. Her academic journey includes positions at TU Dortmund (2006-2007), TU Berlin (2007-2010), and a visiting professorship at Otto-von-Guericke University Magdeburg (2010-2011). Her research focuses on Combinatorial Optimization , Algorithmic Discrete Mathematics , Routing and Scheduling , Robust Optimization , and Algorithmic Game Theory . Her work spans theoretical and applied domains, including network flow analysis, auction algorithms, and strategic decision-making in complex systems. Recent publications (2025-2024) highlight advancements in dynamic auction mechanisms, Stackelberg game formulations, and train routing algorithms. Earlier works (2022-2018) explore matroid theory, packet routing with priority lists, and sensitivity analysis in polymatroid optimization. Key trends include algorithmic design for competitive networks and robustness in time-dependent flows. She is affiliated with the Graduiertenkolleg UnRAVeL (Aachen Institute for Discrete Mathematics and Logic) and contributes to the Chair of Management Science's research agenda in combinatorial optimization and algorithmic game theory.
James R. Perkins is an Associate Professor in the Department of Manufacturing Engineering at Boston University's College of Engineering. His primary affiliations span the Mechanical Engineering, Product Design & Manufacturing, and Systems Engineering departments as both primary and affiliated faculty within the university's academic structure. Education: B.A. in Engineering Science from Harvard University (June 1986) M.S. in Electrical Engineering from University of Illinois at Urbana-Champaign (January 1990) Ph.D. in Electrical Engineering from University of Illinois at Urbana-Champaign (October 1993) Professor Perkins' research focuses on systems engineering with emphases on control, decision analysis, and scheduling theory. As a member of the Boston University Operations Research and Manufacturing Systems group, his work spans real-time scheduling and control of manufacturing systems, supply chain management, resource pricing and congestion control in communications networks, and scheduling human resources in transportation systems and product development. Current projects include synchronization and scheduling of manufacturing systems, data mining and clustering in genetic networks, and analytical solutions of controlled queueing networks. His manufacturing-related research is performed in the Production Control of Manufacturing Systems (PCMS) Laboratory at Boston University. Analysis of Professor Perkins' publication record reveals strong trends in manufacturing systems optimization, with particular emphasis on scheduling algorithms, production control, and resource allocation. His work bridges theoretical operations research with practical applications across manufacturing, communications networks, and product development. Over the past two decades, his research has evolved from fundamental control theory in manufacturing systems to more complex applications involving wireless networks, supply chain management, and new product development, demonstrating remarkable adaptability and interdisciplinary reach. Scientific Awards: NSF Research Initiation Award (1994-1998) IBM Manufacturing Research Graduate Fellowship (1989-1991) John Harvard Scholarship (1985-1986) Harvard College Scholarship (1984-1985) Professor Perkins has served as Principal Investigator for several significant research projects, including "Efficient Control of Manufacturing Systems with Buffer Costs" (NSF Research Initiation Award, 1994-1998) and "Managing the New Product Development Portfolio and Pipeline: An Integrated Approach" (NSF, 1999-2001). He was also Principal Director of a Graduate Assistance in Areas of National Need (GAANN) Award from the Department of Education (1997-2000) and Co-Principal Investigator on projects with Nokia Research Center and NSF. His teaching portfolio includes advanced courses in scheduling models, engineering mathematics, production systems analysis, and statistics and quality engineering, where he has developed new curriculum for specialized topics. Professor Perkins conducts his manufacturing-related research in the Production Control of Manufacturing Systems (PCMS) Laboratory at Boston University. His work often involves collaboration with colleagues such as Professor R. Srikant and Professor P. R. Kumar from the University of Illinois. His research group focuses on developing theoretical frameworks and practical solutions for complex scheduling and control problems across various domains including manufacturing, communications, and transportation systems, with an emphasis on mathematical rigor and real-world applicability.
Dr. Damian Nale Dailisan is a Lecturer in the Department of Humanities, Social and Political Sciences at ETH Zürich, affiliated with the Computational Social Science group. He holds a Ph.D. in Physics from the University of the Philippines, specializing in traffic modeling and machine learning applications. His research focuses on multi-agent systems, particularly in transportation and urban systems. He has held postdoctoral roles and contributed to projects like the ACCeSs@AIM lab. His work bridges computational methods with real-world challenges, including traffic control optimization, AI-driven decision-making, and smart city infrastructure. Notable projects include FAIRLANE for priority lane management and studies on democratizing traffic control systems. Dailisan’s publications span journals like Transportation Research Part C and IEEE Access, addressing topics such as reinforcement learning in traffic signals and ethical AI frameworks. He has presented at workshops like 'Back to the Future' at ETH Zurich and collaborates with interdisciplinary teams to enhance urban mobility solutions. His technical expertise includes Python, network analysis, and agent-based modeling, with contributions to open-source tools for earthquake networks and social systems analysis.
Dr. Vera Tilson is an Associate Professor at the Simon Business School, University of Rochester, specializing in Healthcare Operations Management and Operations Management. Her research focuses on healthcare operations optimization, stochastic scheduling, and supply chain management. Prior to academia, she held roles as a software engineer and project manager in telecommunications, medical instrumentation, and finance. Her teaching interests include quantitative decision-making and healthcare operations, for which she received the MBA Superior Teaching Award in 2009. Her work bridges academic research with practical applications, addressing challenges such as patient no-show management, medication waste reduction, and healthcare GPO strategies. She has published extensively in journals like Management Science, MSOM, and Operations Research. Recent research explores emergency department workflow optimization, humanitarian supply chains, and real-time capacity management in healthcare settings. Her contributions highlight interdisciplinary approaches combining operations research, data science, and healthcare analytics.
Thomas Le Barbanchon is a Full Professor of Economics at Bocconi University since 2025 and holds the Rodolfo Debenedetti Chair in Labor Economics. He received his PhD from Ecole Polytechnique (CREST-ENSAE) in 2012 and has been affiliated with institutions like CEPR, CREST, J-PAL, LEAP, BIDSA, IGIER, IZA, and IFS. His research focuses on labor economics, particularly job search mechanisms, unemployment insurance effects, gender disparities, and labor market policy evaluation. Educational background: PhD in Economics (Ecole Polytechnique), MSc in Economics (Universitat Pompeu Fabra), Diplôme d'ingénieur statisticien-économiste (ENSAE), and Diplôme d'ingénieur (Ecole Polytechnique) Research highlights include: Quantifying the impact of unemployment insurance reforms in France Analyzing gender differences in job search behavior Studying the effectiveness of hiring credits during economic crises Investigating how traditional AI improves job matching Examining migrant-native job search segregation patterns Scientific contributions appear in top journals like American Economic Journal: Applied Economics , Quarterly Journal of Economics , and Review of Economic Studies . Awards include two ERC grants (2017 & 2024) and the Bocconi Impact Award (2022). He mentors PhD students in economics and labor policy, currently serves as Director of IGIER research center, and maintains active editorial roles at Review of Economic Studies and Journal of the European Economic Association .
Jetmir Haxhibeqiri is a Postdoctoral Researcher at Ghent University 's Faculty of Engineering and Architecture , Department of Information Technology. His work focuses on Time-Sensitive Networking (TSN) over wireless systems, WiFi optimization, and Industrial IoT solutions. Key projects: IMEC Postdoctoral Fellowship Collaborations: Jeroen Hoebeke (UGent), Ingrid Moerman (UGent), Xianjun Jiao (UGent) Research Interests : Wireless network coordination, SDN integration for heterogeneous networks, low-latency communication, and machine learning applications in network optimization. Specialized in WiFi-LPWAN coexistence , In-Band Network Telemetry , and Cross-Technology Synchronization . Recent Publications : 2025 work on Wi-Fi-UWB synchronization, 2024 studies on coordinated spatial reuse in WiFi 7, and 2022 research on hardware-efficient PTP clock synchronization. Contributions span from theoretical models to practical implementations in industrial environments. Technical Expertise : Network densification strategies, interference management, and performance evaluation of large-scale wireless deployments. Developed simulation frameworks for LoRaWAN and WiFi TSN, with a focus on ns-3 validation. Education : PhD in Industrial Wireless Communication (2019, Ghent University).
Leonard P. Wesley is an Associate Professor at the Computer Science Department, College Of Science, San Jose State University. With a Ph.D. and M.S. in Computer Science from University of Massachusetts and a B.A. in Physics and Math from Northeastern University, his work spans bioinformatics, pharmaceutical discovery, machine learning, robotics, and evidential reasoning. He has published extensively on SVM/QSAR-based drug prediction, autonomous systems, and uncertainty management. Ph.D., University of Massachusetts - Computer Science M.S., University of Massachusetts - Computer Science B.A., Northeastern University - Physics and Math His research focuses on developing predictive models for drug discovery, autonomous robotics, and data analytics. Recent publications emphasize SVM applications in medical diagnostics and pharmaceutical modeling. He has contributed to conferences in aerospace, robotics, and biotechnology, with invited talks at NASA and Los Alamos National Laboratory. 3D-QSAR & SVM prediction of drug inhibitors Evidential decision analytics Autonomous robotic control PCA/SVM-based sepsis diagnostics Hybrid network congestion management Professor Wesley teaches courses in artificial intelligence, bioinformatics, and advanced programming. His lab investigates applications of machine learning in biotechnology and aerospace, including biomarker identification and CFD expert systems. He has served as session chair at international conferences and collaborated with institutions like NASA and Advanced Decision Systems.
Juan Camilo Castillo is an Assistant Professor in the Department of Economics at the University of Pennsylvania, focusing on Industrial Organization, Microeconomic Theory, and Market Design. His work bridges theoretical insights with real-world applications in digital platforms, urban transportation, and public health economics. Ph.D., Economics, Stanford University (2020) M.S., Economics, Universidad de Los Andes (2013) B.S., Physics and Industrial Engineering, Universidad de Los Andes (2012) Castillo's research spans two primary domains: Online platforms and digital economy (e.g., market power in web search, service quality in ride-hailing) Market design for social challenges (e.g., vaccine distribution, drug market violence) Recent publications examine platform competition in web search, surge pricing impacts, and pandemic response strategies. His methodological approach combines field experiments, econometric modeling, and network analysis.
Dr. Aris Dimeas is a Researcher at the National Technical University of Athens in the Department of Electric Power and Industrial Applications . He holds a diploma and PhD in Electrical and Computer Engineering from NTUA and has extensive experience in power systems operations, renewable energy integration, and smart grid technologies. Specialized in AI applications for power systems Developed control software for demand side management Consultant for PPC (2007-2012) Research Focus : Smart grids and digital twin implementations Renewable energy market dynamics Microgrid optimization and control algorithms Collaborations : Active participant in EU research projects, collaborating with HEDNO and other energy grid operators on electronic meters and intelligent network deployments. Teaching : Instructs courses on electric energy systems, power system analysis, and energy management.
Vlahogianni Eleni is a Professor and Dean of the Department of Transportation Planning and Engineering at the National Technical University of Athens (NTUA). Her research focuses on integrating machine learning , quantum computing , and reinforcement learning with urban mobility and traffic engineering , addressing challenges in eco-routing , congestion pricing , and autonomous vehicle interactions . Her work emphasizes data-driven approaches to traffic forecasting, including quantum neural networks and theory-aware unsupervised learning . Recent publications explore mixed traffic environments , shared space modeling , and parking occupancy prediction , highlighting her commitment to advancing intelligent transportation systems . Professor Vlahogianni leads the Traffic Engineering Laboratory at NTUA and contributes to policy frameworks for connected and automated transport , wildfire resilience , and dynamic mobility solutions . She is actively involved in the LEVITATE project and advocates for explainable AI in transportation applications.
