جست‌وجوی استاد و پژوهشگر

Gary Tan Soon Huatمشاهده پروفایل

دانشیار

• Parallel and Distributed Systems
• Symbiotic Simulation
• Traffic Simulation
• +۵ مورد دیگر

Gary Tan Soon Huat serves as Associate Professor (Educator Track) and Vice-Dean of Student Life at the National University of Singapore's School of Computing, Department of Computer Science. With over three decades of continuous service since 1990, he has established himself as a leading educator and researcher in parallel and distributed systems. His educational background includes a B.Sc (1st class Honours) from NUS, followed by M.Sc and Ph.D degrees from the University of Manchester, UK. As a pioneer in NUS's Direct Honours Programme, his academic journey reflects deep institutional commitment. Tan's research focuses on parallel and distributed computing , symbiotic simulation , and traffic and crisis management simulation . His work bridges theoretical computer science with practical applications in disaster response systems, where he develops frameworks that analyze real-life video feeds to model human movement during emergencies. This research has evolved from foundational work on High Level Architecture and Data Distribution Management to current innovations like the Conscious Movement Model (CMM) that extracts behavioral patterns from CCTV footage. His publication record spans nearly three decades, showing a clear evolution from neighborhood-based multiprocessor scheduling to sophisticated GPU-accelerated traffic simulations and crisis management frameworks. The research demonstrates consistent focus on distributed systems while adapting to emerging technologies like deep learning and GPU computing. ASIASIM FELLOW 2016 NUS Annual Teaching Excellence Awards (03/04, 04/05, 06/07) School Teaching Excellence Awards (1999, 2002, 2016) Faculty of Science Teaching Awards (1992, 1998) ATEA Honour Roll 2008 As an educator, Tan has supervised PhD candidates Wang Chengxin and Muhammad Shalihin bin Othman, focusing on pedestrian movement analysis during crises. His leadership extends beyond research to academic service, including roles as Program Chair of DSRT 2016, Conference Co-chair of SIMUTOOLS 2016, and President of both the Society of Simulation and Gaming of Singapore and the ASIASIM federation. His administrative contributions include serving as Master of Sheares Hall (2003-2013) and current Vice-Dean of Student Life. Tan leads the Modelling and Simulation Group within NUS's Computer Systems Lab, collaborating internationally with KTH (Sweden), FOI (Swedish Defence Research Agency), SMART, and Beihang University. His team's work bridges academic research with practical applications in transportation systems and emergency response planning.

Samitha Samaranayakeمشاهده پروفایل

دانشیار

• Transportation Systems Engineering
• Network Science and Computation
• Algorithms
• +۴ مورد دیگر

Samitha Samaranayake is an Associate Professor in the Engineering Management Program at Cornell University's School of Civil and Environmental Engineering. He holds affiliations with Applied Information Systems, Applied Mathematics, Operations Research and Information Engineering, and Systems Engineering. Education: B.S. in Computer Science (MIT, 2002) M.Eng. in Electrical Engineering and Computer Science (MIT, 2003) M.S. in Management Science and Engineering (Stanford University, 2009) Ph.D. in Systems Engineering (UC Berkeley, 2014) Research Interests: Focuses on optimizing urban transportation systems through cyber-physical systems integration, stochastic network algorithms, and sustainable mobility solutions. Specializes in mobility-on-demand systems, dynamic traffic control, and real-time transportation analytics. Awards: 2012 Dwight David Eisenhower Graduate Fellowship 2016 ACSF Rapid Response Grant ($20,688 with Timur Dogan) Professional Experience: Postdoctoral Associate at MIT's Laboratory for Information and Decision Systems (2014-2015), researcher at Singapore-MIT Alliance for Research and Technology (SMART), and industry experience at Google, Oracle, Synopsys, and INRIA. Labs/Teams: Leads the Samitha Samaranayake Group, collaborating on projects like the National Academy of Engineering's 2024 Frontiers of Engineering Symposium.

Raja Senguptaمشاهده پروفایل

استاد

• Transportation Engineering
• Wireless Communications
• Inertial Navigation for Vehicle Systems
• +۵ مورد دیگر

Raja Sengupta is a Professor at the Department of Civil and Environmental Engineering, University of California, Berkeley. He has been actively involved in research spanning automated cars, drones, wireless networking, and control theory , with a focus on translating academic work into market-ready solutions through industry collaborations. Education : Ph.D. and M.S. in Systems Engineering from the University of Michigan; B.S. in Electrical Engineering from Jadavpur University, India Research Expertise : Transportation systems, wireless communication protocols, and inertial navigation for autonomous vehicles His recent work emphasizes Urban Air Mobility (UAM) , including vertiport network design and eVTOL fleet dynamics. He has also pioneered autonomous UAV structural inspection systems and developed patented technologies for vehicle-to-vehicle communication with Toyota and BAE Aerospace. Notably, he co-founded the successful startup Automatic.com and currently serves as CEO of Responsiblerobotics.com . Key awards include: USDOT’s Connected Vehicle Technology Award (2011) UC Berkeley Energy and Climate Lectures Innovation Award (2014) His research has been standardized by SAE international as J2945 for car-to-car networking , demonstrating significant industry impact.

Giuliano Punzoمشاهده پروفایل

مدرس

• Control Theory
• Complex Systems
• Network Theory
• +۴ مورد دیگر

Dr Giuliano Punzo is a Lecturer in the School of Electrical and Electronic Engineering at The University of Sheffield. His research focuses on complex systems, control theory, and socio-technical interactions. He explores resilience in infrastructure networks, transportation systems, and decision dynamics through network theory and game theory frameworks. Education: Aerospace Engineering background Research Themes: Complex dynamics, socio-technical systems, resilience engineering, and evolutionary networks Recent projects include analyzing road network impacts on economic performance, decision-making in non-spatially embedded networks, and cooperative strategies for infrastructure resilience. He has secured grants totaling over £5 million, including leadership roles in STFC and Innovate UK projects. Teaching responsibilities include control systems design and aerospace engineering courses. His work bridges engineering and social sciences, addressing challenges in urban infrastructure resilience and multi-layer network dynamics.

Xuyun Zhangمشاهده پروفایل

دانشیار

• Scalable Machine Learning
• Big Data Privacy
• Cyber Security
• +۵ مورد دیگر

Dr. Xuyun Zhang is an Associate Professor at the School of Computing, Macquarie University, Australia. He holds a PhD from University of Technology Sydney (2014), and Master's/Bachelor's degrees from Nanjing University (China). His research focuses on scalable machine learning, big data privacy, cyber security, edge computing, and IoT. He has led 11 research projects including Next-Gen Banking (2024-2028) and Scalable Document Intelligence (2022-2027). His work spans secure AI, privacy-preserving techniques, and edge-cloud collaboration. He has received awards such as the Chancellor's Best PhD Thesis (2015) and Early-Career Research Excellence (2019). His recent publications address areas like metaverse service offloading, hypergraph trust prediction, and federated learning frameworks. He actively organizes conferences like the Australasian Information Security Conference (2017) and chairs industry-research initiatives in cloud computing and mobile networking. Education: PhD (UTS, 2014), MEng (Nanjing University, 2011), BSc (Nanjing University, 2008). Teaching includes Machine Learning in Cybersecurity, Data Science, and Software Engineering. Key research contributions include privacy-preserving publishing, edge computing offloading methods, and blockchain-based secure access management. His projects often integrate AI with cloud-edge systems to address real-world challenges in finance, healthcare, and smart manufacturing.

Johan van Leeuwaardenمشاهده پروفایل

استاد

• Queueing Theory
• Stochastic Processes
• Load Balancing
• +۱ مورد دیگر

Johan van Leeuwaarden is a Full Professor specializing in stochastic operations research, with expertise in queueing theory, load balancing, and random graph analysis. His work develops mathematical models for large-scale systems like cloud networks and service industries. He analyzes heavy-traffic regimes and distributionally robust optimization for systems with uncertain parameters. Current research includes appointment scheduling under service time uncertainty and learning algorithms for dynamic resource allocation.

• Transportation Engineering
• Traffic Flow Theory
• Dynamic Traffic Assignment
• +۱۰ مورد دیگر

Vittorio Astarita is an Associate Professor in the Department of Civil Engineering at the University of Calabria, Faculty of Engineering, where he teaches courses such as Teoria del Traffico e della Circolazione , Sistemi di Trasporto , Trasporto Merci e Logistica , and Laboratorio di Trasporti . He is actively involved in research, teaching, and leadership of major national and EU-funded projects. His research interests include Traffic Flow Theory , Dynamic Traffic Assignment , Intelligent Transportation Systems (ITS) , Traffic Simulation , Road Safety , and Sustainable Transport Infrastructure . His work integrates advanced modeling techniques, machine learning, and digital twin technologies to improve transportation systems. The recent publications highlight a strong trend toward applying artificial intelligence and data science to transportation safety, crash prediction, fuel efficiency, and smart mobility. Topics such as Support Vector Machines, Learning Vector Quantization, and Digital Twins are central to his current research direction. CNR Research Fellowship (1995–1996) International Research Scholarship, University of Naples Federico II (1997) Lead funding for CNR Project CNRG008430 (2001) Coordinator of €500,000 'Master in Management of Transport' Principal Investigator of PON M2M Project (€4.7 million, €2.75 million to University of Calabria) Astarita has supervised significant research grants and led international collaborations with MIT and the University of Montreal. He has also organized multiple scientific conferences and contributed to editorial processes. He leads the Laboratorio didattico di ingegneria dei trasporti , focusing on teaching and practical training in transport engineering.

Mahdi Doostmohammadiمشاهده پروفایل

مدرس

• Mixed Integer Optimization
• Polyhedral Theory
• Mathematical Programming
• +۷ مورد دیگر

Mahdi Doostmohammadi is a Lecturer (Assistant Professor) in Operational Research at the Department of Management Science, Strathclyde Business School, University of Strathclyde since 2018. He holds a B.Sc. and M.Sc. in Applied Mathematics from the University of Isfahan (2004, 2007) and a Ph.D. in Operational Research from the University of Aveiro (2014). Prior roles include Post-Doctoral positions at Strathclyde and Instituto Superior Técnico (Lisbon), and a Lecturer position at the University of Edinburgh's School of Mathematics. Education: B.Sc. Applied Mathematics (Computer Science), University of Isfahan, 2000–2004 M.Sc. Mathematics (Optimization and Optimal Control), University of Isfahan, 2005–2007 Ph.D. Operational Research (Distinction), University of Aveiro, 2009–2014 Research Interests: Focus on Mixed Integer Optimization , Polyhedral Theory , Network Optimization , and their applications in production planning, transportation, and metabolic engineering. His work bridges theoretical developments with practical challenges in supply chains, healthcare, and renewable energy systems. Publications Trends: Recent articles emphasize optimization algorithms for supply chain design, healthcare decision-making, renewable energy infrastructure, and metabolic engineering. Methodological strengths include mixed-integer programming and system dynamics modeling. Scientific Awards: First Award of B.Sc. graduates in Mathematics, 2004 Ph.D. with Distinction in Operational Research, 2014 Advising & Grants: Directs MSc programs in 'Data Analytics' and online 'Operational Research'/'Business Analysis and Consulting'. Active in peer review for journals like Journal of the Operational Research Society and Computers & Operations Research .

• Computer Networks
• Software-Defined Networking (SDN)
• Telecommunications
• +۵ مورد دیگر

José Manuel Arco Rodríguez is an Associate Professor in the Department of Automation at the Universidad de Alcalá (Spain). He holds a Doctorate from the same institution for his thesis Propuesta de optimización de la interconexión de redes con calidad de servicio para aplicaciones multimedia (2000), supervised by Dr. Daniel Meziat Luna. His research focuses on intelligent networks, software-defined networking (SDN), edge computing, and telecommunication systems, with particular emphasis on network optimization, protocol design, and AI integration in network architectures. He leads the NetIS research group (Networks and Intelligent Systems), exploring cutting-edge solutions for scalable, reliable data center networks and industrial IoT ecosystems. Key research areas include in-band network control, hybrid SDN architectures, multi-hop edge computing with IoT devices, and low-latency bridging protocols. His work spans theoretical frameworks to hardware implementations (e.g., NetFPGA), with a strong emphasis on practical applications in data centers, campus networks, and industrial environments. Recent contributions address AI-driven network management, plug-and-play routing protocols, and zero-configuration network architectures. Publications highlight advancements in SDN topology discovery (TEDP), scalable addressing (GA3), and path exploration protocols (ARP-Path, All-Path Bridging). His research bridges theoretical networking principles with real-world deployment challenges, often emphasizing interoperability between legacy and modern systems. Arco Rodríguez has collaborated on EU-funded projects and contributed to international standards for network protocols. His lab (NetIS) actively develops open-source tools for network analysis and simulation. Current research trends include AI-enhanced softwarized networks and cloud-edge continuum architectures for IIoT.

Luis de la Cruz Pirisمشاهده پروفایل

استادیار

• Network Optimization
• Cybersecurity
• Intelligent Transportation Systems
• +۳ مورد دیگر

Luis de la Cruz Piris is an Assistant Professor in the Department of Telematics Engineering at Universidad de Alcalá. His research focuses on network optimization, cybersecurity, and intelligent transportation systems. He is part of the NetIS research group (Networks and Intelligent Systems). He earned his Ph.D. in 2019 with a thesis on multi-objective optimization strategies for vehicle coordination at urban intersections, supervised by Dr. Iván Marsá Maestre and Dr. Miguel Ángel López Carmona. His research interests include wireless network optimization (e.g., Wi-Fi channel assignment), IoT security frameworks, and AI-driven threat mitigation. Notable projects include the EnvAdapt-CRO-SL algorithm for dynamic channel management and CloudWall, a resilient healthcare IT infrastructure framework. Recent work explores unsupervised learning for cybersecurity, cooperative approaches to Wi-Fi performance, and distributed multi-agent systems for network resilience. His publications span topics like smart traffic light management, OAuth token configuration in IoT, and fuzzy ontology-based driver behavior analysis.

• Operations Research
• Public Transport Optimization
• Urban Logistics
• +۳ مورد دیگر

Stephan Bütikofer is a researcher at the Zurich University of Applied Sciences (ZHAW), School of Engineering, specializing in operations research and transportation systems. He focuses on public transport optimization, railway timetabling, urban logistics, and network modeling. His work integrates customer behavior and infrastructure constraints into scheduling algorithms. Current Projects: Smart UMH (urban multihub logistics), Customer-oriented Traffic Management Systems, and automated timetable planning. Research Themes: Mesoscopic infrastructure modeling, periodic timetabling with PESP/FPESP, energy optimization in vessel operations, and ULD stock allocation in air transport. Recent Publications: Address periodic timetabling with travel chain integration, maintenance scheduling stability, and graph contraction for railway optimization. Keywords: Operations Research, Public Transport, Network Analysis. Collaborations: Regularly works with ETH Zurich, RWTH Aachen University, and Swiss transport stakeholders like SBB and Swiss International Air Lines.

Ilgin Gulerمشاهده پروفایل

دانشیار

• Transportation Engineering
• Intelligent Transportation Systems
• Traffic Signal Control
• +۸ مورد دیگر

Ilgin Guler is an Associate Professor in the Department of Civil and Environmental Engineering at Pennsylvania State University’s College of Engineering. Her research focuses on intelligent transportation systems, traffic operations, infrastructure sustainability, and equitable mobility solutions. She contributes to interdisciplinary projects such as the Equitable Optimization of Transportation Systems and Services addressing climate and sustainability challenges. Her research interests span Transportation Engineering , Intelligent Transportation Systems , Traffic Signal Control , Connected Vehicles , Pavement Management , and Transit Signal Priority . She applies advanced techniques including deep learning and optimization to improve urban and rural transportation systems. Her work emphasizes safety, equity, and sustainability in infrastructure planning and operations. The recent publications highlight a strong trend in integrating machine learning with classical traffic theory, enhancing infrastructure resilience through data-driven maintenance, and evaluating shared mobility impacts on safety and equity. Her research bridges civil engineering with data science, focusing on real-world applications in Pennsylvania and beyond. Scientific Awards: No awards explicitly mentioned in the provided text. She advises graduate students in transportation engineering and has been involved in multiple research projects, including seed-funded initiatives from the Institute for Energy and the Environment (IEE). While specific grant amounts and student names are not listed, her collaborative work with faculty like Vikash Gayah and Anik Sengupta indicates active mentorship and team leadership. Her research is associated with initiatives such as the Equitable Communities and the Built Environment and leverages tools from connected vehicle technology, impact-echo testing, and generative AI for infrastructure assessment.

Jiaoyang Liمشاهده پروفایل

استادیار

• Artificial Intelligence
• Multi-Agent Path Finding (MAPF)
• Robotics Coordination
• +۷ مورد دیگر

Jiaoyang Li is an Assistant Professor at Carnegie Mellon University's Robotics Institute. She earned her Ph.D. in Computer Science from the University of Southern California in 2022, advised by Sven Koenig, and her B.Eng. from Tsinghua University's Department of Automation. Research Interests: Multi-Agent Path Finding (MAPF), large-scale robot coordination, automated warehousing, multi-arm assembly systems, autonomous vehicle traffic management, and heuristic search algorithms. Key Research Areas: Foundations of MAPF, environment optimization for multi-agent systems, robust execution frameworks, learning-guided planning, and multi-arm coordination. Scientific Contributions: She has published extensively in ICAPS, IJCAI, AAAI, and SoCS conferences. Her work includes award-winning solutions for the NeurIPS 2020 Flatland Challenge, which involved coordinating thousands of agents in railway systems. Notable Awards: ICAPS-24 Best Student Paper, IFAAMAS Victor Lesser Distinguished Dissertation Award, USC Stevens Best Dissertation Award, and multiple competition wins. Leadership and Outreach: She has organized symposium tracks and workshops at ICAPS and AAMAS. Her research has practical applications in Amazon Robotics, airport taxiway planning, and real-time multi-robot execution systems.

• Operations Research
• Machine Scheduling
• Robust Optimization
• +۵ مورد دیگر

Dr. Han Hoogeveen serves as an Associate Professor in the Department of Information and Computing Sciences within the Faculty of Science at Utrecht University. His research focuses on applied operations research, particularly in transportation systems and robust optimization. Hoogeveen obtained his PhD from Eindhoven University of Technology for research on Single Machine Bicriteria Scheduling problems, conducted at the Centrum voor Wiskunde en Informatica (CWI) in Amsterdam under Jan Karel Lenstra. His research interests center on developing robust solutions for real-world planning problems, especially in transportation systems. He has pioneered research on finding solutions that remain feasible during small disruptions, with applications in railway operations, airport management, and public transportation. His work combines theoretical algorithm development with practical implementation through collaborations with major Dutch companies including NS (Dutch Railways), KLM, Amsterdam Airport Schiphol, and Qbuzz. Hoogeveen co-founded an Operations Research group with Marjan van den Akker, which evolved into the AI and Mobility Lab. His research has produced significant practical applications including gate assignment systems for Schiphol Airport, bus scheduling for Qbuzz, and shunting plans for NS. In 2021, he was conducting research for improving planning of city hubs and KLM operations through the kickstart AI initiative. Dr. Hoogeveen has supervised multiple PhD students including Guido Diepen (gate assignment), Marcel van Kooten Niekerk and Jan Posthoorn (bus scheduling), and Roel van den Broek (shunting plans for NS). His work exemplifies his philosophy that successful research must address real-world problems where 'we are not interested in the color of the hood, but in what is running beneath it'.

• Operations Research
• Optimization
• Healthcare Operations
• +۳ مورد دیگر

Farbod Farhadi is a researcher at Roger Williams University , affiliated with the School of Business . His work bridges operations research, optimization, and healthcare logistics, with a focus on solving complex scheduling problems in clinical and industrial settings. His research spans multiple domains: Healthcare operations (hemodialysis center scheduling) Lean manufacturing (U-shaped cells, human factors) Air traffic scheduling (branch-and-price algorithms) Metaheuristics for runway and facility location problems Recent publications emphasize exact optimization models, predictive analysis, and practitioner-oriented solutions for technician cost reduction.