جست‌وجوی استاد و پژوهشگر

Ahmed F. Abdelghanyمشاهده پروفایل

استاد

• Airline Management
• Transportation Systems
• Operations Research
• +۳ مورد دیگر

Dr. Ahmed F. Abdelghany is an Associate Dean for Research and Professor of Operations Management at the College of Business, Embry-Riddle Aeronautical University. He holds a doctorate in Civil Engineering: Transportation Systems from the University of Texas at Austin (2001). His career includes roles as an analyst/senior analyst at United Airlines, Chicago, and authorship of Modeling Applications in the Airline Industry (Ashgate Publishing, 2010). Education: Ph.D., Civil Engineering (Transportation Systems), University of Texas at Austin, 2001 Research focuses on airline management, operations competition, transportation planning, and simulation. He actively participates in projects on commercial airlines, NextGen air traffic systems, and complex transportation modeling. His work spans peer-reviewed journals like European Journal of Operational Research and Journal of Air Transport Management , with recent emphasis on geospatial analysis, econometric forecasting, and data-driven scheduling optimization. Consulting and research projects address airline efficiency, market dynamics, and sustainable air service development. No scientific awards are listed, but he maintains industry partnerships through professional short courses in aviation and transportation sectors.

Zhenhui Yuanمشاهده پروفایل

استادیار

• Machine Learning
• Networking
• IoT
• +۸ مورد دیگر

Zhenhui Yuan is an Assistant Professor at the University of Warwick, School of Engineering, leading the Connected Robotics Lab. He holds a BEng in Software Engineering from Wuhan University (2008) and a PhD in Electronic Engineering from Dublin City University (2012). His research focuses on machine learning in networking, IoT, and robotics, with expertise in UAV communications, edge AI, and vehicular networks. Prior roles include Senior Lecturer at Northumbria University (2020–2023), Associate Professor at Hangzhou Dianzi University (2015–2019), and co-founder/CTO of RobSense Technology (2015–2019). He has received Best Paper Awards at IEEE ICCRE 2016 and IEEE BMSB 2014. His research interests span machine learning applications in networking, robotics, and IoT, with emphasis on UAV swarm systems, edge computing, and quality-of-service optimization. He serves as a Guest Editor for IEEE journals and chairs workshops on 6G-empowered robotic vehicles. He leads projects funded by the University of Warwick (£9k), British Academy (£9k), and Horizon Europe (£92k), among others. His work includes developing the Connected Robotics Lab’s testbeds for 5G emulation and drone swarm control. Key achievements include pioneering AirSlice (UAV network slicing), founding the SwarmLink radio, and advancing video quality metrics for 3D streaming. He actively supervises PhD candidates and collaborates on grants addressing holographic telesurgery, multimodal transport networks, and EV optimization. His labs focus on hardware-in-the-loop emulation and edge AI for robotic systems.

Ningshi Yaoمشاهده پروفایل

استادیار

• Control Systems
• Human-Robot Interaction
• Cyber-Physical Systems
• +۵ مورد دیگر

Ningshi Yao is an Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University. Her research focuses on control systems, human-robot interaction, and bio-inspired robotics. She holds a PhD from Georgia Institute of Technology (2020) and a BS in Automatic Control from Zhejiang University (2014). Prior to her current role, she was a postdoctoral research fellow at Georgia Tech (2020-2021). Her work emphasizes real-time scheduling, cyber-physical systems, and machine learning applications. Notable projects include developing contention-resolving control methods for resource-constrained systems and creating lighter-than-air autonomous blimps for efficient navigation. Recent achievements include dual awards for groundbreaking robotics research (2025). Dr. Yao collaborates with faculty and students on cutting-edge robotics systems, such as blimps for rapid environmental response and medical robotics for ocular imaging. Her lab, part of George Mason's MARC initiative, explores autonomy, robotics, and ethical AI integration.

• Reinforcement Learning
• Electric Vehicle Technology
• Optimization Algorithms
• +۴ مورد دیگر

Arnob Ghosh is an Assistant Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT). His research focuses on reinforcement learning, optimization algorithms, and their applications in smart grid systems, electric vehicle infrastructure, and spectrum management. He has contributed significantly to areas such as multi-agent decision-making under constraints, dynamic resource allocation, and AI-driven hardware design. With an h-index of 9 and over 88 publications, his work bridges theoretical advancements with practical implementations in transportation, energy systems, and telecommunications. Research interests include developing efficient algorithms for constrained Markov decision processes, designing intelligent charging solutions for electric vehicles, and optimizing spectrum access in heterogeneous networks. His recent work explores safe reinforcement learning frameworks, dynamic routing of mobile charging stations, and leveraging large language models for AI accelerator design. Selected media engagements include patents filed with JIS College of Engineering on energy systems and contributions to studies on nonlinear science dynamics. His research emphasizes real-world applications, with projects addressing urban traffic control, renewable energy integration, and competitive market modeling in telecommunications. Collaboration networks span academia and industry, with active projects in India and the US focusing on sustainable energy, autonomous systems, and next-generation communication technologies.

• Operations Research
• Optimization
• Network Flows
• +۳ مورد دیگر

Prof. Horst W. Hamacher is a Professor in the Department of Optimization at the University of Kaiserslautern's Faculty of Mathematics. His research focuses on optimization, operations research, and their applications in logistics, healthcare, and disaster management. Key areas include network flow optimization, evacuation planning models, radiation therapy treatment design, and hub location problems. He leads the Optimization Group (AG Optimierung), developing algorithms for complex systems. His work integrates theoretical advancements with practical solutions, such as minimizing beam-on time in radiation therapy and optimizing urban evacuation routes. He has authored/co-authored over 100 journal papers and book chapters, including seminal contributions to facility location theory and dynamic network flows. Collaborations span academic and industrial partners, addressing challenges in public transportation, medical engineering, and sustainable urban planning. Notable projects include the 'OptionS' initiative for sustainable water management optimization and the 'FlowLoc' framework for evacuation dynamics. He actively contributes to interdisciplinary education, bridging mathematics with real-world applications like robotic assembly and infrastructure design.

Rebeka Čorićمشاهده پروفایل

مدرس

• Fitness Landscape Analysis
• Genetic Programming
• Genetic Algorithms
• +۵ مورد دیگر

Rebeka Čorić is a Lecturer at the School of Applied Mathematics and Informatics, Josip Juraj Strossmayer University of Osijek. She holds a PhD in Computing from the Faculty of Electrical Engineering and Computing, University of Zagreb (2021), an MSc in Mathematics from the University of Osijek (2014), and a BSc in Mathematics from the same institution (2011). Her research focuses on fitness landscape analysis, genetic programming, scheduling optimization, and container relocation problems. She actively contributes to projects like the Hyper-Heuristic Design for Container Relocation (Croatian Science Foundation, 2023-2027) and has co-authored over 10 peer-reviewed publications in journals like *Expert Systems with Applications* and *Journal of Language Modelling*. Her teaching includes courses on Heuristic Algorithms, Web Programming, Data Structures, and Deep Learning for Natural Language Processing. Her research has addressed diverse topics, including energy-efficient container relocation rules, Croatian verb stem analysis via neural networks, and pollen concentration prediction using RNN-based models like PollenNet. She has also explored hyperheuristic approaches to scheduling problems and fitness landscape analysis in genetic programming. Her work bridges theoretical advancements with practical applications in logistics, linguistics, and environmental science. Professionally, she has presented at international conferences (e.g., GECCO, MIPRO) and contributed to service activities like workshops at the Festival of Science and teaching at summer schools. Her current projects emphasize automated heuristic design and optimization techniques across multiple disciplines.

José Proençaمشاهده پروفایل

مدرس

• Component-based systems
• Distributed systems
• Software engineering
• +۳ مورد دیگر

José Proença is a Lecturer and Integrated PhD Researcher at CISTER Research Centre, ISEP, Portugal. He is currently a postdoc focusing on formal models for component-based systems. Previously, he worked at HASLab (University of Minho) and Distrinet (KU Leuven), collaborating with researchers like Luís Barbosa, Danny Hughes, and Dave Clarke. His expertise includes coordination of distributed components (Reo language), software product line engineering, and embedded systems (LooCI middleware and VirtuosoNext RTOS). Education: 5-year degree in Mathematics and Computer Science from University of Minho, with an Erasmus exchange at Bristol University, UK. PhD in Computer Science from Leiden University (2011), conducted at CWI, Amsterdam, in the Foundations of Software Engineering group. Research interests span formal methods, distributed systems, embedded systems, and software engineering. He has contributed to projects like IBEX (quantitative cyber-physical programming) and MARS (toolset for real-time systems). His work emphasizes practical applications of formal models in real-time and safety-critical systems. Publications focus on coordination models, multiparty session types, and formal verification, with contributions to journals like Science of Computer Programming and conferences such as COORDINATION and FMAS. He actively collaborates on tools like CAOS (Scala framework) and ARx (reactive programming for connectors).

• Multi-Agent Systems
• Human-Robot Interaction
• Game Theory
• +۷ مورد دیگر

Katia Sycara is a Research Professor at Carnegie Mellon University's Robotics Institute, part of the School of Computer Science. She also holds the Sixth Century Chair (part-time) in Computing Science at the University of Aberdeen, UK. Her research focuses on multi-agent systems, human-robot interaction, game theory, and adversarial reasoning. She leads the Advanced Agent-Robotics Technology Lab and has developed frameworks like the RETSINA multiagent infrastructure. Education: B.S. in Applied Mathematics (Brown University), M.S. Electrical Engineering (University of Wisconsin), Ph.D. Computer Science (Georgia Tech), Honorary Doctorate (University of the Aegean, 2004). Research interests include semantic web services, agent interoperability, crisis response systems, and negotiation support. She has pioneered work on the DAML-S language for semantic web services and contributed to the OASIS UDDI standard. Notable awards include the 2002 ACM SIGART Agents Research Award and AAAI Fellowship. She has led multimillion-dollar projects funded by DARPA, NASA, AFOSR, and ONR, focusing on applications like autonomous robotics, urban search and rescue, and enterprise integration. Awards: ACM SIGART Autonomous Agents Research Award (2002) AAAI Fellow (2002) IEEE Fellow (2013) Outstanding Alumnus (University of Wisconsin, 2005) Grants and Projects: Command and Control of Multi-Robot Teams (ONR) Games on Graphs (MURI/ONR) Urban Search and Rescue (NASA) Labs/Teams: Director of Advanced Agent-Robotics Technology Lab and contributor to the Semantic Web Science Association.

Luis Fernando PEREZ ARMASمشاهده پروفایل

پژوهشگر

• Operations Management
• Quantitative Methods
• Management Information Systems
• +۳ مورد دیگر

Luis Fernando PEREZ ARMAS is a Post Doctoral Researcher and holds a PhD in Economics from the University of Lille (2024). He is affiliated with IÉSEG School of Management in France, where he has served as a Teaching and Research Assistant since 2019. His academic background includes a Master in Business Administration (2019) and a Bachelor in Chemical Engineering (2012) from Universidad Simón Bolívar, Venezuela. He is a member of the LEM research unit. His research focuses on Operations Management, Quantitative Methods, and Management Information Systems. Notable contributions include applying quantum computing to discrete optimization problems and project scheduling, as well as leveraging machine learning (e.g., LSTM networks) for economic forecasting. His work bridges theoretical advancements in quantum algorithms with practical applications in operations research. In teaching, he instructs courses such as Python for Project Scheduling, Operations Management, Agile Project Management, and Financial Analytics across undergraduate, graduate, and postgraduate programs at IÉSEG. His professional experience includes a Project Manager role at Schlumberger (2012-2017), where he applied engineering and project management expertise. Recent publications explore quantum annealing for solving resource-constrained scheduling problems, limitations of existing quantum algorithms, and the predictive power of social media data in energy markets. While no scientific awards are explicitly mentioned, his interdisciplinary work reflects innovative contributions to operations research and quantum computing applications.

Nick Feamsterمشاهده پروفایل

استاد

• Network Performance
• Cybersecurity
• Internet Privacy
• +۶ مورد دیگر

Nick Feamster is the Neubauer Professor of Computer Science at the University of Chicago and Director of Research at the Data Science Institute. He previously held full professorships at Princeton University and Georgia Tech, directing the Center for Information Technology Policy and the School of Computer Science, respectively. His research focuses on network performance, security, privacy, and equitable internet access, with applications in AI-driven systems, human-computer interaction, and policy. Key roles include leading the Network Operations and Internet Security (NOISE) Lab and co-founding the Internet Equity Initiative. Feamster holds a Ph.D. and S.B./M.Eng. from MIT (Computer Science/Electrical Engineering). Notable recognitions include the ACM Fellowship, Presidential Early Career Award (PECASE), and multiple best-paper awards. His work bridges academia and policy, collaborating with entities like the FCC and City of Chicago. The NOISE Lab develops data-driven systems for network traffic analysis, addressing human behavior insights and security challenges. Recent projects include deploying Netrics for community internet testing and analyzing encrypted DNS protocols. Feamster’s research spans machine learning for network traffic analysis, censorship circumvention (e.g., Infranet), and software-defined networking (SDN). His lab emphasizes real-world impact through open-source tools like NetML and nPrint. Personal interests include marathon running, completing iconic races like Comrades Marathon in South Africa.

Keith Molenaarمشاهده پروفایل

استاد

• Construction Engineering and Management
• Alternative Project Delivery
• Project Cost and Risk Analysis
• +۳ مورد دیگر

Keith Molenaar is the Dean of the College of Engineering & Applied Science and the K. Stanton Lewis Professor of Construction Engineering and Management at the University of Colorado Boulder. He holds a PhD in Civil Engineering (1997), MS in Civil Engineering (1995), and BS in Architectural Engineering (1990), all from CU Boulder. His research focuses on construction engineering and management, particularly in alternative project delivery methods, cost engineering, and risk analysis. He has authored numerous publications on topics such as risk identification in transportation projects, green procurement, and lean construction methodologies. Professional Affiliations : American Society of Civil Engineers, Construction Management Association of America, Design-Build Institute of America. Awards : Fulbright Scholar (2006–2007), National Academy of Construction Membership (2017), and multiple industry recognitions for leadership and innovation. Grants : Secured federal and state funding for projects on risk management, project delivery systems, and transportation infrastructure. Molenaar’s work emphasizes bridging academic research and industry practice, with a focus on improving cost efficiency, risk mitigation, and sustainable infrastructure development.

Albert Wagelmansمشاهده پروفایل

استاد

• Operations Research
• Logistics & Information Systems
• Healthcare Logistics
• +۵ مورد دیگر

Albert Wagelmans is a Professor of Econometrics (Management Science) at the Department of Econometrics, Erasmus School of Economics (ESE), Erasmus University Rotterdam. He is affiliated with ERIM (Erasmus Research Institute of Management) and focuses on Logistics & Information Systems. His research emphasizes optimization methods for production, public transport, and healthcare planning, with notable contributions to supply chain coordination, inventory management, and healthcare logistics. He has held leadership roles, including Director of the Econometric Institute (2006–2014), Vice-President of EURO (2016–2020), and currently serves as President of the Dutch OR Society (NGB). Wagelmans co-founded the Erasmus Center for Optimization in Public Transport (ECOPT) and the Erasmus Center for Healthcare Logistics (EHCL), collaborating with organizations like NS Dutch Railways, Schiphol Group, and the Dutch Transplant Foundation (NTS). His research interests span optimization techniques applied to real-world problems, including healthcare logistics systems, public transport efficiency, and inventory management under uncertainty. Notable projects include the ESCH-R initiative for circular healthcare systems and mobile screening strategies for disease eradication. Wagelmans has advised over 15 PhD students and received awards for teaching excellence. His work has been published in top journals like Operations Research , Transportation Science , and Production and Operations Management .

Dimitrov Dimitarمشاهده پروفایل

دانشیار

• Renewable Energy Systems
• Power Engineering
• Optimization Algorithms
• +۴ مورد دیگر

Associate Professor Dimitrov Dimitar holds a position at the Faculty of Electrical Engineering and Information Technologies (FEIT) within the University of Ss. Cyril and Methodius, Skopje. His primary affiliation is with the Institute of Power Plants and Switchgear . He has been actively involved in academic roles since 1998, starting as an assistant lecturer at the former ETF (Electrotechnical Faculty). Education: PhD in Engineering (2009, FEIT, Skopje) MSc in Engineering (1997, ETF, Skopje) BSc in Engineering (1993, ETF, Skopje) Research interests span renewable energy systems , power engineering optimization , hybrid photovoltaic systems , and AI applications in medical diagnostics (noted in recent publications). His work often addresses grid integration challenges, energy scheduling algorithms, and distributed generation reliability. Recent publications (2020–2025) highlight advancements in: AI-driven medical imaging analysis for endometrial cancer Optimization of hybrid renewable energy systems Security-constrained hydrothermal scheduling No scientific awards are explicitly mentioned in the provided texts. He currently leads research in the Solar Energy Laboratory and contributes to the Multi-functional Platform for Renewable Energy Promotion project.

• Communications
• Networking
• Signal & Image Processing
• +۵ مورد دیگر

Mung Chiang is the Roscoe H. George Distinguished Professor of Electrical and Computer Engineering and President of Purdue University . He holds a PhD from Stanford University (2003) in Electrical Engineering, following earlier degrees from the same institution. His research focuses on optimizing networks and systems, including federated learning, edge computing, and 6G technologies. He leads projects on fog networking, smart data pricing, and social learning networks. Key research areas include network optimization , edge AI inference , and cooperative federated learning . Recent work addresses challenges in dynamic client management, hybrid terrestrial-satellite networks, and energy-efficient D2D systems. His publications emphasize practical solutions for heterogeneous environments and wireless network dynamics. Dr. Chiang has contributed to systems like Coded Edge Computing and Model Predictive Control (MPC) frameworks. He explores the interplay between connectivity and machine learning, with applications in autonomous vehicles and IoT. His work spans theoretical advancements and real-world implementations, including protocols for wireless system discovery and control. Current research trends include 6G innovations, resilient cyberphysical systems, and adaptive learning frameworks for dynamic networks.

Pooya Ronaghمشاهده پروفایل

عضو هیئت علمی

• Quantum Computation
• Quantum Algorithms
• Quantum Error Correction
• +۸ مورد دیگر

Pooya Ronagh is a Research Assistant Professor at the University of Waterloo, affiliated with the Department of Physics & Astronomy and the Institute for Quantum Computing (IQC). He also serves as a Scientific Lead at the Perimeter Institute Quantum Intelligence Lab (PIQuIL) and directs the Hardware Innovation Lab at 1QBit. His work bridges quantum computation, machine learning, and optimal control, focusing on quantum algorithms, error correction, and hybrid quantum-classical systems. Education: PhD in Mathematics (University of British Columbia, 2016), MSc in Mathematics (UBC, 2011), dual BSc in Mathematics and Computer Science (Sharif University of Technology, 2009). Awards include the Benjamin Franklin Fellowship (2009). Research Interests: Quantum algorithms for machine learning, reinforcement learning, fault-tolerant quantum architectures, cryogenic systems, and quantum control. He explores applications of quantum simulation to improve learning efficiency and robustness in AI systems. Recent work includes optimizing quantum error correction decoders, developing scalable superconducting architectures, and advancing neural network-based quantum state tomography. His contributions span theoretical frameworks (e.g., lattice surgery scheduling) and experimental methods (e.g., SFQ pulse control). Teaching: Courses like PHYS 490 (Machine Learning in Physics) emphasize practical coding and interdisciplinary projects. Grants and collaborations involve industry and academic partners in quantum hardware and software development. Labs: Hardware Innovation Lab (1QBit), IQC Quantum Control Group Future Work: Scaling quantum supercomputers, cryogenic neural decoders, quantum-enhanced generative AI