جست‌وجوی استاد و پژوهشگر

Gayane Vardoyanمشاهده پروفایل

استادیار

• Quantum Networking
• Entanglement Distribution
• Quantum Information Systems
• +۳ مورد دیگر

Gayane Vardoyan is an Assistant Professor at the Manning College of Information and Computer Sciences, University of Massachusetts Amherst. She previously held a permanent Assistant Professor position at QuTech (Quantum Internet Division) and the Faculty of Electrical Engineering, Mathematics, and Computer Science at TU Delft (2022–2024). Her research focuses on quantum networking, particularly developing protocols for entanglement distribution and optimizing quantum systems. Vardoyan earned her B.S. in Electrical Engineering and Computer Sciences from UC Berkeley and her Ph.D. from UMass Amherst under Prof. Don Towsley. She has held postdoctoral and research roles at TU Delft, Inria, and Argonne National Lab. Education: Ph.D., University of Massachusetts Amherst (2017–2021) M.S., University of Massachusetts Amherst (2017) B.S., University of California, Berkeley (2013) Research Interests: Vardoyan’s work addresses challenges in distributed quantum systems, including entanglement distribution algorithms, quantum repeater architectures, and performance analysis of quantum networks. She integrates classical networking techniques with quantum principles to enhance protocol efficiency. Current projects emphasize utility maximization, resource allocation, and optimizing quantum network performance under hardware constraints. Awards: Best Paper Award, Performance 2021 Best-In-Session Presentation Award, INFOCOM 2018 Advising & Grants: Supervises PhD and Master’s students on quantum network design and optimization. Collaborates with industry and academic partners on projects funded by NSF and EU grants. Previously led initiatives at QuTech and co-organized events like the Quantum Software Consortium General Assembly. Labs & Teams: Leads the Distributed Quantum Systems group at UMass, focusing on theoretical and applied research in quantum networking. Engages in cross-disciplinary collaborations with computer science and electrical engineering teams.

Yuanzhu Chenمشاهده پروفایل

استاد

• Computer Networking
• Mobile Computing
• Complex Networks
• +۵ مورد دیگر

Yuanzhu Chen is a Professor in the School of Computing at Queen’s University, affiliated with the Faculty of Arts and Science. He previously served as Professor and Department Head at Memorial University of Newfoundland (2005–2021). His research focuses on computer networking, mobile computing, complex networks, and applied machine learning, emphasizing wireless innovation beyond traditional wired systems. He holds a PhD from Simon Fraser University (2004) and a B.Sc. from Peking University (1999). Education: PhD in Computing Science (Simon Fraser University, 2004); B.Sc. in Computer Science (Peking University, 1999). Earlier roles include Post-doctoral Researcher at Simon Fraser University (2004–2005) and leadership positions at Memorial University, including Department Head (2019–2021). Research Interests: Network Coding and Opportunistic Routing Mobile and Wireless Network Protocols Complex Network Analysis Machine Learning Applications Indoor Positioning Systems Social Network Dynamics Selected Awards: Recipient of Queen’s University President's Award for Distinguished Teaching. Lab Affiliation: Director of the Wireless Networking and Mobile Computing Lab (WineMocol). Active in collaborative projects involving smartphone sensors, community-based environmental monitoring, and stock market prediction using web data.

Krishna Jagannathanمشاهده پروفایل

استاد

• Stochastic modeling
• Communication networks
• Information theory
• +۳ مورد دیگر

Krishna Jagannathan is a full-time Professor in the Department of Electrical Engineering at the Indian Institute of Technology Madras (IIT Madras), India. He specializes in stochastic modeling, communication networks, information theory, and queuing theory. He obtained his B.Tech from IIT Madras in 2004, followed by S.M. and Ph.D. degrees from MIT in 2006 and 2010, respectively. After post-doctoral positions at Caltech and MIT, he joined IIT Madras in 2011. Education: B.Tech in Electrical Engineering, IIT Madras (2004) S.M. in Electrical Engineering and Computer Science, MIT (2006) Ph.D. in Electrical Engineering and Computer Science, MIT (2010) Research Interests: His research focuses on stochastic modeling and analysis of communication networks , information theory , and queuing theory . He has made significant contributions to understanding network performance, resource allocation, and risk-aware decision-making in complex systems. He leads the Networks and Stochastic Systems lab at IIT Madras, mentoring a large cohort of Ph.D. and M.S. students working on cutting-edge problems in networking, optimization, and stochastic systems. Scientific Awards: Best Paper Award at WiOpt 2013, Tsukuba, Japan Young Faculty Recognition Award for Excellence in Teaching and Research, IIT Madras (2014) Teaching & Mentorship: He has taught a wide range of courses including Probability Foundations , Stochastic Modeling and Queuing Theory , Convex Optimization , and Signals & Systems , consistently receiving high teaching evaluations. He has supervised over 15 Ph.D. and M.S. students to completion and continues to guide several active researchers.

• Network Tomography
• Software-Defined Networking
• Cyber-physical Systems
• +۶ مورد دیگر

Ting He is a Professor in the Department of Computer Science and Engineering, specializing in interdisciplinary research at the intersection of network sciences, energy systems, and cybersecurity. Their work addresses critical challenges in network tomography, software-defined networking, and cyber-physical systems, with a strong emphasis on advancing edge computing and decentralized learning paradigms. NSF-funded research on Distributed Edge Intelligence (2024–2025) Collaborative projects on Overlay Networks and Adversarial Reconnaissance in SDN Recent publications analyze network topology inference, energy-efficient decentralized learning, and secure cloud file systems. Their research aligns with UN SDGs through contributions to sustainable energy systems and secure IT infrastructure. Key collaborations with Silvestri, La Porta, and Chaudhuri Active in Smart Grid resilience and cascading failure mitigation

Zhe Liuمشاهده پروفایل

استادیار

• Revenue Management
• Supply Chain Management
• Sharing Economy Platforms
• +۳ مورد دیگر

Zhe Liu is an Assistant Professor in the Analytics & Operations group at Imperial College Business School, where he also serves as PhD Director. He holds a PhD in Operations Management from Columbia Business School and a BS in Industrial Engineering from Tsinghua University. His research focuses on revenue management and supply chain optimization, with specialized interests in sharing economy platforms and multi-sourcing strategies. Liu's work examines operational challenges in modern business environments through mathematical modeling, including queueing systems, pricing optimization, and risk management in volatile supply chains. His publications demonstrate consistent themes in platform operations, stochastic optimization, and behavioral interactions within multi-agent systems. Recognized with numerous honors, Liu received the 1st Place Service Science Best Cluster Paper Award (2024), 2nd Place CSAMSE Best Paper Award (2024), and was a finalist in the George Nicholson Student Paper Competition. He actively mentors PhD students and serves as judge for international paper competitions and conference program committees.

Saiedeh Razaviمشاهده پروفایل

دانشیار

• Smart Infrastructure
• Intelligent Transportation Systems
• Construction Management Automation
• +۵ مورد دیگر

Dr. Saiedeh Razavi is an Associate Professor and the inaugural Chair in Heavy Construction at McMaster University's Department of Civil Engineering, directing the McMaster Institute for Transportation and Logistics (MITL). She holds a multidisciplinary background with degrees in Computer Engineering (B.Sc., Sharif University), Artificial Intelligence (M.Sc., Iran), and Civil Engineering (Ph.D., Waterloo). Her research focuses on smart infrastructure, connected mobility, and construction safety, funded by NSERC and the Ontario Ministry of Transportation. Key areas include transforming construction management through AI, autonomous vehicles, and smart work zones. Education: B.Sc. (Sharif), M.Sc. (Iran), Ph.D. (Waterloo) Research Interests: Smart cities, connected vehicle systems, data fusion, risk analysis, and sustainable logistics Leadership Roles: Director of MITL, Associate Chair (Research), and lead of national/international multidisciplinary projects Her work bridges academia, government, and industry to enhance mobility and safety. Notable grants include NSERC funding for transformative transportation systems. Awards include teaching excellence and innovation in team-based projects. Grants & Projects: NSERC, Ontario Ministry of Transportation, and industry collaborations Labs/Teams: MITL, CPS-based construction safety initiatives, and autonomous vehicle research groups

Mor Armonyمشاهده پروفایل

استاد

• Operations Management
• Stochastic Modeling
• Service Operations
• +۷ مورد دیگر

Mor Armony is the Vice Dean for Faculty and Research, Harvey Golub Professor of Business Leadership, and Professor of Technology, Operations & Statistics at the Leonard N. Stern School of Business, New York University. She has been a key faculty member since 1999 and is a leading researcher in stochastic modeling and service operations. Ph.D. in Operations Research, Stanford University (1999) M.S. in Operations Research, Stanford University (1997) M.S. in Statistics, Hebrew University of Jerusalem (1996) B.S. in Mathematics and Statistics, Hebrew University of Jerusalem (1993) Her research focuses on large-scale service systems, particularly in healthcare and contact centers. She investigates patient flow in hospitals, optimization of customer experience, and control of stochastic processing systems using advanced queueing models and operations research techniques. Her work bridges theoretical rigor with practical applications in service operations management. The recent articles reflect a strong trend toward integrating behavioral aspects into operations models, such as customer impatience, strategic patient behavior, and the impact of online reviews on physician demand. Her research spans healthcare operations, call center optimization, and dynamic routing in heterogeneous systems, consistently published in top journals like Management Science , Operations Research , and Production and Operations Management . Scientific recognition includes being named the Harvey Golub Professor of Business Leadership, a distinguished title at NYU Stern. Harvey Golub Professor of Business Leadership She actively advises research projects and collaborates with scholars on topics including staffing, routing, and capacity management. Her work has been supported by ongoing academic engagement and publication, with recent projects addressing appointment scheduling with no-shows, strategic capacity withholding, and co-sourcing in call centers. She leads research in data-driven queueing science applied to hospital operations and is involved in empirical studies on digital health platforms. Her research group, the Operations Management Group at Stern, focuses on developing analytical models for complex service systems. She contributes to interdisciplinary efforts in healthcare operations and collaborates with medical researchers on improving critical care delivery and outpatient scheduling.

Baris Ataمشاهده پروفایل

استاد

• Operations Management
• Applied AI
• Dynamic Decision Making Under Uncertainty
• +۴ مورد دیگر

Baris Ata is the Sigmund E. Edelstone Distinguished Service Professor of Operations Management at the University of Chicago Booth School of Business. His work bridges theoretical operations management with practical applications, focusing on dynamic decision-making under uncertainty. Research Interests Ata’s research spans stochastic networks, manufacturing/service operations, healthcare delivery, and social sector innovation. Recent projects address high-dimensional stochastic control, xenotransplantation candidate selection, criminal justice logistics, and last-mile delivery challenges in Africa. Scientific Awards Best Paper in Service Science Award, INFORMS (2009) William Pierskalla Best Paper Award, INFORMS (2015) Wickham Skinner Best Paper Award, POMS (2019) Manufacturing and Service Operations Management Young Scholar Prize, INFORMS (2015) Emory Williams MBA Teaching Award (2021) Recent Publications Ata’s recent work includes topics in dynamic pricing, stochastic control, and healthcare logistics. His papers examine congestion-based pricing strategies, equilibrium analysis in queues, and policy design for organ transplantation. Broad disciplines include operations management, stochastic modeling, and healthcare analytics.

Vincent Y. F. Tanمشاهده پروفایل

استاد

• Online Decision Making
• Multi-Armed Bandits
• Reinforcement Learning
• +۳ مورد دیگر

Professor Vincent Y. F. Tan holds dual appointments in the Department of Mathematics and the Department of Electrical and Computer Engineering (ECE) at the National University of Singapore (NUS). He is also affiliated with the Institute of Operations Research and Analytics (IORA) and the Institute of Data Science (IDS). His research focuses on Online Decision Making, Multi-Armed Bandits, Reinforcement Learning, Information Theory, and Statistical Signal Processing. Notably, he has been actively publishing in top-tier conferences like NeurIPS, ICML, and IEEE journals, with recent works exploring topics such as low-rank adaptation, off-policy evaluation, and queueing control. Professor Tan has advised numerous PhD students, including Fengzhuo Zhang, Yujun Shi, and Junwen Yang. He has received recognition for his teaching, including a 4.7/5.0 rating for EE5137 Stochastic Processes. His work has led to impactful publications, such as the best paper award at the ICML 2025 workshop on World Models and an oral presentation at ICLR 2025. He currently serves as a Senior Area Chair for NeurIPS 2025 and an Area Editor for the IEEE Transactions on Information Theory. His research group focuses on advancing theoretical and applied aspects of machine learning, with projects funded by grants in areas like distributed optimization and adversarial robustness. He collaborates widely, including with institutions like IIT Delhi and HKUST Guangzhou. Open positions are available for motivated postdocs and students in his research areas.

Lev Levitinمشاهده پروفایل

استاد

• Information Theory
• Computer Networks
• Quantum Information
• +۳ مورد دیگر

Lev Levitin is a Distinguished Professor in the Department of Electrical & Computer Engineering and Division of Systems Engineering at Boston University, with office PHO 332 and contact email levitin@bu.edu. His primary academic focus spans information theory, quantum communication, and computer network architecture. Education: PhD, USSR Academy of Sciences, Gorky University, 1969 Levitin's research integrates fundamental physics with information systems, emphasizing quantum measurement theory, bioinformatics, and the physical limits of computation. His work explores critical phenomena in network dynamics, virtual cut-through routing algorithms, and thermodynamic constraints in information processing. This interdisciplinary approach bridges theoretical physics, computer engineering, and complex systems analysis to address foundational questions in reliable computing. Analysis of his 15 most recent publications reveals two dominant research threads: (1) rigorous modeling of interconnection networks with emphasis on latency, saturation, and phase transitions in multidimensional topologies, and (2) quantum information theory investigations into physical limits of communication, energy requirements, and measurement constraints. The network studies consistently employ virtual cut-through routing as a core methodology, while quantum works establish fundamental bounds on information retrieval and computational speed. Scientific Awards: Life Fellow, IEEE Member, International Academy of Informatization Levitin leads the Reliable Computing Laboratory at Boston University, teaching foundational and advanced courses including Introduction to Engineering, Logic Design, Probability Theory, and specialized graduate courses in Information Theory and Discrete Mathematics. His educational contributions span undergraduate instruction through doctoral supervision, though specific student names and current grant funding details are not documented in the provided materials.

• Pricing and Distribution Systems
• Integrated Risk Management
• Game Theoretic Models
• +۳ مورد دیگر

WEE Kwan Eng is a Senior Lecturer of Operations Management at the Lee Kong Chian School of Business, Singapore Management University (SMU), since 2012. He holds a Ph.D. in Operations Management from Purdue University (2000), an M.S. in Management from NUS (1995), and a B.S. in Mathematics (with Honors) from NUS (1993). His research focuses on pricing strategies, supply chain risk management, game-theoretic models, and queuing systems. He has received multiple teaching honors, including the Dean’s Teaching Honor List (2005–2011). His work spans theoretical and applied operations research, with notable contributions to inventory coordination in retail networks, newsvendor model extensions, and queuing-based manufacturing systems. He has published in top journals like Operations Research Letters and IIE Transactions. Awards: Frederick N. Andrews Fellowship (1995-1997), Dissertation Fellowship (1998-1999) Research Themes: Strategic inventory policies, supply chain coordination, and optimization under uncertainty

Jan A. Van Mieghemمشاهده پروفایل

عضو هیئت علمی

• Operations Management
• Supply Chain Operations
• Operations Strategy
• +۱۱ مورد دیگر

Jan A. Van Mieghem is the A. C. Buehler Professor and Professor of Operations at the Kellogg School of Management, Northwestern University. He also serves as a Professor by Courtesy at the McCormick School of Engineering and Applied Science. His research spans product, service, and supply chain operations, combining strategic and tactical perspectives with mathematical modeling, stochastic analysis, and empirical verification. Ph.D. in Business, Graduate School of Business, Stanford University (1995) MS in Electrical Engineering, Stanford University (1990) MS in Applied Sciences, KU Leuven, Belgium (1989) His research interests focus on operations strategy, supply chain optimization, and digital operations. He explores topics such as operational hedging, capacity investment, network flexibility, and the application of AI in inventory management. His work addresses healthcare operations, dual sourcing, and the interplay between collaboration and productivity in service networks. Recent research trends center on AI-driven inventory systems, dual sourcing under uncertainty, and healthcare resource allocation. He has authored over 60 academic articles and two textbooks: Operations Strategy: Principles and Practice and Managing Business Process Flows: Principles of Operations Management . 2023: First place in POMS College of Supply Chain Management Student Paper Competition 2020: Flexibility Excellence Award 2014: Wickham Skinner Award 2007: First MSOM Best Paper Award Van Mieghem has held leadership roles at Kellogg, including Deputy Dean (2023–present), Faculty Director of the Executive MBA program (2012–2017), and Chairman of the Department of Managerial Economics and Decision Sciences (2006–2009). He advises firms on operations strategy and management and has served on editorial boards of Management Science , Manufacturing & Service Operations Management , and Operations Research . He has mentored numerous Ph.D. students, including Audrey Bazerghi, Simrita Singh, Yangzi Jiang, and Dennis J. Zhang, who have secured academic and industry positions. His teaching spans operations management and strategy across MBA, Ph.D., and executive programs. Van Mieghem's work examines the intersection of operations strategy and execution, emphasizing financial value as a guiding metric. His empirical studies leverage real-world data from healthcare, manufacturing, and e-commerce to validate theoretical models and develop practical frameworks.

Jean Walrandمشاهده پروفایل

استاد

• Communication Networks
• Network Congestion Control
• Game Theory
• +۵ مورد دیگر

Jean Walrand is a Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. His research focuses on communication networks, performance evaluation, game theory, and stochastic networks. He has authored several influential books, including Communication Networks: A Concise Introduction and Probability in Electrical Engineering and Computer Science , and holds numerous patents in network resource management. Ph.D. in EECS from UC Berkeley IEEE Fellow and recipient of the Stephen O. Rice Prize INFORMS Lanchester Prize for operations research contributions His research interests span communication networks, queueing theory, congestion control, wireless network scheduling, and economic models for network resource allocation. Walrand's work has significantly impacted network design and optimization, particularly in distributed algorithms and game-theoretic approaches. His recent publications emphasize network architecture, delay variability reduction, and distributed optimization algorithms. Walrand has mentored over 20 Ph.D. students, including notable contributors to wireless networks and network economics. IEEE Koji Kobayashi Award (2012) ACM Sigmetrics Achievement Award (2013) INFORMS Lanchester Prize for Communication Networks book As advisor to students like Libin Jiang and Hoi-Sheung Wilson So, Walrand has shaped research in wireless MAC protocols, bandwidth trading, and network security. His technical reports and patents address practical challenges in switch fabric design, bandwidth allocation, and power management.

Gustavo Vulcanoمشاهده پروفایل

استاد مدعو

• Revenue Management
• Pricing Analytics
• Retail Operations
• +۶ مورد دیگر

Gustavo Vulcano is an Adjunct Professor in the Department of Information, Operations and Management Sciences at the Leonard N. Stern School of Business, New York University, where he has been affiliated since 2002. He served as Assistant Professor (2002–2010), Associate Professor (2010–2017, tenured in 2012), and has held an adjunct role since 2017. His academic work bridges theoretical and applied operations management with strong industry engagement. Education: Ph.D. in Operations Management, Columbia University, 2003 M.Phil. in Operations Management, Columbia University, 2000 M.S. in Computer Science, University of Buenos Aires, 1997 B.S. in Computer Science, University of Buenos Aires, 1994 His research focuses on revenue and pricing analytics , retail operations , and supply chain management , particularly emphasizing customer choice modeling , data-driven optimization , and computational methods in network revenue management . He integrates stochastic modeling and behavioral insights to develop practical pricing and operational strategies. His work is deeply rooted in real-world applications across airlines, retail, and financial services. The analysis of his publications reveals a consistent trend in leveraging data-driven decision-making under uncertainty, with a focus on dynamic pricing, demand learning, and robust optimization. His articles span premier journals such as Operations Research and Management Science , reflecting a strong theoretical foundation combined with empirical and computational rigor. Key thematic areas include customer behavior modeling, network revenue management, and stochastic optimization for service industries. Scientific Awards and Leadership: Chair, INFORMS Revenue Management and Pricing Section (2016–2017) Associate Editor, Operations Research and Management Science Prof. Vulcano has advised numerous PhD and master’s students and has secured research grants through industry collaborations. His consulting projects with Delta Airlines, Sabre Holdings, Aerolíneas Argentinas, and ICBC demonstrate a strong commitment to translating academic research into practical solutions. He has taught core courses such as Operations Management , Pricing and Revenue Management , and Dynamic Programming across undergraduate, MBA, PhD, and MSBA programs, shaping future leaders in data-driven decision-making. He is actively involved in research labs and teams focused on operations analytics and pricing strategy , often collaborating with interdisciplinary groups at NYU Stern and industry partners. His ongoing editorial roles and consultancy reflect sustained engagement in advancing the field of revenue management and operations science.

Navid Izadyمشاهده پروفایل

مدرس ارشد

• Operations Research
• Healthcare Management
• Stochastic Modelling
• +۳ مورد دیگر

Dr. Navid Izady is a Reader in Operations & Supply Chain at Bayes Business School, part of City St George's, University of London. His academic career includes a PhD from Lancaster University Management School (2010), and prior roles at the University of Southampton. He specializes in stochastic modelling for healthcare and manufacturing operations, collaborating with hospitals and healthcare organizations on sponsored research and consultancy projects. Dr. Izady holds qualifications in Industrial Engineering from Sharif University of Technology (BSc and MSc) and a PhD in Management Science. He teaches operations management, stochastic modelling, healthcare modelling, and decision analysis across BSc, MSc, and MBA programs. His research focuses on optimizing healthcare logistics, patient flow management, and resource allocation in hospitals. He has developed frameworks for managing pandemic and non-pandemic demand, reconfiguring inpatient services, and optimizing staffing and patient admission/discharge processes. His work bridges theoretical stochastic models with practical healthcare challenges, emphasizing operational efficiency and resilience. Notable contributions include studies on inpatient bed pressure reduction, sample pooling techniques for pandemic testing, and queueing theory applications in emergency departments and specialty clinics. His publications highlight innovations in healthcare operations management and simulation methods. Dr. Izady's expertise includes operations research, simulation, statistics, and stochastic processes. He supports industry partnerships and has supervised numerous research students, contributing to both academic and applied knowledge in healthcare and manufacturing systems.