Find Academic Supervisors

Paul G DupuisView profile

Professor

• Probability Theory
• Stochastic Processes
• Control Theory
• +4 more

Paul G Dupuis is the IBM Professor of Applied Mathematics at Brown University. His research focuses on applications of probability theory, stochastic processes, control theory, and numerical methods. He holds affiliations with the American Mathematical Society, Society for Industrial and Applied Mathematics (SIAM), and the Institute for Mathematical Statistics (IMS). His work emphasizes large deviation theory, Markov chain approximations, Monte Carlo simulation, and partial differential equations. Education: Ph.D. in Applied Mathematics from Brown University (1985), M.S. from Northwestern University (1982), and B.S. from Brown University (1981). Research Interests: Control of deterministic and stochastic processes, differential games, numerical methods, operations research, and stochastic processes. His contributions include foundational work on large deviation theory, risk-sensitive control, and queueing networks. Awards: Elected SIAM Fellow (2010), Fellow of the Institute for Mathematical Statistics (2011), IBM Professor of Applied Mathematics (2012), and AMS Fellow (2014). Previously held an NSF Postdoctoral Fellowship (1985-1988). Grants: Current funding from the Army Research Office and National Science Foundation. Key collaborations include work on stochastic approximation, constrained diffusions, and reflected Brownian motion. Teaching: Courses include Operations Research: Probabilistic Models, Information Theory, and Advanced topics in Probability and Stochastic Control.

Mike KosekView profile

Research Fellow

• Transport Protocols
• Congestion Control
• Internet Architecture
• +3 more

Mike Kosek (Dr. rer. nat.) is a Research Fellow at the Chair of Connected Mobility (Department of Informatics) at the Technical University of Munich (TUM). His research focuses on transport protocols, congestion control, internet architecture, and internet measurements. Research Interests: Transport protocol design and analysis Congestion control mechanisms Internet architecture and measurement Network performance optimization DNS protocol behavior and privacy Applications in satellite and aerial communication Recent Research Trends: His publications emphasize QUIC protocol analysis, DNS over QUIC investigations, cross-layer protocol interactions, and satellite communication adaptations. Key methodologies include real-world measurements, protocol design extensions, and dataset creation for reproducibility. Contact: E-mail: kosek@in.tum.de Phone: +49 89 289-18665 Office: 01.05.038, Boltzmannstr. 3, 85748 Garching

• Big Data
• Business Analytics
• Healthcare Analytics
• +4 more

Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.

David Alan GoldbergView profile

Associate Professor

• Applied Probability
• Operations Research
• Stochastic Processes
• +7 more

David Alan Goldberg is an Associate Professor in the School of Operations Research and Information Engineering (ORIE) at Cornell University, part of Cornell Engineering. He joined Cornell in 2017 and previously held the A. Russel Chandler III Associate Professorship at Georgia Tech’s Industrial and Systems Engineering department. Goldberg earned his Ph.D. in Operations Research from MIT (2011) and a B.S. in Computer Science from Columbia University (2006). Education: B.S. in Computer Science, Columbia University (2006) Ph.D. in Operations Research, MIT (2011) Research Interests: Goldberg’s work focuses on applied probability and stochastic processes, including optimal stopping, inventory and queueing models, combinatorial optimization, and robust optimization. He develops algorithms and insights for complex systems, addressing challenges like the curse of dimensionality. His research spans applications in data science, operations research, and stochastic modeling. Notable contributions include distributionally robust inventory control and high-dimensional decision-making frameworks. Awards and Honors: 2025 Community-Engaged Practice and Innovation Award (David M. Einhorn Center) 2023 Sunny Yau ’72 Teaching Award (Cornell) 2019 INFORMS Applied Probability Society Best Publication Award 2015 NSF CAREER Award Multiple INFORMS Nicholson Student Paper Competitions (First Place, 2019 & 2015) Teaching and Service: Goldberg leads Cornell ORIE’s undergraduate research program, connecting students to real-world applications of OR and data science. He teaches courses in probability modeling, stochastic models, and academic skills for PhD students. He chairs the INFORMS Applied Probability Society and serves on editorial boards for Operations Research and Stochastic Systems . At Cornell, he advises the Undergraduate ORIE Society and directs undergraduate studies in ORIE. Labs & Collaborations: Goldberg’s research integrates theoretical rigor with practical applications, often involving collaborations across disciplines. His work bridges operations research, statistics, and computer science to address modern challenges in inventory systems, queueing networks, and decision-making under uncertainty.

Gayane VardoyanView profile

Assistant Professor

• Quantum Networking
• Entanglement Distribution
• Quantum Information Systems
• +3 more

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.

Krishna JagannathanView profile

Professor

• Stochastic modeling
• Communication networks
• Information theory
• +3 more

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.

Zhe LiuView profile

Assistant Professor

• Revenue Management
• Supply Chain Management
• Sharing Economy Platforms
• +3 more

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 RazaviView profile

Associate Professor

• Smart Infrastructure
• Intelligent Transportation Systems
• Construction Management Automation
• +5 more

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 ArmonyView profile

Professor

• Operations Management
• Stochastic Modeling
• Service Operations
• +7 more

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.

Vincent Y. F. TanView profile

Professor

• Online Decision Making
• Multi-Armed Bandits
• Reinforcement Learning
• +3 more

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.

Baris AtaView profile

Professor

• Operations Management
• Applied AI
• Dynamic Decision Making Under Uncertainty
• +4 more

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.

• Pricing and Distribution Systems
• Integrated Risk Management
• Game Theoretic Models
• +3 more

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 MieghemView profile

Academic

• Operations Management
• Supply Chain Operations
• Operations Strategy
• +11 more

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.

• Network Tomography
• Software-Defined Networking
• Cyber-physical Systems
• +6 more

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

Per EnqvistView profile

Associate Professor

• Optimization
• Operations Research
• Systems Engineering
• +6 more

Per Enqvist is an Associate Professor in the Division of Numerical Analysis, Optimization and Systems Theory within the Department of Mathematics at KTH Royal Institute of Technology, Stockholm, Sweden. He has held this position since 2009 after progressing from Assistant Professor (2006-2009) and post-doctoral roles at INRIA France and CNR Italy. His academic background includes: Ph.D. in Optimization and Systems Theory from KTH (2001), supervised by Professor Anders Lindquist M.Sc. in Engineering Physics (Civilingenjör) from KTH (1994) with Applied Mathematics focus Post-doctoral studies at INRIA Sophia-Antipolis (2003-2004) and CNR Padova (2001-2003) Enqvist's research centers on mathematical modeling of stochastic processes, scheduling, and queueing theory with applications across operations research, systems engineering, and signal processing. His principal interests span Optimization, Operations Research, Systems Engineering, Signal Processing, Mathematical Systems Theory, and Modeling and Simulation. He has made significant contributions to spectral estimation, covariance interpolation, and resource allocation frameworks. Publication analysis reveals an evolution from foundational systems theory work (2000s) on spectral estimation and minimal realization toward applied optimization in healthcare operations (2010s-2020s). Recent articles address radiation therapy scheduling and contact center modeling using queueing theory with risk-sensitive measures like CVaR, while earlier work established theoretical frameworks for covariance interpolation and passive system synthesis. No scientific awards are documented in the provided information. He has received funding from Vetenskapsrådet (Swedish Research Council) and led the ACCESS seed project on "Robust Spectral Estimation". Enqvist is course responsible for multiple master's program tracks including Aerospace systems and Industrial Engineering, and oversees the Optimization and Systems Theory seminar series. No student advisement details are provided. He maintains affiliations with the ACCESS Linnaeus centre, Center for Industrial and Applied Mathematics (CIAM), and serves on the Swedish Operations Research Society (SOAF) board.