جست‌وجوی استاد و پژوهشگر

Abhijit Gosaviمشاهده پروفایل

دانشیار

• Operations Research
• Machine Learning
• Supply Chain Management
• +۴ مورد دیگر

Abhijit Gosavi is an Associate Professor in the Department of Engineering Management & Systems Engineering at Missouri University of Science and Technology. His research focuses on simulation-based optimization, Markov Decision Processes, and reinforcement learning, with applications in disaster response, maintenance scheduling, and supply chain management. He has been funded by the National Science Foundation (NSF), Department of Defense, and industry partners. Dr. Gosavi teaches courses on discrete-event simulation, MDPs, product management, and facilities design. Education: Ph.D. in Industrial Engineering from University of South Florida (1999), M.Tech in Mechanical Engineering from Indian Institute of Technology Madras (1995), and B.E. in Mechanical Engineering from Jadavpur University (1992). His research interests span machine learning, data analytics, and systems engineering. Key research contributions include developing simulation-based models for post-earthquake response strategies, digital twins for production line maintenance, and reinforcement learning algorithms for inventory control. His work has been published in journals like Natural Hazards Review , Annals of Operations Research , and International Journal of Production Economics . Funding highlights include an NSF grant for reducing pollution through AI-driven maintenance strategies. He collaborates with researchers in disaster management, cyber-physical systems, and healthcare policy analysis. Labs/Teams: Investigator at the Intelligent Systems Center, focusing on advanced computational methods for systems engineering and optimization.

Karsten Kruseمشاهده پروفایل

مدرس

• Functional Analysis
• Operator Semigroups
• Abstract Cauchy Problems
• +۱۱ مورد دیگر

Karsten Kruse is a Lecturer in the Department of Applied Mathematics at the University of Twente, affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) and the Mathematical Systems Theory (MAST) group. Previously, he was a postdoctoral researcher and teaching assistant at Hamburg University of Technology and held an adjunct lecturer position at Hamburg University of Applied Sciences. PhD in Mathematics, University of Oldenburg (2014) Diploma in Mathematics, University of Oldenburg (2010) German Abitur, Graf-Anton-Günther-Schule (1997) His research centers on Functional Analysis, with focus on operator semigroups, abstract Cauchy problems, locally convex spaces, and vector-valued functions. He also investigates hyperfunctions, the \(\overline{\partial}\)-operator, and Laplace transforms. Complementing his theoretical work, Kruse is deeply engaged in e-learning and e-assessment, particularly through his innovative Surviving Math project, which uses gamification and storytelling to enhance problem-solving skills in engineering students. His teaching spans linear algebra, calculus, analysis, and topology across multiple institutions. His recent publications (2022–2025) consistently explore advanced topics in functional analysis, especially bi-continuous semigroups, preduals, and vector-valued function spaces, demonstrating a cohesive and evolving research program. Several papers involve interdisciplinary applications in queueing networks and robotic logistics. He frequently collaborates with mathematicians such as Felix L. Schwenninger and Christian Seifert. Scientific Awards Award for an outstanding Diploma thesis, University of Oldenburg Award for the best tutorial (Faculty V), University of Oldenburg (2012–2013 and 2013) 2nd place, MINTchallenge by Stifterverband Kruse has supervised multiple bachelor’s and master’s theses and coordinated international research workshops such as ISEM and DETN. He has been involved in several research projects, including those on bi-continuous semigroups and robotic mobile fulfilment systems, supported by institutions like the Simons Foundation. His teaching innovation project Surviving Math has been recognized and further developed at the University of Twente. He is actively involved in academic service, including organizing conference sessions such as at IWOTA 2025, and contributes to the mathematical community through arXiv, ORCID, and zbMath. He maintains a strong publication record and is engaged in both theoretical and applied mathematical research.

Indika Anuradha Mendis Balapuwadugeمشاهده پروفایل

پژوهشگر

• Cognitive Radio Networks
• Wireless Communication
• Dynamic Spectrum Allocation
• +۷ مورد دیگر

Indika Anuradha Mendis Balapuwaduge is a Researcher at the Department of Information and Communication Technology , University of Agder , Norway. He previously served as a Senior Lecturer at the University of Ruhuna (2020-2022) and held postdoctoral and PhD positions at the University of Agder (2017-2020 and 2012-2016). Education PhD in ICT (University of Agder, 2016) MSc in ICT (University of Agder, 2012) BSc in Electrical and Information Engineering (University of Ruhuna, 2008) Research Interests : Focus on Wireless Communication with expertise in Cognitive Radio Networks , Ultra-Reliable Communication , and Applied Machine Learning . His work integrates Dependability Theory and Stochastic Process Modeling to address challenges in 5G/6G Networks , IoT , and Network Slicing . Recent Publications include studies on Electric Vehicle Charging Optimization , Secure IoT Protocols , and 5G Network Slicing . He has contributed to IEEE Transactions and Springer publications, emphasizing Dynamic Spectrum Allocation and Machine Learning Applications .

Samuli Aaltoمشاهده پروفایل

استاد مهمان

• Communication Engineering
• Queueing Theory
• Energy-Aware Systems
• +۲ مورد دیگر

Samuli Aalto is a Visiting Professor at the Department of Information and Communications Engineering, Aalto University School of Electrical Engineering. His research focuses on Communication Engineering , particularly in Queueing Theory , Stochastic Scheduling , and Energy-Aware Systems . He has contributed extensively to optimizing resource allocation in wireless networks and server farms. Academic Affiliation : Aalto University, School of Electrical Engineering Research Themes : Optimal scheduling in queueing systems, energy-efficient network management, and stochastic resource allocation Recent Publications highlight work in: Whittle index applications for multi-class queueing systems Energy-aware dispatching in heterogeneous networks Slowdown minimization in single-server queues Age-energy tradeoff models for wireless systems His research involves mathematical modeling of Markovian systems , processor sharing , and size-based scheduling . Projects include optimizing P2P video-on-demand systems, analyzing queue-specific job sizes , and developing energy-performance tradeoff frameworks for modern data centers and 5G networks.

Assaf Zeeviمشاهده پروفایل

استاد

• Operations Research
• Statistics
• Machine Learning
• +۹ مورد دیگر

Assaf Zeevi is the Kravis Professor of Business at Columbia University's Graduate School of Business (GSB), specializing in Decision, Risk, and Operations. He holds leadership roles, including former Vice Dean at Columbia Business School and Editor-in-Chief of Stochastic Systems . His research focuses on Operations Research, Statistics, and Machine Learning, with applications in dynamic pricing, healthcare analytics, and recommendation systems. Education: B.Sc. and M.Sc. (Cum Laude), Technion, Israel Ph.D., Stanford University Research Interests: Dr. Zeevi develops theory and algorithms for reinforcement learning, bandit problems, stochastic optimization, and statistical learning. His work bridges theoretical foundations with practical applications in online platforms, healthcare, and revenue management. Awards: 2019 Lanchester Prize NSF CAREER Award IBM Faculty Award Google Research Award Advising & Grants: He has mentored over 14 doctoral students, many now leading academics and industry professionals. His grant-funded research includes projects on secondary spectrum markets, differentiated services design, and stochastic modeling. Funders include NSF, IBM, Google, and the Binational Science Foundation. Labs & Teams: Collaborates across academia and industry, serving on editorial boards (e.g., Operations Research ) and scientific advisory boards for tech startups. Active in INFORMS prize committees and global innovation initiatives.

• Operations Research
• Operations Management
• Dynamic Resource Allocation
• +۷ مورد دیگر

Yehua Wei is an Associate Professor in the Decision Sciences area at Duke University's Fuqua School of Business. He holds a Ph.D. in Operations Research from MIT and an undergraduate degree in Combinatorics and Optimization from the University of Waterloo. His research focuses on complex decision-making under uncertainty, including dynamic resource allocation, process flexibility, vehicle routing, and queueing networks. He has been recognized with awards such as the George Nicholson Paper Competition and the Daniel H. Wagner Prize. His teaching spans business analytics and operations research courses at both master's and doctoral levels, earning him the 2023 MQM Teaching Award for Innovation and Excellence. Education: Ph.D. in Operations Research Center (ORC), MIT Bachelor's in Combinatorics and Optimization and Pure Math, University of Waterloo Research emphasizes developing methodologies for managing uncertainties through convex optimization, stochastic networks, and game theory. Notable contributions include work on fulfillment flexibility in e-commerce, vehicle routing with stochastic demand, and strategic service network design. Articles frequently explore intersections of operations research with real-world applications like supply chain resilience and inventory systems. Awards include the 2023 TSL Intelligent Transportation Systems SIG Paper Award and the 2019 MSOM Service Management SIG Best Paper Prize. He has advised on multiple doctoral and master's theses, though specific advisee names are not listed. His work addresses challenges in logistics, manufacturing, and service industries, often employing advanced analytical frameworks to enhance system efficiency and robustness.

Zbigniew T Kalbarczykمشاهده پروفایل

استاد پژوهشی

• Computer Security
• Fault Tolerance
• Reliable Systems
• +۷ مورد دیگر

Zbigniew T. Kalbarczyk is a Research Professor at the Coordinated Science Laboratory and the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign (UIUC), holding this position since 2004. He holds M.S. degrees in Mechanical Engineering (Technical University of Warsaw, 1981) and Electronic Engineering (Technical University of Sofia, 1984), as well as a Ph.D. in Computer Science from the Bulgarian Academy of Sciences (1992). His research focuses on reliable and secure computing systems , including fault tolerance, cybersecurity, and cyberphysical systems. He leads the DEPEND Group, which investigates trustworthy systems, health analytics, and big-data applications. Key projects include securing supercomputing infrastructure against environmental attacks, improving IoT security, and advancing healthcare systems through AI-driven solutions. Recent collaborations involve industry partners like IBM, Mayo Clinic, and the National Science Foundation (NSF), with notable funding such as a $500K NSF grant for cybersecurity research. His work bridges theoretical concepts and practical implementations, emphasizing real-world testing on systems like Blue Waters supercomputers and smart grids. Notable students include Krishnakant Saboo (Ph.D. 2023), Homa Alemzadeh (William Carter Award recipient), and Arjun Athreya (best paper award winner). The DEPEND Group also collaborates internationally, including with Singapore’s VinUniversity and the National University Hospital.

Pu Wangمشاهده پروفایل

دانشیار

• Computer Networking
• Cyber-Physical Systems
• Internet of Things
• +۴ مورد دیگر

Pu Wang is an Associate Professor in the Department of Computer Science at the University of North Carolina at Charlotte (UNC Charlotte), part of the College of Computing and Informatics (CCI). His research focuses on networked systems, generative AI, computer vision, and computational biomechanics. He holds a Ph.D. from Georgia Institute of Technology (2013) and previously served as an Assistant Professor at Wichita State University (2013–2016). Education: B.E. in Electrical Engineering, Beijing Institute of Technology, 2003 M.E. in Electrical and Computer Engineering, Memorial University of Newfoundland, 2008 Ph.D. in Electrical and Computer Engineering, Georgia Tech, 2013 Research interests include modeling of networked systems (e.g., Software Defined Networking, IoT), AI-driven human mesh recovery, and biomechanically accurate 3D pose estimation. His work is supported by NSF grants and has led to advancements in federated learning, motion synthesis, and underwater communication systems. Awards and Honors: John A. See Innovation Award (Wichita State, 2016) BWN Lab Researcher of the Year (Georgia Tech, 2012) Best Student Paper Runner-Up (IEEE SCC 2016) Fellow of Memorial University’s School of Graduate Studies (2008) Key publications span top venues like ICCV, CVPR, AAAI, and IEEE journals, addressing topics such as masked motion control, vision-language models, and federated learning optimization. He actively mentors graduate students in AI/ML, computer vision, and network systems.

Siddhartha Banerjeeمشاهده پروفایل

دانشیار

• Data-driven decision-making
• Stochastic control
• Economics and computation
• +۳ مورد دیگر

Sid Banerjee is an Associate Professor in the School of Operations Research and Information Engineering at Cornell University , with field memberships in the Computer Science Department , Electrical and Computer Engineering (ECE) , and the Center for Applied Mathematics . His research focuses on the intersection of data-driven decision-making , stochastic control , economic theory , and large-scale network algorithms , with applications to ride-sharing platforms, online marketplaces, and smart transit systems. His work has been recognized with prestigious awards including the NSF CAREER award , multiple grants from NSF (CNS 1955997, CNS 1952011, DMS 1839346), and support from ARL Network Sciences and Engaged Cornell . He has advised numerous PhD students and postdoctoral researchers, many of whom have transitioned to academic positions at institutions like MIT Sloan , Facebook Research , and Amazon . His recent publications analyze problems in fair allocation , information design , reinforcement learning , and market robustness , often combining tools from online algorithms , Bayesian game theory , and large-scale optimization . During 2021-2022, he was on sabbatical at the Simons Institute in Berkeley, co-organizing the program on Data-Driven Decision-Making .

Ruhai Wangمشاهده پروفایل

استاد

• Satellite Networks
• Delay-Tolerant Networks
• Space Communications
• +۳ مورد دیگر

Dr. Ruhai Wang is a Professor in the Phillip M. Drayer Department of Electrical and Computer Engineering at Lamar University. He holds a Ph.D. in Electrical/Computer Engineering from New Mexico State University and leads research in space communication networks. His office is located in the Cherry Building (Rm. 2205), and he can be contacted at rwang@lamar.edu or (409) 880-1829. Research Focus: Dr. Wang specializes in Delay-/Disruption-Tolerant Networks (DTN), satellite/space communications, cybersecurity, and wireless ad hoc networks. His work bridges theoretical modeling and practical implementations for space Internet systems, with ongoing projects focused on DTN protocol development for NASA collaborations. Publication Trends: His 15 most recent publications (2016-2020) primarily analyze protocol optimization for space communications, with emphases on Licklider Transmission Protocol (LTP), Bundle Protocol efficiency, deep-space channel modeling, and integrated terrestrial-satellite networks. Key themes include disruption resilience, transmission timing optimization, and network scalability under asymmetric conditions. Awards and Honors: Distinguished Lecturer, IEEE AESS (2025) Teaching Board Member, Ph.D. Program in STIET, University of Genova (2018-Present) Best Associate Editor, IEEE Aerospace & Electronics Systems Magazine (2015) Lamar University Presidential Faculty Fellowship (2015) IEEE ComSoc Best Tutorial Paper Nominee (2009) University Merit Award (2007) Advising and Projects: Currently mentoring doctoral candidates Alaa Sabbagh and Hacer Varol, and MSEE students Qinglin Xie and Arkun Zhuang. His primary project involves developing DTN protocols for space networks through a NASA/JPL-collaborated testbed. Grant-supported research focuses on reliable data delivery in deep-space environments. Professional Service: Senior IEEE member (AESS, ComSoc), Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and IEEE Aerospace & Electronics Systems Magazine. Former TPC co-chair for IEEE ICC and organizer of international workshops on satellite communications.

Lei Jiaoمشاهده پروفایل

استاد پژوهشی

• AI Systems
• Edge Computing
• Cloud Computing
• +۵ مورد دیگر

Dr. Lei Jiao is a Research Professor at the School of Computer and Data Sciences , University of Oregon, specializing in large-scale systems across cloud, edge, and NextG networks. Their interdisciplinary work integrates network optimization , machine learning , and game theory to enhance system efficiency, scalability, sustainability, and resilience. Research interests include Edge AI , Cloud Computing , Energy Systems , Cybersecurity , and Multimedia . Current affiliations: Center for Cyber Security and Privacy , University of Oregon; former role at Nokia Bell Labs , Ireland. Dr. Jiao's recent publications focus on AI systems in cloud-edge environments, resource orchestration , cybersecurity , and energy-efficient computing . Their work has earned recognition through IEEE/ACM awards and grants from the National Science Foundation and Ripple . As an educator, Dr. Jiao teaches Intermediate Algorithms , Optimization , and Edge Computing Seminars . They actively mentor PhD and MSc students across institutions like Fudan University , BUPT , and University of Oregon .

Zongli Linمشاهده پروفایل

استاد

• Nonlinear Control
• Robust Control
• Control Applications
• +۶ مورد دیگر

Zongli Lin is the Ferman W. Perry Professor and Associate Chair for Graduate Studies in the Department of Electrical and Computer Engineering at the University of Virginia's School of Engineering and Applied Science. His research focuses on nonlinear control, robust control, and control applications, with recent work spanning reinforcement learning, microgrid resilience, and HVAC system optimization. He has held editorial roles at journals like Automatica and serves as series editor for Springer/Birkhauser's Control Engineering series. Lin's academic leadership includes board memberships with the IEEE Control Systems Society and chairing its Technical Committee on Nonlinear Systems and Control. He is General Chair of the 2028 American Control Conference. His honors include IEEE, IFAC, and AAAS Fellowships. Research interests emphasize control theory applied to energy systems (e.g., battery storage, DC microgrids) and multi-agent systems. Over 150 publications reflect contributions to anti-windup compensation, distributed control algorithms, and adaptive control methodologies. Lin advises graduate students focusing on control systems theory and applications. His work integrates theoretical advancements with practical implementations, such as CO₂ controller design for cell culturing systems and HVAC energy optimization frameworks.

• Applied Mathematics
• Statistics
• Strategy
• +۷ مورد دیگر

Prof. Hanqin Zhang is a Professor in the Department of Analytics And Operations at the National University of Singapore (NUS Business School). He holds a Doctor of Science from the Chinese Academy of Sciences (1991) and a Master of Science from Xian Jiaotong University (1985). His research focuses on applied mathematics, statistics, strategy, transportation logistics, control engineering, and numerical methods. He has served as an associate editor for journals like European Journal of Operational Research and TOP , and has reviewed for top-tier journals including Operations Research and Queueing Systems . His recent work addresses optimal inventory policies, queueing systems, and stochastic control, with notable contributions to dual-sourcing strategies, staffing optimization in ticket queues, and fluid models of parallel service systems. He has supervised students in stochastic processes and inventory management, reflecting his expertise in bridging theoretical advancements with practical applications in operations research. Notable research trends include leveraging order-tracking information for inventory systems, analyzing ergodicity in Markov chains, and optimizing multi-source supply chains under uncertainty. His publications span high-impact journals such as Operations Research and Queueing Systems , showcasing a focus on stochastic systems and operations management.

• Operations Research
• Robust Optimization
• Queueing Theory
• +۷ مورد دیگر

Chaithanya Bandi is an Associate Professor at the National University of Singapore (NUS) in the Analytics and Operations Department of the NUS Business School, with a joint appointment in the Department of Mathematics. His research focuses on decision-making under uncertainty, robust optimization, and their applications in operations management, healthcare, e-commerce, and energy systems. He develops robust optimization models for queueing control, risk optimization, and mechanism design. Key research areas include robust queue inference, two-stage distributionally robust optimization, and multi-item auction mechanisms. He has contributed to operational challenges in healthcare (e.g., patient re-entry scheduling), energy systems (electricity generation optimization), and e-commerce (price optimization for fashion products). His work integrates theoretical advancements with practical implementations in large-scale systems. Recent publications emphasize adversarial evaluation of large language models, dynamic scheduling algorithms, and robust policies for uncertain environments. His methodologies often involve novel optimization frameworks and scalable computational approaches. Dr. Bandi holds a PhD in Operations Research and has collaborated with industry leaders like Flipkart and healthcare providers to apply his models in real-world settings. His contributions bridge theoretical rigor and practical applicability in complex operational systems.

Eric Torngمشاهده پروفایل

دانشیار

• Algorithms
• Online Algorithms
• Scheduling
• +۴ مورد دیگر

Eric Torng is an Associate Professor in the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), serving as Associate Chair for Research and Faculty Development in CSE and Associate Dean of MSU's Graduate School. He holds a Ph.D. from Stanford University (1994) and has received awards including the NSF CAREER Award (1997) and multiple teaching excellence awards. His research focuses on algorithms, online algorithms, scheduling, perimeter defense strategies, and packet processing. Notable contributions include multi-vehicle perimeter defense systems, fast packet classification techniques (e.g., TupleMerge), and algorithmic approaches to resource optimization. Dr. Torng has authored over 100 publications and secured over $2 million in external grants. His work bridges theoretical computer science with practical applications in networking, robotics, and distributed systems.