جست‌وجوی استاد و پژوهشگر

Samir Elhedhliمشاهده پروفایل

استاد

• Large-scale Optimization
• Logistics
• Supply Chain Management
• +۱۱ مورد دیگر

Samir Elhedhli is a Professor in the Department of Management Sciences at the University of Waterloo, within the Faculty of Engineering. His research focuses on Large-scale Optimization, Logistics, Supply Chain Design, Healthcare Operations, Airline Scheduling, and Data Analytics. He has held grants from NSERC, CFI, OCE, and MITACS, collaborating with industries in aircraft manufacturing, airline scheduling, and warehouse management. Education: PhD in Management Science, McGill University (2001) Master's in Industrial Engineering, Bilkent University (1996) Bachelor's in Industrial Engineering, Bilkent University (1994) Research Interests: Data Analytics & Data Science Large-scale Optimization (Interior-point methods, decomposition, column generation) Supply-chain Analytics (Logistics, warehousing, routing, scheduling) Environmental Sustainability in Supply Chains Key Awards: CORS Service Award (2013) University of Waterloo Distinguished and Outstanding Performance Awards (2005–2019) Grants & Advising: Active grants from NSERC, CFI, OCE, and MITACS Currently accepting graduate student applications Administration & Service: Chair, Department of Management Sciences (2014–2018) President, Canadian Operational Research Society (2011–2012) Co-Editor-in-Chief, INFOR Journal (2014–present) Labs & Teams: Leads the WanOpt research group focused on optimization methodologies and applications.

Churlzu Limمشاهده پروفایل

دانشیار

• Operations Research
• Mathematical Optimization
• Nonlinear Programming
• +۱۱ مورد دیگر

Dr. Churlzu Lim serves as Associate Professor, Associate Chair and Curriculum Director in the Industrial and Systems Engineering Department at the University of North Carolina at Charlotte. He also functions as the Undergraduate Program Director and teaches across both graduate and undergraduate engineering programs. His academic credentials include: Ph.D. in Industrial and Systems Engineering from Virginia Polytechnic Institute and State University M.S. in Management Engineering from Korea Advanced Institute of Science and Technology B.S. in Management Science from Korea Advanced Institute of Science and Technology Dr. Lim's research centers on Operations Research and Mathematical Optimization , with specialized expertise in nonlinear programming, global optimization, and network interdiction problems. His theoretical work addresses nondifferentiable optimization for Lagrangian duals of large-scale mixed integer programs and network games using multilevel programming. Practical applications of his research span supply chain analysis, project risk management, and production planning systems including the flexible requirements profile (FRP) methodology. Recent work explores new service development in autonomous EV charging systems within machine-to-machine environments. His scholarly contributions have been recognized with significant awards: IIE Transactions Best Paper Award (2008) IIE Pritsker Doctoral Dissertation Award, 2nd Place (2005) Grado Fellowship at Virginia Tech (2001-2004) INFORMS Doctoral Colloquium Participant (2003) Dr. Lim teaches graduate courses including Engineering Systems Optimization, Integer Programming, and Processing Systems Simulation, along with undergraduate courses in deterministic and stochastic systems analysis. His instructional approach integrates theoretical frameworks with real-world engineering applications. As Associate Chair and Curriculum Director, he plays a key role in academic program development and educational leadership within the department.

• Machine Learning
• Optimization
• Data Mining
• +۲ مورد دیگر

Dr. Annabella Astorino is a researcher at ICAR-CNR (Italian National Research Council) in Rende, Italy, with expertise in machine learning, optimization, and computational biology. Her work focuses on classification algorithms using nonsmooth optimization, spherical separation, and multiple instance learning (MIL) approaches. Key Research Themes Geometric separation techniques (polyhedral, spherical) Multiple instance learning for biomedical applications Nonsmooth optimization in semisupervised learning Clustering methods for edge detection in images Recent publications highlight her development of Lagrangian relaxation for MIL, kernel-enhanced spherical separation algorithms, and DC optimization for computer vision tasks. Her collaborations include researchers like A. Fuduli, M. Gaudioso, and P. Veltri.

Robert Dylewskiمشاهده پروفایل

استاد

• Nondifferentiable convex optimization
• Projective methods
• Petri nets and linear programming
• +۱۳ مورد دیگر

Dr. Robert Dylewski , a Professor at the Institute of Mathematics at the University of Zielona Góra, specializes in nonlinear analysis, optimization, and mathematical modeling applied to economic and ecological systems. His research spans theoretical and applied domains, with focus areas in iterative algorithms, combinatorial geometry, and nonlinear wave propagation. Key research themes include: nondifferentiable convex optimization, projective methods, Petri nets, energy efficiency, flexible production systems. Teaching activities cover optimization methods, decision theory, and operational research fundamentals. Current work explores relationships between Gaussian and Archimedes-Borchardt algorithms, nonlinear wave equations generalizing Korteweg-de Vries, stochastic solutions for nonlinear PDEs, and geometric partitions in Euclidean space. His mathematical investigations integrate topology, graph theory, and computational methods.

María Beatriz Hernández Jiménezمشاهده پروفایل

استاد

• Operations Research
• Mathematical Programming
• Optimization Theory
• +۶ مورد دیگر

María Beatriz Hernández Jiménez is a Full Professor at Pablo de Olavide University, affiliated with the Department of Economics, Quantitative Methods and Economic History. She earned her PhD from the University of Seville in 2007, supervised by Dr. Marko Antonio Rojas-Medar and Dr. Rafaela Osuna Gómez, with a thesis titled 'Generalized Convexity in Non-Regular Optimization Problems'. Research Focus Her work centers on mathematical optimization under uncertainty , specializing in generalized convexity, interval-valued functions, fuzzy programming, and multiobjective decision-making. Key areas include: Development of optimality conditions for non-differentiable and interval-valued systems Duality theory in Riemannian manifolds and conic-constrained problems Efficiency analysis in multiobjective optimization Publication Trends Her 15 most recent articles (2013–2023) reveal a strong emphasis on generalizing differentiability concepts (e.g., Hukuhara derivatives for interval-valued functions) and extending optimality frameworks to fuzzy/interval contexts. Over 60% of these works address multiobjective or non-regular problems, often incorporating variational inequalities, conic constraints, or Riemannian geometry. Collaborations She frequently collaborates with researchers at the intersection of optimization and applied mathematics, including Rafaela Osuna-Gómez and Gabriel Ruiz-Garzón.

• Optimization
• Operations Research
• Machine Learning
• +۴ مورد دیگر

Ying Cui serves as an Assistant Professor in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley, where she conducts foundational research in data science optimization. She holds editorial responsibilities as associate editor for Mathematical Programming and serves as vice chair of Nonlinear Optimization for the INFORMS Optimization Society. Her academic background includes: Ph.D. in Mathematics from the National University of Singapore B.Sc. in Mathematics from Zhejiang University, China Dr. Cui's research centers on mathematical optimization frameworks for complex decision systems, with particular expertise in nonsmooth/semidefinite variational analysis , stochastic programming under uncertainty , and computational methods for nonconvex machine learning problems . Her work bridges theoretical advances with practical applications in operations research and statistical estimation, emphasizing algorithmic efficiency for modern data challenges. Her major recognitions include: Mathematical Programming Meritorious Service Award (2023) NSF CISE Research Initiation Initiative Award (2022) INFORMS JFIG Paper Prize (Third Place, 2022) Louis Chen Hsiao Yun Best Dissertation Prize (NUS, 2016) Dr. Cui secured significant research funding through the NSF CRII Award (2022) and actively mentors graduate students, evidenced by her finalist status as faculty advisor for the Dupacova-Prekopa Best Student Paper Prize (2023). She has co-authored the influential monograph Modern Nonconvex Nondifferentiable Optimization in the MOS/SIAM Series on Optimization, establishing foundational methodologies for contemporary optimization challenges.

• Optimization Techniques
• Programming Models
• Mathematical Methods for Economics
• +۷ مورد دیگر

Alberto Peretti is an Associate Professor at the Department of Economics of the University of Verona since 2007, with previous academic appointments as Associate Professor at the University of Milano-Bicocca (1998-2007) and Researcher at the University of Verona (1988-1998). His research expertise spans mathematical optimization with applications in economics and finance: Specializes in JEL C61 - Optimization Techniques; Programming Models; Dynamic Analysis Focuses on MSC classifications including 49M37 (nonlinear programming), 65K05 (mathematical programming), and 90C series (linear/nonlinear programming) Research covers gradient methods, conjugate gradient, Newton-type methods, penalization methods, and interior point methods His scholarly work addresses both differentiable and non-differentiable optimization problems with applications to portfolio optimization, financial model calibration, and economic decision-making under uncertainty. His teaching portfolio includes Mathematical Models for Economic and Financial Decisions and Mathematics courses for undergraduate economics programs. Peretti earned his Mathematics degree from the University of Padua and completed a visiting fellowship at the Numerical Optimization Centre of Hatfield Polytechnic (UK). He maintains an active research profile with publications spanning from 1987 to 2024. He participates in departmental governance through the Economics Department Council and various committees, and is affiliated with research centers including CIDE (Centro Interuniversitario di Econometria) and CRIEP (Centro di Ricerca Interdipartimentale sull'Economia Pubblica).

Clément Vidalمشاهده پروفایل

استادیار

• High Energy Astrobiology
• Cosmological Natural Selection
• Philosophy of Cosmology
• +۸ مورد دیگر

Clément Vidal is a philosopher and assistant professor at the Free University of Brussels (VUB) , affiliated with the Global Brain Institute , the Evolution, Complexity and Cognition group , and the Center Leo Apostel . He earned a Bachelor’s (2002), Master’s in Philosophy (2003), Master’s in Logic (2004), Master’s in Cognitive Sciences (2005), Teaching Diploma (2009), Ph.D. in Philosophy (2013) all from major European institutions. His research bridges cosmology, philosophy, and complexity science, focusing on the evolutionary developmental (Evo Devo) Universe hypothesis and the Global Brain as a planetary intelligence network. He pioneered high energy astrobiology to search for advanced extraterrestrial life in binary star systems and developed a Cosmic Evolution Equation to study complexity emergence across possible universes. His 2014 book The Beginning and the End: The Meaning of Life in a Cosmological Perspective proposes cosmological ethics and immortality narratives. Key contributions include: Founding the Evo Devo Universe research community with John Smart, Establishing the High Energy Astrobiology prize, Advancing metaphilosophical criteria for worldview comparison, Exploring computational analogies in cosmology.

Francisco Facchineiمشاهده پروفایل

استاد

• Nonlinear Optimization
• Nondifferentiable Optimization
• Complementarity Problems
• +۴ مورد دیگر

Francisco Facchinei is a Professor at Sapienza University of Rome, affiliated with the Department of Computer, Automatic and Management Engineering Antonio Ruberti within the College of Engineering. His research spans nonlinear and non-differentiable optimization, complementarity problems, variational inequalities, and game theory applications in telecommunications. His work focuses on developing algorithms for nonconvex optimization with ghost penalties, asynchronous distributed methods, and applications in healthcare and communications systems. Key Contributions: Foundational work in variational inequality theory, generalized Nash equilibrium problems, and optimization over dynamic networks. Recent Trends: Emphasis on asynchronous parallel algorithms, stochastic optimization, and non-invasive medical diagnostics via machine learning. He has held academic positions at Sapienza University since 1990, progressing from Ricercatore to Professore Ordinario. No scientific awards are explicitly mentioned in the provided texts.