جست‌وجوی استاد و پژوهشگر

• Operations Research
• Optimization Models
• Linear Programming
• +۶ مورد دیگر

Juan Carlos Espinoza-García is an Adjunct Professor in the Department of Administration and Business Management at Tecnológico de Monterrey (Campus Querétaro). His part-time role includes teaching optimization-focused courses and conducting applied research in industrial systems. He holds affiliations with the Challenge Based Research Fund and contributes to Sustainable Development Goals (SDG 9: Industry/Innovation, SDG 11: Sustainable Cities). Education: PhD Business Administration - ESSEC Business School MS Industrial Engineering - University of Michigan MS Manufacturing Systems - Tecnológico de Monterrey BS Industrial Engineering - Tecnológico de Monterrey His research specializes in operations research and optimization methodologies , particularly Linear/Mixed-Integer Programming applied to logistics, scheduling, and robust decision-making under uncertainty. This work addresses real-world industrial challenges through mathematical modeling, emphasizing efficiency in supply chains and production systems. Recent publications highlight interdisciplinary applications: A 2024 study integrates project management frameworks into engineering education, while 2019 work optimizes quality inspection processes in manufacturing. This reflects consistent focus on bridging theoretical optimization with practical implementation. Teaching responsibilities include: Heuristics/Metaheuristics for Process Optimization Value Chain Modeling Intelligent Logistics Networks Organizational Process Optimization

Claudia Solís-Lemusمشاهده پروفایل

استادیار

• Statistical Modeling
• Phylogenetics
• Microbiome Analysis
• +۳ مورد دیگر

Claudia Solís-Lemus is an Assistant Professor in the Department of Plant Pathology at the University of Wisconsin-Madison, where she develops statistical and machine learning methods to solve complex biological problems. Her work bridges computational statistics with plant pathology and evolutionary biology, focusing on network-based approaches to genomic and microbiome data. Educational background: PhD in Statistics, University of Wisconsin–Madison Her research centers on phylogenetic network inference , microbiome analysis , and high-dimensional statistical modeling . She creates open-source tools like CMiNet and MiNAA to empower biologists with robust network analysis capabilities. Her lab tackles challenges in biodiversity research, agricultural disease prediction, and microbial ecology through innovative computational frameworks that handle massive biological datasets. Analysis of her 2024-2025 publications reveals a cohesive focus on scalable network inference methods across phylogenetics and microbiome studies. She integrates Bayesian statistics, regularization techniques (e.g., spike-and-slab LASSO), and high-performance computing to address data complexity. Her work consistently emphasizes practical software implementation (R packages, Shiny apps, Julia tools) for real-world biological applications including potato disease prediction, hornwort evolution, and freshwater ecosystem dynamics. Scientific recognition: NSF CAREER Award (2022) for "Towards Scalable and Robust Inference of Phylogenetic Networks" Dr. Solís-Lemus leads an interdisciplinary research group at the Wisconsin Institute for Discovery, securing competitive grants to advance phylogenetic network methodology. Her CAREER project combines algorithmic innovation with educational outreach to train next-generation computational biologists. Current efforts focus on improving network inference for polyploid genomes and developing consensus methods for microbiome data integration across diverse environmental conditions. The Solís-Lemus Lab operates within UW-Madison's Wisconsin Institute for Discovery ecosystem, fostering collaborations between statisticians, computer scientists, and biologists. Her team actively develops user-friendly software to lower computational barriers for life scientists studying evolutionary processes and microbial communities.

İHSAN GÜZELمشاهده پروفایل

مدرس

• Transportation Engineering
• Civil Engineering
• Road Construction
• +۲ مورد دیگر

Dr. İhsan Güzel serves as a Lecturer in the Faculty of Engineering and Architecture at Bingol University, Turkey. His academic work builds upon 28 years of professional experience with the Turkish General Directorate of Highways (KGM), where he held progressively responsible engineering roles from 1988 to 2016. His educational foundation includes: Undergraduate Degree from Firat University Master's Degree from Firat University PhD from Firat University Dr. Güzel's research centers on practical transportation engineering challenges, particularly road construction, maintenance optimization, and traffic safety. His work investigates asphalt mixture innovations (including steel fiber reinforcement and recycled materials), road geometry design, seismic resilience of infrastructure, and cost-effective maintenance solutions. Recent studies focus on utilizing earthquake debris in road construction, traffic sign impacts on vehicle operating costs, and parametric modeling of road maintenance expenses. His publication record shows consistent output with 15 significant works from 2007-2024, accelerating notably after 2018. The research demonstrates strong regional focus on Eastern Anatolia (particularly Bingöl Province) while addressing national transportation challenges. His methodology blends field data collection, laboratory testing, and statistical analysis to solve practical highway engineering problems. Dr. Güzel maintains active collaborations with researchers from Bitlis Eren University, Dicle University, and other Turkish institutions. His industry background provides unique practical insights that bridge academic research and real-world infrastructure implementation. While no formal awards are documented, his sustained publication output and applied research approach demonstrate significant contribution to transportation engineering practice in Turkey. His advising capacity and grant activity aren't explicitly documented, but his collaborative publications suggest engagement with graduate students and research projects.

Jean-François Côtéمشاهده پروفایل

استاد

• Combinatorial optimization
• Stochastic programming
• Mathematical programming
• +۵ مورد دیگر

Jean-François Côté is a Full Professor at the Department of Operations and Decision Systems within the Faculty of Business Administration at Laval University. His research focuses on combinatorial optimization, stochastic programming, and mathematical programming with applications in vehicle routing, cutting and loading problems, and logistics optimization. Dr. Côté holds a Doctorate in Computer Science, Operations Research from the University of Montreal, along with Master's and Bachelor's degrees in the same field from the same institution. His academic credentials provide a strong foundation for his interdisciplinary research at the intersection of computer science and operations research. His research spans several key areas in operations research including: Combinatorial optimization techniques for complex routing problems Stochastic programming approaches for handling uncertainty in logistics Mathematical programming models for integrated decision making Vehicle routing and delivery optimization in various contexts Cutting and loading problems in transportation and manufacturing Professor Côté's recent publication record demonstrates a strong focus on solving complex logistics and transportation problems with mathematical rigor. His work addresses challenging real-world problems including same-day delivery optimization, bike sharing systems, home healthcare routing, and automotive manufacturing sequencing. His methodological contributions include novel algorithmic approaches such as logic-based Benders decomposition, disaggregated integer L-shaped methods, and branch-and-regret algorithms. Dr. Côté has published extensively in top-tier operations research journals including: INFORMS Journal on Computing European Journal of Operational Research Transportation Science Computers & Operations Research Operations Research He actively collaborates with researchers across North America and Europe through the CIRRELT research center. His work addresses practical problems faced by industries including transportation, healthcare, manufacturing, and e-commerce. Professor Côté supervises graduate students working on cutting-edge optimization problems and contributes to advancing both theoretical and applied aspects of operations research. His laboratory, part of the broader research ecosystem at Laval University, focuses on developing innovative mathematical models and algorithms to solve complex decision-making problems in logistics and supply chain management.

• Real-Time Scheduling
• Model-Based Systems Engineering
• Unmanned Aerial Vehicles
• +۳ مورد دیگر

Emmanuel Grolleau is a Full Professor at ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace - École Nationale Supérieure de Mécanique et d'Aérotechique) specializing in real-time systems. He is affiliated with the LIAS laboratory (Laboratoire d'Ingénierie des Applications de la Sensorique) where he leads the Real Time Team. His work bridges theoretical scheduling principles with practical embedded system implementations across multiple domains. Professor Grolleau's primary research interests include: Real-Time Scheduling: uniprocessor, multiprocessor, and distributed scheduling with practical considerations like transactions and precedence constraints Model-Based Systems Engineering (MBSE): developing bridges between UML-MARTE and AADL to real-time scheduling tools Unmanned Aerial Vehicles (UAVs): autopilot architecture design and optimization Energy Systems: co-heading the LabCom ANR Laboratoire d'Insertion des Énergies Nouvelles et d'Optimisation des Réseaux (LIENOR) His publication record demonstrates a clear progression from fundamental scheduling theory to applied work spanning avionics, drone technology, and power systems. Recent work shows strong focus on UAV autopilot architectures, model-based frameworks for real-time systems, and energy management in power distribution networks. Professor Grolleau serves on multiple prestigious program committees including Real-Time Networks & Systems (RTNS) since 2012, ACM/SIGAPP Symposium On Applied Computing (SAC) since 2015, DETECT since 2018, and DroneSE in 2023. He has led significant research projects such as PIA CORAC Panda and FUI WARUNA, which developed the Time4Sys pivot meta-model to connect theoretical scheduling with practical implementation. His collaborative work extends across multiple institutions and industries, with publications spanning real-time scheduling theory, UAV systems, energy management, and avionic architectures. The consistent thread through his work is the practical application of real-time scheduling principles to solve complex engineering problems in safety-critical systems.

Ricardo Ferreiraمشاهده پروفایل

پژوهشگر

• Spintronics
• Magnetic Tunnel Junctions
• Nano-oscillators
• +۷ مورد دیگر

Ricardo Ferreira serves as Research Scientist Group Leader of the Spintronics research group at the International Iberian Nanotechnology Laboratory (INL). With a PhD in Physics Engineering from Instituto Superior Técnico (IST) completed in 2008, his career has focused on advancing spintronics technology through Magnetic Tunnel Junctions (MTJs). His research group develops high-yield fabrication processes for both micro-scale (down to 1μm²) and nano-scale (down to Dr. Ferreira's research interests span multiple cutting-edge areas in spintronics, with primary focus on nano-oscillators, neuromorphic computing architectures, and advanced magnetic field sensors. His work bridges fundamental physics with practical applications, particularly in developing devices that exploit spin transfer and spin Hall effects for next-generation computing paradigms. The group has made significant contributions to RF signal processing, true random number generation, and physical unclonable functions using spintronic devices. His recent publications reveal a strong trend toward neuromorphic computing applications, with multiple papers on spin-torque nano-oscillators for reservoir computing, weighted neural networks, and RF signal classification. The research demonstrates increasing sophistication in controlling vortex states and coupled oscillator dynamics for computational applications, while maintaining strong contributions to fundamental spintronics phenomena and sensor development. Co-author of 150+ peer-reviewed publications Co-inventor in 4 patent applications submitted at INL Participant in 6 European projects in the last decade Leader of multiple high-TRL industrial application projects Ferreira actively mentors PhD students and postdoctoral researchers, with several alumni having completed their doctoral work under his supervision. His group engages in both fundamental research and applied projects targeting Industry 5.0 ready production systems and space applications. The laboratory maintains advanced fabrication capabilities including UHV sputtering systems, ion milling equipment, and comprehensive characterization tools for spintronic device development.

WATANABE Takeshiمشاهده پروفایل

استاد

• Fluid Engineering
• Atmospheric Sciences
• Mathematical Physics
• +۴ مورد دیگر

Professor Takeshi Watanabe serves in the Department of Applied Physics at Nagoya Institute of Technology's Graduate School of Engineering. Specializing in fluid dynamics and turbulence theory, his research bridges fundamental physics with atmospheric and industrial applications. Education: Doctor of Science (2000.03, Kyushu University) Master of Science (1997.03, Kyushu University) Bachelor's Degree (1995.03, Tokyo University of Science, Faculty of Science, Department of Applied Physics) Watanabe's research focuses on turbulent flows , particularly particle-laden turbulence, cloud microphysics, and passive scalar transport. His work employs advanced computational techniques including direct numerical simulation (DNS) to investigate phenomena like energy dissipation statistics, vortex dynamics, and polymer scission in turbulent environments. Key contributions include modeling turbulence modulation by particles and supersaturation spectra in cloud systems. His publication record demonstrates consistent high-impact contributions to fluid mechanics, with recent articles in Physical Review Fluids and Journal of Fluid Mechanics addressing fundamental turbulence characteristics across diverse applications from atmospheric science to industrial fluid systems. Awards: Fellow Member Certification (Japan Society of Fluid Mechanics, 2023) HPCI Outstanding Research Achievement Award (RIST, 2021) Japan Fluid Mechanics Society Central Chapter Outstanding Presentation Award (2004) As Principal Investigator for multiple competitive grants including JSPS Kakenhi projects (totaling over ¥48 million), Watanabe leads collaborative research on cloud turbulence and particle-fluid interactions. His advisory role extends to high school outreach programs at Nagoya Institute of Technology, demonstrating commitment to science education. Watanabe actively contributes to academic governance as理事 (Board Member) of the Japan Society of Fluid Mechanics and strategic committee member at the National Institute for Fusion Science, where his expertise in turbulence informs plasma simulation research.