جست‌وجوی استاد و پژوهشگر

Matthias Walterمشاهده پروفایل

استادیار

• Operations Research
• Optimization
• Mathematical Programming
• +۵ مورد دیگر

Matthias Walter is an Assistant Professor in the Department of Mathematics of Operations Research. His research focuses on optimization, mathematical programming, and algorithm design, with applications in transportation, combinatorial optimization, and logistics. He contributes to the SCIP Optimization Suite and has developed the Combinatorial Matrix Recognition Library. His work spans topics such as linear programming relaxations, pseudo-Boolean solving, and multilinear optimization. Key research interests include operations research, integer programming, and algorithmic solutions for complex optimization problems. He has collaborated on projects like optimizing parcel transportation and analyzing congestion games. His recent publications address challenges in flow shop scheduling, graph realization, and pseudo-Boolean functions. Walter actively participates in academic activities, organizing events like the Mathematical Olympiad in Saxony-Anhalt and presenting invited talks on topics such as McCormick relaxations. His contributions to computational tools and theoretical advancements highlight his role in advancing optimization methodologies.

Shaoning Hanمشاهده پروفایل

استادیار

• Mathematical Optimization
• Mixed-Integer Nonlinear Programming
• Nonsmooth Optimization
• +۳ مورد دیگر

Shaoning Han is a Presidential Young Professor (Assistant Professor) in the Department of Mathematics and the Institute of Operations Research and Analytics (IORA) at the National University of Singapore (NUS). He previously held a postdoctoral position at the University of Southern California (USC), working under Prof. Jong-Shi Pang. His research focuses on mathematical optimization, including mixed-integer nonlinear programming, nonsmooth optimization, and their applications in operations research and data science. Han earned his Ph.D. in Industrial Engineering from USC under Prof. Andrés Gómez and a B.S. in Mathematics from the University of Science and Technology of China (USTC). His work emphasizes advancing optimization methodologies, particularly for problems involving complementarity constraints, indicator variables, and sparsity. Recent contributions include progressive MIP methods for indefinite QPs, real-time solutions for banded matrix problems, and convexification techniques for nonconvex optimization. Han is actively recruiting PhD students interested in mathematical optimization. Research Highlights: His articles span theoretical advances (e.g., epi-stationarity analysis, parametric variational inequalities) and applied frameworks (e.g., robust SVMs, binarized neural networks). Key themes include polynomial-time solvability of MRFs, convex relaxations for low-rank functions, and sparse signal estimation. Awards: Third Place, INFORMS JFIG Paper Competition (2023) Journal of Global Optimization Best Paper Honorable Mention (2023) Teaching: Courses include MA5243 (Advanced Mathematical Programming) and MA3252 (Linear and Network Optimization). Labs/Teams: Active member of IORA, NUS’s Smart Nation Research Cluster.

• Operations Research
• Optimization
• Mathematical Programming
• +۵ مورد دیگر

Marianna De Santis is an Associate Professor in the Department of Information Engineering (Dipartimento di Ingegneria dell’Informazione) at the University of Florence, Italy. She previously held positions at Sapienza University of Rome and other institutions. Her research focuses on optimization, particularly in multiobjective programming, mixed-integer programming, and algorithm design. She has authored numerous articles in top journals and developed software tools like BBMOQIP and MOMIX for solving complex optimization problems. Education : PhD in Operations Research, Sapienza University of Rome (2012) MSc in Applied Mathematics (2007), BSc in Mathematics (2005) Research Interests : Dr. De Santis specializes in optimization theory and applications, including multiobjective optimization, integer programming, and algorithm design. Her work bridges theoretical advancements with practical implementations, addressing challenges in machine learning, bioinformatics, and operations research. Key areas include semidefinite programming, robust optimization, and exact methods for complex combinatorial problems. Articles Trends : Her recent work emphasizes multiobjective optimization, with contributions to hyperparameter optimization, robust combinatorial methods, and sustainable modeling. Publications span journals like Journal of Global Optimization and Mathematical Programming , reflecting her expertise in algorithmic innovation and mathematical rigor. Grants & Teaching : She leads projects on augmented Lagrangian methods and multiobjective integer optimization. Teaching includes courses on operations research, optimization, and data science at the undergraduate and graduate levels. She has also organized international workshops and served on conference committees. Labs/Teams : Her research group develops optimization software (e.g., BBMOQIP) and collaborates internationally on projects involving algorithm design and real-world applications.

• Operations Research
• Game Theory
• Optimization
• +۳ مورد دیگر

Julio González Díaz holds the position of General Coordinator of Doctorate and USC at the University of Santiago de Compostela , within the Department of Statistics, Mathematical Analysis and Optimization . His work focuses on advancing mathematical methodologies in optimization, game theory, and operations research, with notable contributions to polynomial optimization, energy network modeling, and algorithmic development. He oversees doctoral programs and contributes to academic governance at the university level. His research interests span game theory (especially cooperative and non-cooperative frameworks), optimization techniques (including global and polynomial optimization), and applied modeling in energy systems and supply chain networks. He has developed algorithms like RAPOSa for polynomial optimization and explored applications such as gas transmission networks and portfolio design. Publications emphasize computational efficiency in optimization, fairness in resource allocation , and interdisciplinary applications of game theory. His work bridges theoretical foundations with practical implementations, as seen in his contributions to open-source solvers and algorithmic advancements. He has received institutional recognition, including an Excellence Award in doctoral program administration. His academic leadership includes coordinating master's and PhD programs in statistical techniques and operations research, fostering educational innovation and international collaborations.

Amaya Nogales Gómezمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Machine Learning
• Telecommunications
• +۳ مورد دیگر

Amaya Nogales Gómez is an Associate Professor at the Interdisciplinary Institute for Artificial Intelligence (3IA) at Université Côte d’Azur and a member of the Wimmics Research Team. Her research focuses on combinatorial optimization, machine learning, and their applications in telecommunications and operations research. She holds a Ph.D. in Mathematics from the University of Seville (2015) and has held roles including Postdoctoral researcher at I3S and researcher at Huawei France (2014–2019). Education: PhD in Mathematics, University of Seville (2015); Postdoctoral studies at I3S, Sophia Antipolis. Her research interests include: Optimization algorithms for resource allocation and network design Machine learning techniques for pattern recognition and classification Applications in mobile video streaming and radio resource management Key research areas span telecommunications optimization, data-driven decision making, and mathematical modeling. She has contributed to patents and publications in top-tier conferences/journals. Current openings: See internship on Fairness-aware NLP here .

• Applied Mathematics
• Graph Theory
• Combinatorics
• +۳ مورد دیگر

Prof. Angelika Wiegele is a full Professor at the Department of Mathematics at Alpen-Adria-Universität Klagenfurt. She serves as a member of the university senate and head of the Institut für Mathematik. Her research focuses on semidefinite optimization, combinatorial optimization, and their applications in graph theory and operations research. She holds a Dipl.-Ing. (2001) and Dr. techn. (2006) from Alpen-Adria-Universität Klagenfurt, with thesis supervision by Franz Rendl. Her academic career includes positions at TU Graz, IASI-CNR Rome, and Universität zu Köln, as well as a visiting professorship at Università di Roma Tor Vergata. Her educational background includes studies at City University London (Erasmus) and TU Eindhoven (Leonardo project). Recent work emphasizes SDP-based methods for graph partitioning, edge expansion, and combinatorial problems, with a focus on high-performance computing solutions. Her research bridges theoretical optimization with practical applications in network design and algorithmic development. Publications from 2021–2024 highlight advancements in semidefinite programming for graph partitioning, SDP-based bounds for cutwidth, and exact solvers for clustering problems. She contributed to the BiqBin and SOS-SDP solvers for quadratic optimization and co-edited special journal issues on mixed-integer nonlinear optimization. Her work often appears in top operations research journals and conference proceedings. Prof. Wiegele has held global faculty positions at the University of Cologne (2022–2024) and is active in international research collaborations through PRACE high-performance computing initiatives. She maintains an ORCID profile and a university webpage with teaching and research materials.

Yossiri Adulyasakمشاهده پروفایل

استاد

• Supply Chain Analytics
• Optimization under Uncertainty
• Large-Scale Optimization
• +۴ مورد دیگر

Yossiri Adulyasak is a Full Professor in the Department of Logistics and Operations Management at HEC Montréal, holding the Canada Research Chair in Supply Chain Analytics. He is also an Adjunct Professor at the University of Montreal's Department of Computer Science and Operations Research and a scientific advisor at IVADO Labs. His research focuses on supply chain optimization, data-driven decision-making, and robust optimization under uncertainty, with applications in retail, transportation, and humanitarian logistics. Education: PhD in Operations and Logistics Management (HEC Montréal), Master of Civil Engineering in Transportation Engineering (Chulalongkorn University). Research Interests : Supply chain analytics, large-scale optimization algorithms, stochastic programming, machine learning integration, and resilient supply chain design. His work emphasizes practical applications in logistics networks, inventory management, and dynamic resource allocation under uncertainty. Recent Articles : Focus on AI-driven retail analytics, robust optimization for lot-sizing and facility location, and humanitarian logistics. Key topics include pandemic response strategies, electric vehicle routing, and drone delivery systems. Awards : Recipient of the 2021 Prix de recherche Chenelière Éducation/Gaëtan Morin for excellence in scientific publications. Supervision : Directed 3 PhD dissertations and over 40 master’s and project supervisions, collaborating with companies like Bombardier, Pratt & Whitney Canada, and JDA. Active in industrial partnerships for supply chain optimization solutions. Lab/Teams : Member of GERAD (Group for Research in Decision Analysis) and IVADO Labs, contributing to cross-disciplinary AI and operations research initiatives.

Sonia Cafieriمشاهده پروفایل

استاد

• Nonlinear Optimization
• Global Optimization
• Combinatorial Optimization
• +۳ مورد دیگر

Sonia Cafieri is a Professor at the École Nationale de l'Aviation Civile (ENAC) in Toulouse, part of the Université de Toulouse. She leads the Mathematics of Optimization and Operations Research (MORO) group within the OPTIM research team. Her roles include membership in the Managing Board of EUROPT and the Nonlinear Mathematical Programming group of GdR-ROD. She chairs the Program Committee of EUROPT 2021 and serves on ENAC's Research and Doctoral Councils. Education: HDR in Applied Mathematics (2012, Université Paul Sabatier), PhD (2006, University of Naples), and Laurea in Mathematics (2001, Second University of Naples). Research focuses on Nonlinear Optimization, Global Optimization, Combinatorial Optimization (network clustering), and Operations Research applications in air transportation and engineering. Recent work addresses air traffic management, trajectory optimization, and stochastic programming for robust scheduling. Publications span optimization methodologies and applications, with a focus on aircraft conflict resolution, drone trajectory planning, and robust cyclic scheduling. Software contributions include ROSE (reformulation engine) and COUENNE (MINLP solver). Teaching includes courses on Numerical Analysis, Combinatorial Optimization, and Operations Research for Air Transportation at ENAC and other institutions.

• Mechanical Engineering
• Additive Manufacturing
• Smart Materials
• +۴ مورد دیگر

Pascal LAFON is a Full Professor at the University of Technology of Troyes (UTT), affiliated with the Laboratory of Mechanical & Material Engineering (LASMIS) and the Department of Physics, Mechanics, Materials and Nanotechnology . He serves as the Director of Corporate Relations at UTT since 2023 and previously led LASMIS lab from 2012-2016. His academic duties include coordinating the 'Mechanics, Material and Advanced Manufacturing' master’s program (2018-2023) and the UTT doctoral program's 'Material, Mechanics, Optics and Nanotechnology' training (2012-2023). Director of Corporate Relations, UTT (2023-present) Head, LASMIS Lab (2012-2016) Master’s Program Coordinator (2018-2023) Doctoral Training Supervisor (2012-2023) His research focuses on Mechanical Optimization (mixed/random variables, nonlinear objectives), Additive Manufacturing (design, material behavior), and Smart Material Applications . Current projects integrate metamodeling (RBF, Kriging) with multi-objective optimization for manufacturing processes and structural systems. Publications and projects demonstrate expertise in: metal forming , composite materials , springback analysis , and breakwater design . He has supervised 13 PhD students since 1996, including international collaborations with Lebanese University and Northwestern Polytechnical University .

Sriram Sankaranarayananمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Formal Methods
• Robotics
• +۳ مورد دیگر

Sriram Sankaranarayanan is a Professor of Computer Science and the Associate Dean for Digital Education in the College of Engineering at the University of Colorado Boulder. He earned his PhD in Computer Science from Stanford University in 2005 under Zohar Manna and Henny Sipma. Prior to joining CU Boulder in 2009, he worked as a research staff member at NEC Laboratories America. His research focuses on formal methods for cyber-physical systems, including hybrid dynamical systems analysis, safety verification, and applications in robotics, medical devices (e.g., artificial pancreas systems), and human-autonomy interaction. He leads the Programming Languages & Verification group at CU Boulder and teaches courses in programming languages, algorithms, and control systems. Recent work emphasizes neural network-based control systems, robust safety guarantees, and anticipatory algorithms for stochastic games. His contributions span theoretical advancements (e.g., control barrier functions) and practical tools like the Sherlock verification framework. He has advised numerous PhD students, including Emily Jensen, Monal Narasimhamurthy, and Kandai Watanabe. Publications highlight innovations in physics-informed neural networks (PINNs), polyhedral control Lyapunov functions, and anticipate-act strategies for human-robot collaboration. Research spans domains from energy policy modeling to healthcare technology, reflecting his interdisciplinary approach to system-level challenges.

Florbela Alexandra Pires Fernandesمشاهده پروفایل

دانشیار

• Optimization
• Nonlinear Programming
• Nonconvex Optimization
• +۶ مورد دیگر

Florbela Alexandra Pires Fernandes serves as an Associate Professor at the Polytechnic Institute of Bragança since 1998, contributing to mathematics education and research. She holds a Bachelor's degree in Mathematics (Education) from the University of Coimbra, a Master's in Applied Mathematics, and a PhD in Sciences (Mathematics) from the University of Minho, establishing a strong foundation in theoretical and applied mathematics. Her educational background includes: Bachelor in Mathematics (Education), University of Coimbra MSc in Applied Mathematics, University of Minho PhD in Sciences (Mathematics), University of Minho Professor Fernandes' research centers on Optimization, specializing in algorithm development for nonlinear and nonconvex problems with mixed variables. Her work bridges theoretical mathematics with industrial applications, extending into machine learning, data analysis, and educational technology through the MathE platform. She actively promotes mathematics education through initiatives like mathematical games for student engagement and inclusive projects such as Eurekit for visually impaired learners. Analysis of her 61 publications (2023-2025) reveals strong interdisciplinary trends: optimization algorithms applied to waste management (hybrid fleet routing), healthcare (LiDAR-based rehabilitation and liver disease diagnosis), retail safety (occupational accident prediction), and educational technology (fuzzy clustering for student categorization in MathE). Her work consistently transforms theoretical algorithms into practical solutions across diverse sectors. She has coordinated or collaborated in multiple funded projects: Eurekit: Inclusive educational games for visually impaired and colorblind students e-nature: Environmental science education initiatives mathE: Intelligent mathematics learning and assessment platform SmilD: Educational technology development FIT4FoF: Workforce upskilling for factories of the future SmartHealth: Robotic systems for upper limb rehabilitation Professor Fernandes leads interdisciplinary teams connecting mathematics with engineering, healthcare, and education. Her MathE platform development involves computer scientists and educators, while SmartHealth collaborations include rehabilitation specialists and robotics engineers, demonstrating her ability to bridge theoretical research with real-world implementation through strategic partnerships.

• Control Systems
• Game Theory
• Robotics
• +۳ مورد دیگر

Filippo Fabiani is an Assistant Professor at the IMT School. His research focuses on control systems, game theory, and optimization, with applications to robotics, multi-agent systems, and nonlinear dynamics. He explores topics such as Nash equilibrium seeking in strategic environments, fault-tolerant control, and neural network-based system identification. His work combines theoretical advancements in distributed algorithms with practical implementations in aerospace and robotic systems. Notable areas include spacecraft proximity guidance, resilient control for nonlinear systems, and adaptive strategies in competitive multi-agent scenarios. He also investigates belief-sharing mechanisms and robust stabilization under uncertainty. Publications highlight contributions to generalized Nash games, distributed equilibrium-seeking algorithms, and model predictive control. Research spans both foundational theory and applied engineering solutions, emphasizing the interplay between strategic decision-making and control system design.

Sara Amarمشاهده پروفایل

استادیار

• Multi-Criteria Decision Making
• Operations Research
• Industry 5.0
• +۷ مورد دیگر

Dr. Sara Amar is an Assistant Professor of Industrial and System Engineering at Bowling Green State University (BGSU), part of the College of Technology, Architecture and Applied Engineering. She holds a Ph.D. in Industrial and Logistics Engineering and a Master's in Logistics and Transportation. Her research focuses on Multi-Criteria Decision Making, Operations Research, Industry 5.0, Sustainable Development, and Urban Logistics. Dr. Amar actively contributes to academic conferences as a reviewer and committee chair, emphasizing practical applications of theoretical frameworks in industrial and logistical challenges. Her educational background includes advanced degrees in logistics and engineering, complemented by a strong publication record spanning topics from facility layout optimization to emotional factors in supply chain digitalization. Research highlights include sustainable urban planning frameworks, emotional intelligence integration in decision-making models, and bi-criteria optimization approaches for industrial problems. Dr. Amar's work bridges theoretical models with real-world applications in transportation, energy systems, and socio-economic policy design. Her publications demonstrate a focus on interdisciplinary solutions, combining mathematical modeling with practical case studies. Notable contributions include studies on energy transportation cost optimization using nonlinear programming and interactive facility layout design methodologies. While no specific grants or awards are listed, her active conference participation underscores her engagement with the academic community.

Buser Sayمشاهده پروفایل

مدرس

• Sequential Decision Making
• Mathematical Optimization
• Machine Learning
• +۳ مورد دیگر

Dr. Buser Say is a Lecturer in the Department of Data Science & AI at Monash University, where he leads research at the intersection of sequential decision making, mathematical optimization, and machine learning. He also serves as Director of Student Engagement for the Faculty of Information Technology. His current projects include 'Blackbox Multi-Objective Optimization of Unknown Functions' and 'Human-in-the-Loop Microgrid Project'. Dr. Say develops algorithms for optimal planning with neural network transition models and functional selectivity in decision systems. He employs mixed-integer programming and high-dimensional optimization techniques.

Pooya Ronaghمشاهده پروفایل

عضو هیئت علمی

• Quantum Computation
• Quantum Algorithms
• Quantum Error Correction
• +۸ مورد دیگر

Pooya Ronagh is a Research Assistant Professor at the University of Waterloo, affiliated with the Department of Physics & Astronomy and the Institute for Quantum Computing (IQC). He also serves as a Scientific Lead at the Perimeter Institute Quantum Intelligence Lab (PIQuIL) and directs the Hardware Innovation Lab at 1QBit. His work bridges quantum computation, machine learning, and optimal control, focusing on quantum algorithms, error correction, and hybrid quantum-classical systems. Education: PhD in Mathematics (University of British Columbia, 2016), MSc in Mathematics (UBC, 2011), dual BSc in Mathematics and Computer Science (Sharif University of Technology, 2009). Awards include the Benjamin Franklin Fellowship (2009). Research Interests: Quantum algorithms for machine learning, reinforcement learning, fault-tolerant quantum architectures, cryogenic systems, and quantum control. He explores applications of quantum simulation to improve learning efficiency and robustness in AI systems. Recent work includes optimizing quantum error correction decoders, developing scalable superconducting architectures, and advancing neural network-based quantum state tomography. His contributions span theoretical frameworks (e.g., lattice surgery scheduling) and experimental methods (e.g., SFQ pulse control). Teaching: Courses like PHYS 490 (Machine Learning in Physics) emphasize practical coding and interdisciplinary projects. Grants and collaborations involve industry and academic partners in quantum hardware and software development. Labs: Hardware Innovation Lab (1QBit), IQC Quantum Control Group Future Work: Scaling quantum supercomputers, cryogenic neural decoders, quantum-enhanced generative AI