جست‌وجوی استاد و پژوهشگر

• 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

Luigi Glielmoمشاهده پروفایل

استاد

• Automatic Control
• Model Predictive Control
• Renewable Energy Systems
• +۵ مورد دیگر

Luigi Glielmo is a Professor of Automatic Control at the University of Sannio in Benevento, Italy. He holds a Master's and PhD in Electronic Engineering and Automatic Control from the University of Naples Federico II. Previously, he taught at the University of Palermo before returning to Naples. His academic leadership roles include Head of the Department of Engineering at University of Sannio (2001–2007), Rector’s Delegate for Technology Transfer (2009–2019), and Coordinator of PhD programs in Information Engineering and Information Technologies for Engineering. Research interests focus on automatic control engineering, including model predictive control, renewable energy systems, smart grids, robotics, biomedical applications (e.g., deep brain stimulation modeling), satellite autonomy, and Boolean control networks. He founded the GRACE research group and has authored over 190 papers, two books, and holds two patents. He is a Senior Member of IEEE, serves on the editorial board of IEEE Control Systems Letters, and chairs the IEEE Control Systems Society Technical Committee on Automotive Controls. Leadership roles include General Co-Chair of the 2019 European Control Conference and ordinary member of IFAC’s Conference Board. His work bridges theoretical advancements with practical applications in energy systems, robotics, and industrial automation.

• Numerical Optimization
• Mixed-Integer Nonlinear Programming
• Global Optimization
• +۱۴ مورد دیگر

Ruth Misener is a Professor in the Department of Computing at Imperial College London, where she leads the Computational Optimization Group and holds the BASF/RAEng Research Chair in Data-Driven Optimization (2022–2027). She is affiliated with the Faculty of Engineering and contributes to interdisciplinary research institutes including the Data Science Institute, the Institute for Molecular Science and Engineering, and the Sargent Centre for Process Systems Engineering. Her research lies at the intersection of numerical optimization, operations research, and machine learning, with applications in chemical engineering, bioprocess optimization, energy systems, and industrial scheduling. She develops global optimization algorithms for mixed-integer nonlinear programs (MINLP), focusing on real-world challenges such as heat recovery network design, petrochemical process optimization, and robust bioreactor operation. A key innovation is her work on optimizing over machine learning surrogates, including tree ensembles and neural networks, enabling data-driven decision-making under uncertainty. Her recent publications demonstrate a strong trend toward integrating Bayesian optimization with active learning, explainable AI, and industrial applications, particularly in collaboration with BASF, Royal Mail, and Eli Lilly. She develops and maintains open-source optimization tools such as ROmodel, OMLT, and ENTMOOT, which are publicly available on GitHub. STEM for Britain acceptance Runner-Up Presentation Award at PSE@ResearchDayUK Best Quality Poster to Simon Olofsson 1st Poster Prize at UK/Ireland Annual Meeting of the Society for Industrial & Applied Mathematics (2018) 2nd Poster Prize at Centre for Process Systems Engineering Industrial Consortium Meeting (2017) 1st Poster Prize at 2nd PSE@ResearchDayUK (2017) 2nd Presentation Prize at Department of Computing Research Associate Symposium (2017) Runner-Up for May Hicks Award (via student Natasha Page) Ruth supervises a dynamic research team and has examined and mentored numerous PhD students, including Jean Kossaifi, Robert Walecki, Alexander Thebelt, and Toby Boyne. She leads major research grants, including the BASF/RAEng Research Chair and the IConIC Prosperity Partnership, and collaborates with industry partners to advance continuous manufacturing and data-driven process optimization. Her team actively disseminates work through open-access publications, video presentations, and social media.

Evrim Dalkiranمشاهده پروفایل

دانشیار

• Global Optimization
• Reformulation-Linearization Technique (RLT)
• Mixed-integer Nonlinear Programming (MINLP)
• +۹ مورد دیگر

Dr. Evrim Dalkiran is an Associate Professor in the Department of Industrial and Systems Engineering at Wayne State University's College of Engineering. She holds a Ph.D. in Industrial and Systems Engineering from Virginia Tech (2011), and B.S./M.S. from Bogazici University (2003, 2006). Her work focuses on global optimization and decision analysis with applications in healthcare operations and supply chain management. B.S., Industrial Engineering, Bogazici University, Turkey M.S., Industrial Engineering, Bogazici University, Turkey Ph.D., Industrial and Systems Engineering, Virginia Tech Her research spans Global Optimization , Reformulation-Linearization Technique , Mixed-Integer Programming , and Multi-Objective Optimization , with application domains in Healthcare Operations , Emergency Patient Flow , Supply Chain Management , and Diabetes Risk Modeling . Current research includes real-time coordination tools for emergency departments and inverse optimization models. Her publications demonstrate expertise in polynomial programming , RLT implementations , and healthcare logistics , with recent work on automotive sustainability and smart grid allocation . Articles span journals like European Journal of Operational Research and Operations Research . Best Paper Award, Journal of Global Optimization, 2012 Outstanding Faculty Award, WSU, 2016 Pritsker Dissertation Award Finalist, 2012 IIE Student Paper Competition Advisor, multiple awards As faculty advisor, she mentors students in projects related to emergency department optimization and supply chain modeling . Her grant history includes multiple Veterans Administration projects on patient flow and Goodyear-funded supply chain optimization. She teaches advanced optimization courses and maintains professional affiliations with INFORMS and Mathematical Optimization Society.

• Discrete Optimization
• Non-Convex Optimization
• Operational Research
• +۳ مورد دیگر

Akshay Gupte is a Professor in the School of Mathematics at the University of Edinburgh, specializing in Optimization and Operational Research. His research focuses on mathematical and algorithmic aspects of discrete and non-convex optimization, with applications in engineering, finance, and decision-making systems. He holds a PhD in Operational Research from Georgia Tech and teaches advanced courses such as Optimization Methods in Finance for MSc students. Education: BEng in Industrial Engineering from the University of Bombay MSc in Operational Research from the University of Arizona PhD in Operational Research from Georgia Tech Research Interests: Optimization problems involving discrete choices and non-convexity, with a focus on algorithm design and computational strategies. His work bridges applied mathematics, computer science, and engineering, addressing challenges in logistics, finance, and large-scale decision systems. Articles Trends: Recent publications emphasize algorithmic advancements in non-convex optimization (e.g., spatial branch-and-bound, semidefinite programming), multi-objective decision-making (e.g., biobjective programming), and stochastic frameworks for real-world problems like facility location and home service scheduling. Awards & Grants: No specific awards listed, but his research has been supported by collaborative grants in mixed-integer programming and optimization algorithms. He advises students through his teaching and research collaborations within the Optimization Group at the University of Edinburgh.

Ricardo G. Sanfeliceمشاهده پروفایل

استاد

• Hybrid Dynamical Systems
• Nonlinear Control
• Robust Control
• +۹ مورد دیگر

Ricardo G. Sanfelice is Professor and Chair of the Department of Electrical and Computer Engineering at the University of California, Santa Cruz (UCSC), within the Baskin School of Engineering. He is also Director of the Cyber-Physical Systems Research Center and the CITRIS Aviation Initiative. Education: Ph.D., Electrical and Computer Engineering, University of California, Santa Barbara, 2007 M.S., Electrical and Computer Engineering, University of California, Santa Barbara, 2004 B.S., Electronic Engineering, Universidad Nacional de Mar del Plata, Argentina, 2001 His research focuses on modeling, stability, robust control, and observer design for nonlinear and hybrid systems, with applications in robotics, aerospace, power systems, and biological systems. He leads the Hybrid Systems Lab at UCSC and has contributed significantly to the theoretical foundations and practical implementations of hybrid feedback control and cyber-physical systems. The most recent publications highlight a strong trend toward computation-aware control, hybrid model predictive control, and set-valued methods for safety-critical systems. His work bridges theoretical rigor with real-world applications, particularly in autonomous vehicles and networked control systems. Scientific Awards and Honors: Fellow of IEEE ACM Test-of-Time Award (HSCC Conference) SIAM Control and Systems Theory Prize NSF CAREER Award Air Force Young Investigator Award (YIP) IEEE Control Systems Magazine Outstanding Paper Award Educator of the Year for Higher Education Multiple plenary and semiplenary speaking invitations Blavatnik National Award Campus Nominee ASEE Air Force Summer Faculty Fellow Senior Member of IEEE Prof. Sanfelice has advised several graduate students, including Jun Chai and Dawn Hustigs-Schultz, and has been involved in significant research grants and initiatives such as the AFOSR Center of Excellence and CITRIS Aviation Prize. He is Associate Editor for Automatica and has led the IEEE Technical Committee on Hybrid Systems. He leads the Hybrid Systems Lab at UCSC, which focuses on theoretical and applied aspects of hybrid dynamical systems, including simulation tools like SHARC (Simulator for Hardware Architecture and Real-time Control).

• Operations Research
• Combinatorial Optimization
• Bilevel Optimization
• +۶ مورد دیگر

Ivana Ljubic is a Full Professor in Operations Research at ESSEC Business School, specializing in combinatorial optimization, bilevel optimization, and network design with applications in telecommunications, logistics, and bioinformatics. She holds a PhD in Computer Science from TU Wien (2004) and a Habilitation from the University of Vienna (2013). Editorial roles: Associate Editor for Operations Research , Transportation Science , and Networks Professional leadership: Chair of INFORMS Telecommunication & Network Analytics Section Her research focuses on mixed-integer programming, metaheuristics, and exact algorithms for problems like Steiner trees, regenerator location, and capacitated vertex separators. Recent work includes applications in community energy storage, social media influence maximization, and sustainable last-mile delivery. She has received multiple awards, including the Glover-Klingman Prize (2021) and Marguerite Frank Award (2022). Her publications span leading journals like Management Science , Operations Research , and Mathematical Programming , with over 70 articles to date.

• Mixed-Integer Nonlinear Programming (MINLP)
• Global Optimization
• Chemical Process Optimization
• +۳ مورد دیگر

Tapio Westerlund is a Professor in Mathematics at Åbo Akademi University's Faculty of Science and Engineering. His research focuses on mixed-integer nonlinear programming (MINLP), convex optimization, and nonsmooth optimization techniques, with applications in chemical process engineering and environmental science. Key Research Areas: MINLP, global optimization, supporting hyperplane methods, and limestone dissolution modeling. Notable Contributions: Development of the Supporting Hyperplane Optimization Toolkit and reformulation frameworks for nonconvex MINLP problems. Collaborations: Active in interdisciplinary research networks with external collaborations across countries. His recent publications emphasize convex MINLP algorithms, hyperplane techniques, and applications to wet flue gas desulfurization. While no specific awards or students are listed in the provided data, his citations and Mendeley readership indicate significant academic impact.

• Sustainable Energy Systems
• Mathematical Optimization
• Industrial Process Engineering
• +۳ مورد دیگر

Frank Pettersson is a Senior Lecturer at the Faculty of Natural Sciences and Engineering, Department of Process and Systems Engineering, Åbo Akademi University. His research aligns with UN Sustainable Development Goals (SDGs), focusing on sustainable energy systems and industrial process optimization through mathematical modeling. Expertise Areas: Mathematical Optimization, Hydrogen-Based Steelmaking, Biogas Digestate Recycling, Energy Storage Systems, Gas Distribution Networks, Blast Furnace Efficiency His recent work analyzes hydrogen transition in steel plants, water scarcity in power sectors, and nutrient recycling in biogas systems. Key methodologies include Mixed-Integer Linear Programming (MILP) and systems engineering approaches. Academic supervision spans Energy Technology diploma theses (2013–2017) and ongoing Master’s student mentorship (2025). While no specific scientific awards are listed, his publications demonstrate impact in sustainable industrial solutions and energy systems.