جست‌وجوی استاد و پژوهشگر

• Dynamical Systems
• Differential Equations
• Mathematical Analysis
• +۳ مورد دیگر

Luis Ángel Sánchez Pérez serves as a Professor at Spain's Polytechnic University of Cartagena, with a distinguished career in mathematical research spanning over a decade. His work primarily focuses on theoretical and applied aspects of dynamical systems and differential equations, contributing significantly to the understanding of nonlinear phenomena in mathematical modeling. His research interests center on dynamical systems theory, particularly monotone systems, periodic orbit analysis, and stability properties in nonlinear differential equations. He applies geometric and analytical methods to study convergence behavior, bifurcations, and orbital stability across diverse contexts including electrical circuits, biochemical oscillators, and generalized cone structures. His work bridges abstract mathematical theory with practical applications in engineering and biological systems. Publication analysis from 2000-2010 reveals consistent specialization in geometric approaches to dynamical systems, with recurring themes of monotonicity, stability criteria, and high-dimensional behavior. His research demonstrates particular expertise in adapting the Poincaré-Bendixson theorem to novel system classes, analyzing multi-equilibrium circuits like Chua's system, and developing convergence criteria for biological models including the Goodwin oscillator. The trajectory shows increasing sophistication in handling complex nonlinear interactions while maintaining rigorous mathematical foundations.

• Hybrid Systems
• Networked Control Systems
• Model Predictive Control (MPC)
• +۵ مورد دیگر

Prof. W.P.M.H. (Maurice) Heemels is a Full Professor at the Eindhoven University of Technology in the Mechanical Engineering department, leading the Control Systems Technology group. His work focuses on hybrid systems , networked control , and model predictive control (MPC) with applications in cyber-physical systems , precision agriculture , and cancer treatment optimization . PhD in Mathematics (1999) and MSc in Mathematics (1995) from TU/e Assistant Professor at TU/e Electrical Engineering (2000-2004) Research Fellow at Embedded Systems Institute (2004-2006) His research addresses resource-aware control strategies to replace traditional time-triggered systems with event-triggered schemes , enabling efficient use of computational and communication resources. Applications span automated driving , precision agriculture , thermal control in lithography , and nuclear fusion reactors . He has developed innovative hybrid integrator-gain systems (HIGS) and reset controllers to overcome limitations of linear time-invariant controllers. Model predictive control is a core methodology, applied to hyperthermia treatments, wafer scanner thermal control, and drone-based farming systems. His 2025 publications emphasize networked control for nuclear fusion, safety-critical MPC in autonomous vehicles, and data-driven control barrier functions for nonlinear systems. Key trends include hybrid systems theory , resource-aware control , and scalable optimization for large-scale applications. 2025: DISC PhD Award for Stefan Heijmans 2019: EECI European PhD Award for Victor Dolk 2017: Best Paper Award @ EBCCSP Conference 2014: Automatica Outstanding Service Award 2000: ASML-award for best fundamental PhD thesis He has supervised 88+ students and secured over 7 MEuro in research funding from NWO, EU, and industry. His Control Systems Technology group operates labs including the Automotive Engineering Science Laboratory and Robotics Laboratory , contributing to the UN Sustainable Development Goals for sustainable cities and climate action through cyber-physical systems.

Vera Roshchinaمشاهده پروفایل

دانشیار

• Convex Geometry
• Mathematical Optimization
• Nonsmooth Analysis
• +۳ مورد دیگر

Associate Professor Vera Roshchina is a mathematician at the University of New South Wales (UNSW) Sydney , affiliated with the College of Science and School of Mathematics & Statistics . Her research focuses on convex geometry , mathematical optimization , and nonsmooth analysis , with significant contributions to projection methods, hyperbolicity cones, and Chebyshev approximation. Her recent work explores constructing spectrahedra with prescribed facial dimensions (2025) optimal camouflaging in billiards (2025) convergence of projection algorithms (2024) amenability of hyperbolicity cones (2024) topological properties of convex sets (2023) She is supported by multiple ARC Discovery grants and received the Christopher Heyde Medal (2021) . Her teaching includes courses in Mathematical Optimization and Calculus . She organized and participated in international research programs like MoCaO lectures (2024) and the WODCA2025 workshop , collaborating with researchers globally. Her publications span journals in optimization, nonlinear analysis, and dynamical systems.

Andreas Waechterمشاهده پروفایل

استاد

• Large-scale nonlinear optimization
• Mixed-integer nonlinear optimization
• Software implementation of numerical algorithms
• +۴ مورد دیگر

Andreas Waechter is a Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University's McCormick School of Engineering. He holds a Ph.D. in Chemical Engineering from Carnegie Mellon University (2002) and an M.S. in Mathematics from the University of Cologne (1997). Before joining Northwestern in 2011, he was a Research Staff Member at IBM Research (Yorktown Heights, NY). His research focuses on developing numerical algorithms for nonlinear continuous and mixed-integer optimization, with applications in power systems, scientific computing, and sustainability. Key contributions include the open-source solver Ipopt (winner of the 2011 Wilkinson Prize and 2009 INFORMS Computing Society Prize), and the Bonmin and Couenne solvers for mixed-integer optimization. Waechter has received numerous awards, including the 2017 Charles Broyden Prize and the 2020 ARPA-E Grid Optimization Competition award. His work emphasizes both theoretical advancements and practical software implementation, with applications ranging from power grid optimization to machine learning. Education: Ph.D., Chemical Engineering, Carnegie Mellon University, 2002 M.S., Mathematics, University of Cologne, 1997 His research interests span optimization algorithms, algorithmic differentiation, and interdisciplinary applications. He has advised over a dozen graduate students and collaborates with industry and academic institutions globally. Waechter's software packages are widely used in academia and industry, reflecting his commitment to open-source computational tools.

• Artificial Intelligence
• Machine Learning
• Predictive Maintenance
• +۵ مورد دیگر

Dr. Mosayeb Davoudi Kashkouli serves as a Lecturer in Engineering Technologies at the University of the West of England, affiliated with the Department of Engineering Design and Mathematics within the Faculty of Environment and Technology. His interdisciplinary work bridges artificial intelligence, mechanical engineering, and biomedical innovation through active collaborations with Airbus UK, Bristol Robotic Laboratory, and healthcare manufacturing networks. His educational foundation includes: PhD in Mechanical Engineering Master's in Data Science Research focuses on AI-driven engineering solutions with emphasis on: Predictive maintenance systems using machine learning for Remaining Useful Life (RUL) forecasting Biomedical applications including nano/micro materials design for wound care and prosthetics via 3D/4D printing Computer vision techniques for real-time object detection and video inpainting Redistributed manufacturing in healthcare ecosystems Publication trends reveal a strategic pivot from mechanical engineering (2014-2019 pressure vessel creep analysis) to contemporary AI/computer vision research, exemplified by 2024 work on synthetic data for low-resolution object detection. This evolution demonstrates increasing focus on machine learning applications for industrial and healthcare challenges. Current funding includes leadership of a New Starter Researcher Development Scheme project (2023-2026) on predictive maintenance. Key collaborations span: Airbus UK for industrial applications Big Data Enterprise and Artificial Intelligence Laboratory for algorithm development Redistributed Manufacturing in Healthcare Network (RiHN) Bristol Robotic Laboratory (BRL) for robotics integration He actively contributes to the Big Data Enterprise and Artificial Intelligence Laboratory and Bristol Robotic Laboratory, driving projects that merge robotics, AI, and healthcare innovation through interdisciplinary team structures focused on intelligent manufacturing systems.

• Quantum Computing Optimization
• Interior Point Methods
• Semidefinite Optimization
• +۱۱ مورد دیگر

Professor Tamás Terlaky holds the Alcoa Endowed Chair at Lehigh University 's P.C. Rossin College of Engineering and Applied Science , directing the Quantum Computing and Optimization Laboratory (QCOL) . He maintains Adjunct Professor roles at McMaster University and University of Pannonia , and serves as Visiting Professor at Strathclyde University . Ph.D. & M.Sc. from Eötvös University, Budapest Doctor of Academy of Sciences (Hungary) Habilitation from University of Pannonia Research Interests span Quantum Computing Optimization , Interior Point Methods , High-Performance Computational Optimization , Mathematical Modeling , and Medical Engineering Applications . Specific foci include Proton Therapy Treatment Optimization , Nuclear Reactor Core Reloading , and Service System Optimization . Recent Publications demonstrate expertise in Quantum Interior Point Methods , Quantum Linear System Algorithms , and Combinatorial Optimization , with applications to Medical Physics , Structural Engineering , and Quantum Software Design . Scientific Awards : Fellow of Fields Institute , INFORMS , SIAM , IFORS , and Canadian Academy of Engineering INFORMS Wagner Prize recipient IISE Outstanding Innovation in Service Science award MITACS Mentorship Award Teaching includes courses on Conic Optimization , Interior Point Methods , and Optimization Methods and Software . Currently leading a $2.1M DARPA grant for Quantum Computing Optimization research.

Bingcong Liمشاهده پروفایل

پژوهشگر

• Machine Learning
• Optimization
• Signal Processing
• +۳ مورد دیگر

Bingcong Li is a postdoctoral researcher at ETH Zurich collaborating with Prof. Niao He and the ODI group. Previously, they completed doctoral studies at the University of Minnesota under Prof. Georgios B. Giannakis, followed by industry experience focused on large language models (LLMs). Education includes a PhD from the University of Minnesota under Prof. Georgios B. Giannakis. Research centers on making computation efficient, accessible, and affordable across heterogeneous resources—from GPU clusters to consumer hardware—through interdisciplinary approaches combining deep learning, optimization, and signal processing. Key research areas address foundational computing architectures, large-scale system sustainability, and personalized AI access. Their work develops theoretically grounded methods for explainable systems, with recent focus on LLM fine-tuning efficiency. Publication trends show consistent contributions to top conferences (NeurIPS, ICML, ICLR) with emphasis on optimization techniques for resource-constrained LLM deployment. Their advising and grant activities aren't explicitly detailed, though they actively participate in academic service through conference talks (EUROPT 2025, ICASSP 2025) and co-organizing events like the Efficient LLMs Fine-tuning Track at AI+X Summit. Lab affiliation centers on ETH Zurich's ODI group under Prof. Niao He, focusing on optimization-driven AI solutions.

• Space Antenna Technology
• Defence Antenna Systems
• Satellite and Space Communication
• +۵ مورد دیگر

Foez Ahmed is a Visiting Fellow and Research Fellow at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). He holds a B.Sc. (Hons.) and M.Sc. in Information and Communication Engineering from the University of Rajshahi, Bangladesh, and an M.Eng. in Electrical and Computer Engineering from the South China University of Technology. His academic appointments include prior roles as Assistant Professor at RU, Lecturer at Northern University Bangladesh, and King Khalid University. His research specializes in cutting-edge antenna technologies, with emphasis on: Space and defence antenna systems Metasurface-driven beam-steering mechanisms Satellite-on-the-move terminals 3D-printable RF structures for high-efficiency applications Recent publications (2022-2025) demonstrate a consistent focus on metasurface innovation for satellite communications, featuring dielectric/metallic metastructures, phase-correction techniques, and additive manufacturing solutions. He has received numerous scientific awards, including: Commonwealth iRTP Scholarship & International Research Scholarship Chinese Government Scholarship & UTS Gold Medal First Prize in CSIRO Bushfire Challenge and IEEE presentation awards Faculty-wide research grants and travel funds Ahmed leads a $1.1 million NSW government-funded project developing satellite terminal antenna technology. He has taught courses including Electronics and Circuits (UTS) and Introduction to Engineering (Macquarie University).

• Continuous Optimization
• Numerical Methods
• Convex Optimization
• +۱۲ مورد دیگر

Mirai Tanaka is an Associate Professor at The Institute of Statistical Mathematics (ISM) in Tachikawa, Tokyo, where they lead research in optimization theory and its applications. Currently affiliated with the Statistical Decision-Making Group in the Department of Fundamental Statistical Mathematics, Tanaka also holds concurrent appointments at the Risk Analysis Research Center at ISM and the Statistical Science Program at The Graduate University for Advanced Studies. Previously, Tanaka served as an Assistant Professor at ISM (2017-2020) and at Tokyo University of Science (2014-2017). Tanaka's research focuses on continuous optimization, numerical methods, and their applications across diverse fields. Their work spans convex and non-convex optimization, proximal algorithms, DC programming, and mathematical modeling for real-world problems. Specific interests include gradient methods, subgradient methods, Bregman proximal algorithms, Newton methods, and interior point methods. Tanaka has applied these techniques to problems in machine learning, data analysis, signal and image processing, control engineering, maritime affairs, supply chain management, forest science, and polymer chemistry. Their recent publications reveal a strong emphasis on developing efficient algorithms for challenging optimization problems, with particular attention to convergence properties and practical implementations. Tanaka's work bridges theoretical developments with real-world applications, as evidenced by publications spanning pure optimization theory to applied problems in various scientific domains. 12th Research Encouragement Award, Operations Research Society of Japan (2022) Best Paper Award, 15th Congress of the Asian Network for Quality (2017) Best Paper Award, 14th Congress of the Asian Network for Quality (2016) Teshima Seiichi Memorial Research Award (Doctoral Dissertation Award), Tokyo Institute of Technology (2015) Tanaka actively supervises graduate students at The Graduate University for Advanced Studies and has received multiple research grants from the Japan Society for the Promotion of Science (JSPS), including current funding for projects on forest pest control and practical aerial image processing. They have organized numerous workshops including the ZIB-IMI-ISM-NUS-RIKEN-MODAL-NHR Workshop series and the Continuous Optimization and Related Fields Summer School.

Philipp Hungerländerمشاهده پروفایل

دانشیار

• semidefinite optimization
• conic optimization
• polynomial optimization
• +۴ مورد دیگر

Philipp Hungerländer is an Associate Professor at the Institute of Mathematics, University of Klagenfurt. He is a member of the combinatorial optimization working group led by Prof. Franz Rendl, focusing on advanced optimization techniques for real-world industrial applications. Research Interests: His work spans three core areas: (1) semidefinite, conic, and polynomial optimization for nonlinear discrete problems, (2) quadratic programming and active-set algorithms for convex/nonconvex models, and (3) exact and heuristic methods for combinatorial optimization in routing and scheduling. Additionally, he explores game theory and dynamic games. Recent Publications: His 15 most recent articles reflect expertise in railway logistics, facility layout, home delivery services, and medical pandemic response. Topics include integrated freight routing, dial-a-ride optimization, and applications of mixed-integer programming. Contact: Email: Philipp.Hungerlaender@aau.at

Lennart Binkowskiمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Quantum Algorithms
• Theoretical Physics
• +۴ مورد دیگر

Lennart Binkowski is a doctoral candidate and scientific staff member at the Institute of Theoretical Physics , part of the Faculty of Mathematics and Physics at Leibniz University Hannover. His research focuses on quantum computing, particularly quantum algorithms and combinatorial optimization. University: Leibniz University Hannover School: Faculty of Mathematics and Physics Department: Institute of Theoretical Physics Email: lennart.binkowski@itp.uni-hannover.de Lennart's research interests span quantum algorithms, quantum walks, and optimization frameworks. His work explores quantum programming languages, Pauli transfer matrices, and hybrid quantum-classical systems. Recent publications highlight advancements in QAOA, quantum permutation generation, and tensor network applications. Lennart's 15 most recent articles focus on quantum computing trends, including algorithm design, constraint handling, and tensor structures. No scientific awards are mentioned in the provided data. Contact details: Schneiderberg 32, 30167 Hanover, Germany (Building 3702, Room 013).

• Quantum Physics
• Quantum Computing
• Optimization
• +۳ مورد دیگر

Gabriele Uchida is a Professor in the Research Group Education, Didactics and Entertainment Computing at the Faculty of Computer Science. Their work spans quantum physics, optimization theory, and education technology. Notable contributions include studies on entanglement in quantum systems and copositive optimization. Uchida has organized academic events like the Informatiktag series and contributed to conferences on mathematical optimization. Research interests focus on quantum entanglement mechanisms, algorithmic optimization, and integrating IT into educational practices. Their publications highlight interdisciplinary approaches, blending theoretical physics with computer science. Publications analyze quantum dots, copositive matrices, and blended learning strategies, with citations in top journals. Activities include academic event organization and peer-reviewed presentations on topics like conic optimization.

• Thermal Engineering
• Materials Science
• Computational Modeling
• +۳ مورد دیگر

Jiawei Hu is a Research Fellow at the University of Surrey's School of Chemistry and Chemical Engineering, specializing in computational modeling and thermal engineering. Their work focuses on advanced energy storage systems, granular flow dynamics, and electrostatic interactions in particulate systems. Research interests include thermal management of all-solid-state batteries, heat conduction in composite materials, and discrete element method (DEM) modeling for granular and pharmaceutical systems. Recent studies explore the impact of microstructural parameters on thermal conductivity, as well as electrostatic phenomena in silo and rotating drum environments. Publications highlight trends in interdisciplinary research at the intersection of energy storage, materials science, and computational physics. Key contributions include DEM-CFD coupled models for particle systems and investigations into friction-induced heating mechanisms. No academic awards or grants are explicitly listed in the provided materials. Advising records are unavailable, though affiliations with Surrey's Chemistry and Chemical Engineering School suggest involvement in collaborative research initiatives.

• Antenna Design
• Microwave Engineering
• Electromagnetic Theory
• +۳ مورد دیگر

Chunxu Mao is a Senior Research Fellow at the University of Surrey, specializing in antenna design and microwave engineering. His work focuses on reconfigurable antennas, millimeter-wave applications, and wearable technology. Key research areas include polarization control, wideband systems, and beam-scanning antennas for 5G and IoT applications. Collaborations span institutions globally, with a strong emphasis on practical implementations for wireless communication systems. Education: Not explicitly stated in provided texts. Affiliations: University of Surrey (Senior Research Fellow). Key Projects: Development of leaky-wave antennas, dual-polarized systems, and textile-based wearable antennas. Research Interests: Antenna reconfiguration, metamaterials, filtering antennas, and miniaturized designs for 5G, UAVs, and vehicular systems. His work addresses challenges in bandwidth enhancement, radiation pattern control, and low-profile implementations through innovative structural designs and simulation techniques. Publications: Over 20 peer-reviewed articles in top journals like IEEE Transactions on Antennas and Propagation, focusing on antenna array design, polarization engineering, and millimeter-wave systems. Recent contributions include quad-beam leaky-wave antennas and compact dual-band filtennas for vehicle applications. Labs/Teams: Collaborates with interdisciplinary teams on advanced antenna systems for wearable devices, satellite communication, and IoT infrastructure.

Jiakai Luمشاهده پروفایل

دانشیار

• Food Process Engineering
• Modelling and Numerical Simulation
• Computational Fluid Dynamics
• +۵ مورد دیگر

Jiakai Lu is an Associate Professor in the Department of Food Science at the University of Massachusetts Amherst. His research focuses on transport phenomena in food and biomaterial processing, integrating food process engineering, fluid mechanics, and applied mathematics to enhance process sustainability and improve food quality and safety. Key areas include interfacial dynamics in food dispersions, fouling layer mechanisms in dairy processing, and pharmacokinetic modeling of drug-bacteria interactions. His work addresses critical challenges such as stabilizing food dispersions (foams, gels, emulsions) through surfactant and rheological studies, developing computational tools for fouling layer formation and removal in heat exchangers, and modeling microbiome impacts on drug metabolism using PBPK models. He has contributed to over a dozen peer-reviewed publications in high-impact journals like Physics of Fluids , Scientific Reports , and AICHE Journal . Research Highlights: Mechanistic understanding of interfacial dynamics in food dispersions Fouling layer growth and removal via jet impingement and microbubble impact PharmacoMicrobiomics of narrow therapeutic index drugs Dr. Lu has received the 2010 First Place Food Engineering Division Paper Competition from the Institute of Food Technologists. His lab actively collaborates across disciplines to bridge fundamental science with industrial applications in food processing and biotechnology.