جست‌وجوی استاد و پژوهشگر

Kadir Sarıözمشاهده پروفایل

استاد

• Naval Architecture
• Ocean Engineering
• Seakeeping Performance
• +۳ مورد دیگر

Professor Kadir Sarıöz is a full-time faculty member at Istanbul Technical University in the Department of Shipbuilding and Ocean Engineering . His career spans over three decades of research and teaching in naval architecture and ocean engineering, focusing on seakeeping, ship maneuvering, hull-form optimization, and hydrodynamic simulation. Research Interests Professor Sarıöz’s work revolves around the hydrodynamic performance of marine vehicles. His investigations include: Seakeeping behavior of high-speed and conventional displacement hulls Experimental and computational ship maneuvering in calm water and waves Optimization algorithms for hull-form and propeller design under mission-specific constraints Dynamic positioning capability analysis under realistic environmental loads Simulation-based routing of large tankers through restricted waterways such as the Istanbul Strait Recent Projects 2021 – 2023: “Refakat Römorkörü Performansının Çok Serbestlik Dereceli Deneysel ve Hesaplamalı Analizi” (Revolving Fund, Principal Investigator) 2020: “Shell Antalya Terminali B şamandıra sistemindeki boru hattının tadilatı incelemesi” (Revolving Fund, Principal Investigator) Publication Trends Between 1990 and 2025, Professor Sarıöz has authored or co-authored more than 30 peer-reviewed journal and conference papers. Early works concentrated on practical seakeeping criteria and automated hull fairing, while recent contributions emphasize system-based maneuvering prediction, multi-objective optimization of naval combatant hulls, and environmentally driven dynamic positioning analyses. A clear progression from empirical and semi-empirical methods to high-fidelity CFD and experimental validation is evident. Laboratory & Facilities His research is supported by the university’s towing tank and planar motion mechanism facilities, equipped with modern motion controllers and servo-motor systems enabling precise captive maneuvering tests.

Triantafyllou Savvasمشاهده پروفایل

استادیار

• Computational Mechanics
• Structural Engineering
• Fracture Mechanics
• +۵ مورد دیگر

Triantafyllou Savvas serves as an Assistant Professor in the Department of Structural Engineering at the School of Civil Engineering, National Technical University of Athens (NTUA), with his faculty appointment documented since October 2020. His academic work is centered within one of Greece's premier engineering institutions, contributing to both advanced structural analysis education and cutting-edge computational research. Professor Savvas's research program focuses on computational structural mechanics with emphasis on developing advanced numerical methods for complex engineering challenges. His expertise spans material point methods for contact and fracture problems, wave-structure interaction phenomena (particularly for dams and flexible structures), vibroacoustics in porous media, and the mechanical behavior of textile reinforced mortar (TRM) systems for masonry strengthening. His work bridges theoretical computational advances with practical applications in infrastructure resilience against extreme events like tsunamis and earthquakes. Analysis of his recent publications (2021-2025) reveals a cohesive research trajectory centered on computational innovation: he has pioneered high-fidelity material point formulations for contact mechanics, developed multiscale virtual element methods for poroelastic media, established empirical models for TRM-masonry interfaces, and explored machine learning integration in topology optimization. His work consistently addresses critical gaps in simulating dynamic structural failures and wave impacts. Scientific Awards: No scientific awards were documented in the provided source materials. Advising and Grants: While the source materials do not specify current students or grant awards, Professor Savvas's extensive publication record across high-impact journals indicates active graduate research supervision and likely involvement in competitive research funding. His collaborative work with institutions like NTUA's Department of Structural Engineering suggests participation in national and international research consortia focused on computational mechanics and structural safety.

• Computational Fluid Dynamics
• Aerodynamic Design
• Ship Hull Reconstruction
• +۴ مورد دیگر

Nikolos Ioannis serves as a Professor at the School of Production Engineering and Management, Technical University of Crete, currently on leave but maintaining active research status. His work spans computational fluid dynamics, aerodynamics, and marine engineering within the Department of Production Engineering and Management. His primary research focuses on computational fluid dynamics with emphasis on ship hull reconstruction from 2D drawings, hypersonic flow simulation, and wind turbine optimization. Recent publications demonstrate expertise in geometric modeling , rarefied gas dynamics , and renewable energy systems . The 2025-2020 article portfolio reveals consistent contributions to naval architecture, aerodynamic shape optimization, and laser-matter interactions with strong methodological focus on B-spline functions, DSMC methods, and differential evolution algorithms. Professor Ioannis maintains an active email contact ( inikolos@tuc.gr ) and office location at D4.107 in the MPD Building. His work shows significant interdisciplinary connections between production engineering, computational physics, and marine applications with particular strength in translating theoretical models to practical engineering solutions.

Zbyněk ŠÍRمشاهده پروفایل

دانشیار

• Computer-Aided Geometric Design (CAGD)
• Differential Geometry
• History of Geometry
• +۳ مورد دیگر

Zbyněk ŠÍR is an Associate Professor at the Mathematical Institute within the Faculty of Mathematics and Physics at Charles University in Prague . He specializes in Computer-Aided Geometric Design (CAGD) , Differential Geometry , and the History of Geometry , with a focus on Pythagorean Hodograph curves and their applications in geometric modeling. Education: 1989: Graduated from Gymnázium J. K. Tyla, Hradec Králové 1993: DEA (Diplôme d'Études Approfondies) in Algebra and Geometry, University Pierre et Marie Curie (Paris VI) 1995: Master's in Mathematics (Riemannian Geometry, Representation Theory), Charles University 2002: PhD in Mathematics (History of French Geometry), Charles University & Université Pierre et Marie Curie 2012: Habilitation in Mathematics (Geometry and Topology), Charles University His research spans theoretical and applied geometry, including Pythagorean Hodograph curves , rational curves , and historical mathematical texts . Recent work focuses on rotation-minimizing motions , framing motions , and complex quaternions for minimal surfaces. Collaborations with researchers like Carlotta Giannelli, Lucia Sacco, and Bert Jüttler highlight interdisciplinary applications in robotics, aerospace, and computational geometry. ŠÍR teaches courses in Geometric Modeling and Mathematical Education , emphasizing the use of tools like Mathematica for visualizing curves, surfaces, and geometric transformations. His teaching integrates theoretical concepts (e.g., Frenet frames, projective geometry) with practical applications (e.g., CNC manufacturing, 3D reconstruction).

Martin Kellerمشاهده پروفایل

استاد

• Control Engineering
• Automated Driving Systems
• Model Predictive Control
• +۴ مورد دیگر

Prof. Dr.-Ing. Martin Keller is a Professor of Control Engineering at the Department of Electrical Engineering & Information Technology, South Westphalia University of Applied Sciences in Hagen, Germany. He leads research in advanced control systems with a specialization in automotive applications and automated driving technologies. His academic leadership includes directing the Laboratory for Control Engineering where practical courses, project work, and research activities are conducted. Education: Diploma in Electrical Engineering from TU Dortmund (2011), PhD in Control Systems Engineering from TU Dortmund (2017) Professional Experience: Algorithm Development Engineer (2017-2019) and Team Lead (2019-2022) at ZF Group before transitioning to academia Teaching Responsibilities: Courses in Control Engineering 1/2, Medical Control Systems, and Advanced Control Systems Professor Keller's research centers on automated driving systems with emphasis on trajectory planning, collision avoidance, and vehicle guidance algorithms. His work bridges theoretical control concepts with practical automotive implementations, particularly focusing on model predictive control frameworks for real-time applications. The research group develops algorithms for maneuver decision-making, trajectory planning, and tracking control essential for autonomous vehicle functions. Analysis of his 15 most recent publications reveals strong concentration in automated driving control systems , with 80% of works published between 2018-2021 focusing on trajectory optimization, collision avoidance, and model predictive control applications. Key research themes include sampling-based planning methods, environment modeling for optimization, and real-time capable control architectures for lateral vehicle guidance. His scientific contributions appear primarily in IEEE conferences and automotive engineering journals, with notable publications in IEEE Transactions on Intelligent Vehicles and IEEE Intelligent Transportation Systems Conference proceedings. While no specific awards are listed in the provided materials, his consistent publication record in top-tier venues demonstrates significant scholarly impact. Professor Keller actively supervises project work and final theses through the Control Engineering Laboratory, where students engage in hands-on development of control systems. His industry experience at ZF Group informs practical research directions focused on implementable solutions for automotive applications. The laboratory facilities at Haldener Str. 182 serve as the operational base for both teaching and research activities.

• Structural Mechanics
• Reinforced Concrete Structures
• Numerical Modeling
• +۳ مورد دیگر

Erol Lale is a Lecturer in the Civil Engineering Department at Istanbul Technical University, specializing in Structural Mechanics, Reinforced Concrete Structures, and Numerical Modeling. He holds a PhD in Structural Engineering from the same institution, with prior academic roles including Research Assistant since 2005. His research focuses on advanced numerical techniques such as Lattice Discrete Particle Modeling (LDPM), Isogeometric Analysis, and High-Order Microplane Models to study concrete behavior under dynamic loading, size effects, and fracture mechanics. He has contributed to over 20 peer-reviewed publications, including works on reinforced concrete columns, damage localization algorithms, and multiscale analysis of geotechnical systems. Teaching responsibilities include courses like 'Reinforced Concrete II' and 'Prestressed Concrete' at the undergraduate level. His work integrates computational mechanics with experimental validation, addressing challenges in structural integrity and material failure under extreme conditions.

Emre Koyuncuمشاهده پروفایل

دانشیار

• Unmanned Aerial Vehicle Engineering
• Air Traffic Management
• Path Planning
• +۳ مورد دیگر

Emre Koyuncu is an Associate Professor in the Department of Aeronautical Engineering at Istanbul Technical University. His research focuses on unmanned aerial vehicle (UAV) engineering, air traffic management, and control systems. He is actively involved in EU-funded projects such as AIRMOB and AI4HyDrop, addressing challenges in drone operations, trajectory planning, and airspace safety. His work integrates reinforcement learning, particle filters, and control theory to enhance UAV autonomy and flight safety. Key projects include development of GNSS-denied navigation systems, stealth-maneuver strategies for aircraft, and resilient air traffic management frameworks. Research Interests: UAV navigation, trajectory optimization, control barrier functions, and stochastic control systems. Projects: Leading EU initiatives on drone safety (AIRMOB), AI-based navigation (AI4HyDrop), and resilient air traffic networks (START project). Awards: Received the Boeing Faculty Encouragement Grant (2015). His publications span topics like optimal recovery diffusion control, cooperative terrain-based navigation, and collision avoidance algorithms. He collaborates internationally on aerospace systems, emphasizing practical applications in aviation safety and autonomy.

Jessica Zhangمشاهده پروفایل

استاد

• Computational Geometry
• Isogeometric Analysis
• Finite Element Method
• +۱۲ مورد دیگر

Dr. Jessica Zhang is the George Tallman Ladd and Florence Barrett Ladd Professor of Mechanical Engineering at Carnegie Mellon University, with a courtesy appointment in Biomedical Engineering. She holds prestigious fellowships from ASME, SIAM, and other institutions. Her research focuses on computational geometry, isogeometric analysis, and applications in biomedicine and materials science. She has published over 200 technical articles and received numerous awards, including the PECASE and ASME Van C. Mow Medal. Education: PhD in Computational Engineering and Sciences from the University of Texas at Austin (2005), M.Eng. in Aerospace Engineering (UT Austin), and degrees from Tsinghua University in China. Research Interests: Computational geometry, mesh generation, finite element methods, and their applications in biomedical engineering, materials science, and mechanical engineering. Her lab develops algorithms for biomodeling at molecular to organ scales. Recent Achievements: In 2025, she was selected for the AWM-SIAM Kovalevsky Lecture and the ASME Van C. Mow Medal. Her work on neuron growth modeling and machine learning frameworks has advanced computational biomedical applications. Awards: Includes Simons Visiting Professorship, NSF CAREER Award, and multiple best paper awards. She chairs committees for conferences like Solid and Physical Modeling Symposium. Grants and Mentorship: Advised over 50 students and postdocs. Her lab collaborates across disciplines, including NextManufacturing Center and Materials Research Science and Engineering Center. Labs/Teams: Computational Bio-Modeling Lab, focusing on interdisciplinary projects in mechanical, biomedical, and materials engineering. Active in initiatives like Bioengineered Organs and NextManufacturing.

Shiaofen Fangمشاهده پروفایل

استاد

• Data Visualization
• Visual Analytics
• Interactive Machine Learning
• +۲ مورد دیگر

Shiaofen Fang is Professor of Computer Science and Associate Dean for Research at Indiana University's Luddy School of Informatics, Computing, and Engineering. He holds a Ph.D. in Computer Science from the University of Utah and M.S./B.S. degrees in Mathematics from Zhejiang University. His research focuses on data visualization, medical image analysis, and interactive machine learning. Research interests span: Data visualization including healthcare analytics and neuroimaging tools Medical image analysis for FASD diagnosis and brain connectomics Interactive AI for explainable machine learning systems Volume graphics for 3D modeling and rendering Publications demonstrate strong focus on AI applications in healthcare and education, visualization techniques for biomedical data, and geometric modeling. Recent works increasingly address ethical AI and bias mitigation. Research funded by NSF, NIH, DoD, and NIJ. Collaborates extensively with biomedical researchers and healthcare institutions. Leads projects on neuroimaging visualization, healthcare data exploration, and 3D facial analysis.

Ioannis Nikolosمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Turbomachinery Design
• Wind Turbine Optimization
• +۵ مورد دیگر

Ioannis Nikolos is a Professor at the School of Production Engineering and Management, Technical University of Crete, and holds a Visiting Professor position at the Institute of Plasma Physics & Lasers (IPPL), Hellenic Mediterranean University. With over 30 years of R&D experience, he has coordinated 39 projects and participated in 13 more. His research focuses on Computational Fluid Dynamics (CFD), Turbomachinery, Design Optimization, and Traffic Flow Modeling. He has authored/co-authored 60 journal papers, 110 conference papers, and three books, with an h-index of 24 (Google Scholar). Education: Diploma (1990) and PhD (1996) in Mechanical Engineering from the National Technical University of Athens (NTUA). His expertise spans fluid dynamics, engineering design optimization, and unmanned aerial vehicle aerodynamics. He is a Senior Member of AIAA and serves as an Associate Editor for ASME journals. Research Interests: Computational Engineering, Turbomachinery Component Design, Wind Turbine Optimization, Traffic Flow Modeling, and Plasma Physics applications. His work integrates computational intelligence with traditional engineering methods. Awards: Recipient of the IEEE ITS Society Outstanding Application Award (2018) for contributions to traffic management systems. He leads the Turbomachinery & Fluid Dynamics Laboratory and has supervised 7 completed PhD theses. Grants & Advising: Extensive R&D funding from EU, Industry, and Greek State. Currently supervising 3 PhD students. Editorial roles include ASME Journal of Fluids Engineering and Water. Labs & Teams: Director of the Turbomachinery & Fluid Dynamics Laboratory, collaborating on projects involving CFD, plasma physics, and autonomous systems.

• Data Science & Analytics
• Machine Learning
• Computational Statistics
• +۵ مورد دیگر

Professor İnci Batmaz, affiliated with the Department of Statistics at Middle East Technical University (METU), has held her current academic rank since 2012. She is also an affiliated faculty member of METU's Institute of Applied Mathematics (Financial Mathematics Program) and has served in administrative roles such as Chair of the Department of Statistics and Administrative Coordinator for institutional development initiatives. Ph.D. in Computer Engineering, Ege University (1993) Ph.D. Dissertation at Carnegie-Mellon University (Fulbright Scholar, 1988-1991) M.S. in Computer Engineering, Ege University (1986) B.S. in Statistics, METU (1984) Her research spans Data Science, Machine Learning, and Computational Statistics with applications in Environmental Statistics, Quality Improvement, and Financial Analytics. Key methodologies include Response Surface Methodology, Design of Experiments, and advanced regression splines (MARS, CMARS, RCMARS). She has made significant contributions to statistical modeling of climate patterns, financial systems, and industrial quality control. Recent publications focus on regression splines for predictive modeling (2021), climate change analysis (2016), robust statistical methods under uncertainty (2011), and machine learning applications in finance and environmental science. Her work emphasizes both theoretical developments and real-world implementations across diverse domains. Scientific Awards TÜBİTAK International Post-Doctoral Fellowship (2016-2017) Multiple METU Faculty Performance Awards (2003-2013) Best MSc Thesis Awards (2009, 2012) as co-advisor Fulbright Doctoral Scholarship (1988-1991) Seven TÜBİTAK research grants and publication supports She has advised two MSc students to award-winning theses and collaborated with international researchers including Prof. Gerhard W. Weber. Her professional experience includes visiting positions at Imperial College London and Tilburg University, along with board memberships in academic institutions like the Graduate School of Natural and Applied Sciences.

• Computational Modelling
• Solid Mechanics
• Material Interfaces
• +۵ مورد دیگر

Sonia Fernández-Méndez is a Professor (Catedrática de Universidad) at Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Civil and Environmental Engineering (DECA) and the Escola Tècnica Superior d'Enginyeria de Camins, Canals i Ports de Barcelona (ETSECCPB) . She also holds a lecturer position at the Facultat de Matemàtiques i Estadística (FME). Her research focuses on computational modeling in solid mechanics, material interfaces, electroactive materials, 4th-order PDEs, and advanced discretization methods like HDG and X-FEM. She leads the Laboratori de Càlcul Numèric (LaCàN) , a top research group in applied numerical methods. Education: Licenciatura en Matemàtiques (UPC, 1996), PhD in Applied Mathematics (UPC, 2001) under Antonio Huerta. Her awards include the Jacques Louis Lions Award 2010 and Juan Carlos Simó Award 2009. She has supervised 7 PhD students, including Rubén Sevilla and Alba Muixí. Her work bridges high-order methods with industrial applications in energy and materials science. Key contributions: Pioneered hybridizable discontinuous Galerkin (HDG) methods for fracture mechanics and flexoelectric metamaterials. Published extensively in Computer Methods in Applied Mechanics and Engineering , Journal of Scientific Computing , and International Journal for Numerical Methods in Engineering . Active in EU-funded projects on computational mechanics and energy materials.

Marco Fregoمشاهده پروفایل

دانشیار

• Robotics
• Control Systems
• Optimization Algorithms
• +۲ مورد دیگر

Marco Frego is a Tenured Associate Professor in the Faculty of Engineering at the Free University of Bozen-Bolzano. His research spans robotics, control systems, optimization algorithms, and manufacturing engineering, with applied work in industrial automation and computational geometry. Recent publications demonstrate a strong focus on robotic path planning, manufacturing efficiency, and machine learning integration in control systems. These include innovations in climbing robots for mountain rescue, Q-learning for predictive control, and heuristic solutions for wood yield optimization. Thematically, his work bridges theoretical mathematics with industrial applications, emphasizing practical implementations in robotics and production engineering.

• Control Theory
• Optimization
• Hybrid Systems
• +۳ مورد دیگر

Jinglai Shen is a Professor in the Department of Mathematics and Statistics at the University of Maryland Baltimore County (UMBC). His primary research interests include control theory, optimization, hybrid systems, multibody dynamics, and nonlinear control. He holds a Ph.D. in Aerospace Engineering from the University of Michigan (2002) and has held postdoctoral positions at Rensselaer Polytechnic Institute. He has received significant funding from the National Science Foundation (NSF) for projects related to switching dynamics, optimization, and smart vehicle platooning. Shen's research spans theoretical and applied domains, including constrained optimization, statistical estimation, and control system design for mechanical systems. He has advised multiple Ph.D. and Master’s students, contributing to their success in academic and industrial careers. He teaches advanced courses such as Matrix Analysis and Foundations of Optimization, reflecting his expertise in applied mathematics and control systems. His publications focus on topics like sparse recovery, switched systems stability, and distributed optimization algorithms. Collaborators include leading researchers from institutions like Purdue University and the University of Groningen. He is a Senior Member of IEEE and a member of SIAM.

Konrad Abramowiczمشاهده پروفایل

دانشیار

• Functional Data Analysis
• Statistical Methods in Biomechanics
• Climate Research
• +۴ مورد دیگر

Konrad Abramowicz is an Associate Professor and Head of the Department of Mathematics and Mathematical Statistics at Umeå University. His research focuses on functional data analysis, classification, and local inference procedures in the presence of misalignment, with applications in biomechanics, climate research, and forest growth analysis. He teaches stochastic simulations and parametric modeling methods, emphasizing student development and curiosity-driven learning. Education: University of Wrocław (Poland), with Erasmus exchange to Umeå University Research: Functional data analysis, interdisciplinary collaborations in biomechanics and climate science Awards: Teaching awards for dedication to student mentorship Internationalization: Postdoctoral work in Australia; collaborations with Italy and India; faculty-level international contact Konrad's research spans functional data analysis applied to knee kinematics after ACL injuries, climate reconstruction using sediment data, and statistical methods for forest growth analysis. He developed computational tools like the fiberLD R package for fiber length determination in forestry studies. His recent publications highlight interdisciplinary applications of statistical methods, with a focus on movement pattern analysis, climate modeling, and non-destructive forest assessment. Konrad advocates for international collaboration and adaptive academic practices to address global challenges. Konrad has received teaching awards and is recognized for his supportive approach to students. He actively participates in university initiatives for international student integration and served as international coordinator for academic exchange programs. As a key member of the IceLab interdisciplinary research hub, Konrad bridges statistical methods with applications in biomechanics and environmental science. His work emphasizes the importance of mathematical abstraction in solving real-world problems.