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ESRA GÜRBÜZ YILDIRIMView profile

Assistant Professor

• Architecture
• Planning and Design
• Architectural Design
• +7 more

Esra Gürbüz Yıldırım is an Assistant Professor at the Faculty of Architecture of Gaziantep University , Turkey, where she has been teaching since 2019. She previously served as a Research Assistant at Istanbul Technical University (2007-2011) and Gaziantep University (2011-2019). Her academic journey includes a PhD in Informatics in Architectural Design (2018) and an MSc in Informatics in Architectural Design (2010) from Istanbul Technical University, along with a Licence in Architecture (2006) from the same institution. Current Role: Assistant Professor, Gaziantep University Educational Background: PhD (2018), MSc (2010), Licence (2006) Teaching Focus: Architectural Design, Digital Media, Architectural History Research Interests center on architectural design integration with digital technologies, urban morphology analysis, and socio-cultural sustainability in urban transformation. She employs computational methods like Space Syntax and generative modeling to study traditional architectural patterns and contemporary design applications. Scientific Contributions include publications on Gaziantep's traditional architecture and its modern adaptations, urban sustainability, and digital pedagogy in architecture. Her work bridges historical analysis with computational design tools. 2021: Two studies on Gaziantep's urban transformation 2018: Space Syntax analysis of socio-cultural impacts 2010: Generative design models for traditional patterns Awards and Collaborations include editorship roles in the MimED 2008 and Arched 2008 award programs. She has advised graduate students like Ipek Ozan (2020 thesis on historical building reuse) and leads administrative roles in her department (Head 2017-2018, Deputy Head 2020-2022, Head 2022-2024).

• Engineering Graphics
• Descriptive Geometry
• Computer Graphics
• +4 more

Evelina Anatoliivna Bazhmina is an Associate Professor at Zaporizhzhia Polytechnic University, specializing in engineering education with a focus on descriptive geometry, engineering graphics, and computer graphics. She has been affiliated with the university since 1993 and holds a PhD in Professional Education, which she defended in 2023 with her dissertation on forming a culture of independent work among mechanical engineering students using BYOD technology. Her educational background includes: Specialist diploma in 'Materials Science in Mechanical Engineering' from ZNTU (1998) Bachelor's degree with honors in 'Jurisprudence' from ZNTU (2012) Specialist diploma with honors in 'Jurisprudence' from ZNTU (2013) Dr. Bazhmina's research focuses on innovative teaching methods for engineering graphics, blended learning approaches, and the application of BYOD technology in technical education. She also has expertise in civil and family law, contributing to interdisciplinary educational approaches. Her work emphasizes student-centered learning and the development of independent work skills among technical students. Her extensive publication record demonstrates a strong commitment to improving engineering education through technology integration, with particular emphasis on formative assessment, personalized learning approaches, and the development of students' self-directed learning capabilities in technical disciplines. Scientific awards and recognitions include: Honorary badge 'For Impeccable Work' III degree (2024) Honorary certificate of the Executive Committee of the Zaporizhzhia City Council (2016) Gratitude of the Board of Education and Science of Zaporizhzhia Regional State Administration (2011) Honorary certificate of the Trade Union of Education and Science Workers of Ukraine (2011) Honorary certificate of the Department of Education and Science of Zaporizhzhia Regional State Administration (2002) Dr. Bazhmina has authored multiple textbooks and teaching materials, including 'Diagnostics of the formation of a culture of independent work of students of the mechanical engineering industry' and 'Fundamentals of engineering graphics,' contributing significantly to educational resources in her field. She teaches Descriptive Geometry, Engineering Graphics, and Computer Graphics courses at the university.

• Algorithm Engineering
• Efficient Algorithms and Data Structures
• Intelligent Computing & Engineering
• +11 more

Christos Zaroliagis is a Full Professor in the Department of Computer Engineering & Informatics at the University of Patras, Greece, where he serves as Head of the Intelligent Computing & Engineering Lab (ICE Lab). He is also a Senior Research Associate at the Computer Technology Institute & Press "Diophantus" in Patras. Previously, he held positions at the Max-Planck-Institut für Informatik in Saarbrücken, Germany, and the Department of Informatics at King's College, University of London, UK. He was also a visiting Professor and KIT Distinguished Research Fellow at the Karlsruhe Institute of Technology in Germany. Professor Zaroliagis specializes in algorithm engineering, optimization, decentralized computing, and cryptography & information security, with applications in large-scale networks and systems. His research has significant focus on mobility in smart cities, intelligent transportation systems, and big data analysis. He has published extensively in major international journals and conferences, and has served as editor for several academic journals including Algorithms, Journal of Discrete Algorithms, and ACM Journal of Experimental Algorithmics. His work spans both theoretical foundations and practical implementations, with numerous software libraries and systems developed under his leadership. His recent publications demonstrate continued innovation across cloud computing, intelligent transportation systems, decentralized computing, and big data analytics, showing a clear progression from foundational algorithm design to practical applications in smart city infrastructure. The research shows strong interdisciplinary connections between computer science, operations research, and urban planning. prize award 2012 for Academic and Scientific Excellence awarded by the Greek Ministry of Education KIT Distinguished Research Fellow Mercator Fellow Professor Zaroliagis leads the Intelligent Computing & Engineering Lab (ICE Lab), which has produced several significant software systems including PGL (graph algorithms library), ECC-LIB (cryptography library), Searchius (collaborative search engine), and iClone (social navigation system). His academic service includes heading the EURAXESS Services Center of the University of Patras and serving as National Contact Point for the FP7 PEOPLE Program - Mobility. He has been extensively involved in organizing international conferences and serving on program committees across computer science.

• Computer-Aided Design (CAD)
• Manufacturing Engineering
• Mechanical Engineering
• +3 more

John Bijnens is a Senior Lecturer at KU Leuven , affiliated with the Manufacturing Processes and Systems (MaPS) unit on the Diepenbeek Campus. His work focuses on computer-aided design (CAD), geometry data exchange, and flexible manufacturing systems. Research Interests Model-Based Definition (MBD) CAD interoperability STEP AP242 standards Interactive e-learning for mechanical design Flexible manufacturing Digital twin technology Publications highlight his contributions to CAD data exchange accuracy, geometric modeling, and educational tools for mechanical design. No scientific awards are explicitly mentioned. His teaching role emphasizes curriculum development and contact person responsibilities within the Mechanical Engineering Department.

Yves WeinandView profile

Professor

• Timber Construction
• Computational Geometry Processing
• Robotic Fabrication
• +7 more

Yves Weinand serves as Full Professor of Timber Construction at École Polytechnique Fédérale de Lausanne (EPFL), where he directs the transdisciplinary Wood Construction Laboratory (IBOIS) within the School of Architecture, Civil and Environmental Engineering. His appointment spans the Institute of Civil and Environmental Engineering (IIC) and teaching units in Architecture (SAR) and Civil Engineering (SGC), reflecting his interdisciplinary focus at the intersection of structural engineering and architectural design. His research expertise spans computational geometry processing, robotic timber construction, and experimental joinery techniques, with particular emphasis on digital fabrication workflows for complex wood structures. Weinand's work integrates augmented reality systems with traditional craftsmanship and develops novel computational methods for timber plate structures and through-tenon connections. Analysis of his recent publications reveals a strong trend toward hybrid digital-physical construction workflows, with increasing focus on AI-assisted fabrication, real-time quality control, and sustainable material utilization. His research bridges fundamental structural mechanics with practical building applications through technology transfer projects. Lignum Prize - Western Region Mention (2018) French Academy of Architecture silver medal (2017) Grand Prix d'architecture de Wallonie for Vidy theater (2019) Wood Distinction 2019 for Vaud Parliament building (2019) Medal for Research and Technique from French Academy of Architecture (2017) Weinand supervises numerous doctoral candidates while teaching ten courses across bachelor to postgraduate levels, including computational architecture and digital timber construction. His laboratory collaborates with industry partners through technology transfer contracts for projects like the Annen Vault, Rossinière Centre, and Brussels Sportstower, implementing EPFL-developed computational methods in real-world construction. The IBOIS laboratory operates as a transdisciplinary research hub connecting architectural design exploration with structural engineering innovation, maintaining active partnerships with timber industry stakeholders and architectural practices across Europe.

• Computer Vision
• Machine Learning
• Medical Image Analysis
• +4 more

Dr. Xianfang Sun is a Senior Lecturer at Cardiff University's School of Computer Science and Informatics, where they have been a faculty member since 2005. Their research bridges traditional control theory with modern computer vision and machine learning applications. They actively supervise postgraduate students and maintain collaborations across multiple disciplines. Dr. Sun's research spans machine learning, computer vision, and graphics with a focus on medical imaging applications. Their work demonstrates a clear evolution from early control theory research toward applied computer vision systems, particularly in medical diagnostics and agricultural technology. Current projects emphasize lightweight architectures for real-world deployment, especially in brain tumor segmentation and fruit ripeness detection systems. Their publication record reveals strong trends in medical image analysis (brain tumor segmentation, cancer cell manipulation), agricultural computer vision (fruit ripeness detection), and media forensics. Recent work prioritizes clinically adaptable systems with computational efficiency, showing practical implementation focus rather than purely theoretical contributions. Dr. Sun has secured funding through EPSRC projects and previously led NSFC and 863 Program projects in China. Their supervision interests include AI for medical diagnosis, image processing, pattern recognition, and 3D geometry processing. Based at Cardiff University's Abacws building, Dr. Sun maintains active research in both theoretical and applied aspects of visual computing, with recent work showing increasing emphasis on real-world medical applications requiring robust and efficient implementations.

Namık ÇıblakView profile

Assistant Professor

• Mechanical Engineering
• Machine Design
• Robotics
• +5 more

Assistant Professor Namık Çıblak is affiliated with Yeditepe University's Faculty of Engineering, Department of Mechanical Engineering. He has held academic positions since 1992, including roles at Georgia Southern University and American University of the Middle East. PhD in Mechanical Engineering (Georgia Institute of Technology, 1997) MS in Mechanical Engineering (Middle East Technical University, 1989) BS in Mechanical Engineering (Middle East Technical University, 1986) His research spans Mechanical Design , Robotics , and Biomechanics , focusing on stiffness analysis, parallel manipulators, and medical device development. Recent work explores soliton motions in continua and neural network applications in muscle imaging. Prominent publications include: 2021: Kinematic Condition For Soliton Motions of an n-dimensional Continuum 2019: Leveraging artificial neural networks for muscle meshing 2018: Resolution of the Vibrating String Controversy 2013: Variable Tension String Model Scientific contributions include: Silver Medal, Istanbul International Invention Fair Multiple patents in mechanical systems and surgical devices He has supervised 12+ graduate theses and led major projects including: TÜBİTAK-funded Biomechatronic Robotic Snake (2015-2018) Energy Harvesting Sensor for Tire Pressure Monitoring (2018-) Heart Turcica Centrifugal Blood Pump Development

Gordana ĐukanovićView profile

Associate Professor

• Geometry of architectural form
• Descriptive geometry
• Relativistic geometry
• +4 more

Gordana Đukanović is an Associate Professor at the Faculty of Forestry, University of Belgrade, where she has been employed since October 1, 1994. She currently teaches courses in geometry, engineering graphics, and related subjects across multiple academic programs including Basic Academic Studies, Master's programs, and Vocational Studies. Education: Graduated from the "Vuk Karadžić" High School (mathematics department - programmer) in Loznica Graduated from the Faculty of Civil Engineering in Belgrade (Construction department) on March 7, 1988 Defended her master's thesis from the Faculty of Architecture in Belgrade on December 26, 2000 Defended her doctoral dissertation from the Faculty of Architecture, University of Belgrade on November 2, 2012 Professor Đukanović specializes in the geometry of architectural form with research focusing on descriptive geometry, relativistic geometry, engineering graphics, and photogrammetry. Her work bridges architectural theory with practical applications in forest engineering and building design. She has published 49 papers including more than 5 peer-reviewed scientific papers in journals, 35 papers presented at congresses and symposia, one practical guide, and numerous studies and projects for wood processing companies. Her recent publications demonstrate a strong interdisciplinary approach connecting geometry with environmental science, architecture, and engineering. The research spans from theoretical mathematical explorations to practical applications in air pollution analysis, flood management, structural integrity assessment, and renewable energy systems design. Scientific Awards and Recognition: University Scholarship as one of the three students with the best grade point average during the first two years of university Certified court expert in the field of building valuation Professor Đukanović serves as a member of the Serbian Society for Geometry and Graphics (SUGIG) and the International Society for Geometry and Graphics (ISGG). She has passed the professional exam in civil engineering at the Association of Engineers and Technicians of Serbia. Her teaching responsibilities include courses in descriptive geometry with engineering graphics for Ecological Engineering in Land and Water Resources Protection, Furniture and Wood Products Construction, and Technology of Wood House Production.

• Machine Learning
• Optimization
• Data Mining
• +2 more

Dr. Annabella Astorino is a researcher at ICAR-CNR (Italian National Research Council) in Rende, Italy, with expertise in machine learning, optimization, and computational biology. Her work focuses on classification algorithms using nonsmooth optimization, spherical separation, and multiple instance learning (MIL) approaches. Key Research Themes Geometric separation techniques (polyhedral, spherical) Multiple instance learning for biomedical applications Nonsmooth optimization in semisupervised learning Clustering methods for edge detection in images Recent publications highlight her development of Lagrangian relaxation for MIL, kernel-enhanced spherical separation algorithms, and DC optimization for computer vision tasks. Her collaborations include researchers like A. Fuduli, M. Gaudioso, and P. Veltri.

Yu FengView profile

Associate Professor

• Computational Fluid-Particle Dynamics
• Biomedical Engineering
• Pulmonary Healthcare Innovation
• +6 more

Yu Feng is an Associate Professor in the School of Chemical Engineering at Oklahoma State University , with affiliate roles in Mechanical and Aerospace Engineering. He leads the Computational Biofluidics and Biomechanics Laboratory (CBBL@OSU) and contributes to the Oklahoma Center for Respiratory and Infectious Diseases (OCRID) . His work bridges computational fluid-particle dynamics (CFPD) , machine learning , and digital twin technologies to advance pulmonary drug delivery and occupational health risk assessment . Ph.D., Mechanical Engineering, North Carolina State University (2013) M.S., Mechanical Engineering, NC State (2010) B.S., Engineering Mechanics, Zhejiang University (2007) Research spans multi-scale aerosol modeling for lung disease progression analysis, smart inhaler optimization , and in silico toxicology . His 2023-2025 publications demonstrate expertise in VOF-to-DPM simulations for inhaler design, CFPD-PK integration for THC delivery, and nasal hair dynamics studies. Awards include NSF EPSCoR Fellowship , Distinguished Early Career Award at OSU , and Journal of Aerosol Science Excellence in Research Award . Teaching focuses on CHE 5110/4773/5773: Computational Fluid-Particle Dynamics and Chemical Engineering Laboratory courses. Outreach initiatives include Lungevity K-12 program using augmented reality for pulmonary education and public engagement on SARS-CoV-2 transmission and clean energy safety .

Neha ChandaranaView profile

Senior Lecturer

• Composite Materials
• Acoustic Emission Monitoring
• Damage Detection
• +4 more

Neha Chandarana is a Senior Lecturer at the School of Civil, Aerospace and Design Engineering, University of Bristol, and a Visiting Researcher at the University of Manchester. She is affiliated with the Bristol Composites Institute and leads the ACCIS Engineering Education Research Group. Research Focus: Composite materials, sustainable development, acoustic emission monitoring, and damage detection in carbon fibre laminates. Projects: Principal Investigator for the IGNITE Network+ and Ca-pow! projects, addressing energy research inclusivity and educational equity for marginalized students. Publications: Recent work explores mycelium composites for Africa, tooling pressure effects in composites, and sensor integration for damage detection. Education: BSc Hons and PhD in engineering-related disciplines.

Imanol Munoz-PandiellaView profile

Assistant Professor

• Computer Graphics
• Cultural Heritage
• 3D Reconstruction
• +4 more

Imanol Munoz-Pandiella is an assistant professor in the Computer Science Department at Universitat Politècnica de Catalunya – BarcelonaTech (UPC) and a core member of the ViRVIG research center . His work bridges computer graphics and cultural-heritage science, with a focus on 3-D reconstruction, appearance modeling, and interactive visualization of historical artefacts. Education Ph.D. in Computer Graphics (2017) – joint programme between Université de Limoges and Universitat de Girona (supervisors: Stéphane Mérillou, Xavier Pueyo, Carles Bosch, Nicolas Mérillou) Pre-doctoral stay – Yale University (supervisor: Holly Rushmeier) Research Interests Dr Munoz-Pandiella investigates the intersection of Computer Graphics and Cultural Heritage . Current themes include: Appearance change and weathering analysis in architectural heritage High-fidelity 3-D reconstruction from sparse data Interactive narrative frameworks for 4-D (time-varying) heritage models Physically-based rendering and differentiable inverse rendering Color constancy and illumination-robust imaging for conservation science Publication Landscape His 2024–2025 output is dominated by 4-D cultural-heritage visualization , digital restitution of lost or weathered artworks , and real-time rendering techniques . Earlier work (2021–2022) concentrated on LiDAR intensity correction and neural colorization . Collectively, these publications map onto broad disciplines of Computer Graphics , Computer Vision , and Digital Heritage , with sub-fields spanning differentiable rendering, mural-painting restoration, and interactive 3-D exploration. Scientific Awards & Grants Assistant Professor position award – UPC, 2023 Post-doctoral fellow award – DTIC, Universitat Pompeu Fabra, 2023 Participant and grantee – European Cloud for Heritage OpEn Science (ECHOS), 2024 Service & Leadership Program Chair, CEIG 2026 (with Elena Garces) Program Co-Chair, Web3D 2023 Guest Editor, Computers & Graphics special issue on Web3D 2023 Program Committee member, CEIG 2023 Laboratory & Collaborations Dr Munoz-Pandiella conducts his research within the ViRVIG research center at UPC, collaborating closely with cultural-heritage stakeholders across Europe. His interdisciplinary teams integrate art historians, conservation scientists, and graphics engineers to deliver open-source tools and datasets for heritage documentation and dissemination.

Kimberly ConnerView profile

Associate Professor

• Mathematics Education
• Secondary Education
• Proof Theory
• +5 more

Kimberly Conner is an Associate Professor of Mathematics Education at the University of Northern Iowa, affiliated with the College of Humanities, Arts and Sciences. Her research focuses on designing and analyzing pedagogical strategies for teaching proof at the secondary level, particularly through number talks, dot talks, and peer critique processes. Office: 308 Wright Hall Phone: (319) 273-2907 Office Hours: TTH 11:00-12:00 & 2:00-3:00 (Fall 2025) Her research examines how teachers' questioning practices foster mathematical reasoning, with emphasis on generality requirements in proof, technology-mediated instruction, and the development of collaborative proof-construction frameworks. Recent work explores virtual simulations for preservice teacher training, instructional tensions in geometry classrooms, and leadership roles of elementary mathematics specialists. Kimberly's publications span topics such as peer critique systems, proof understanding trajectories, and the integration of technology in mathematics education. While no formal awards or student advisement details are listed in the provided data, her work addresses critical gaps in secondary mathematics pedagogy and teacher development.

• Smart Manufacturing
• Digital Twins
• Geometry Assurance
• +4 more

Dr. Roham Sadeghi Tabar is a researcher at Chalmers University of Technology , specializing in Geometry Assurance and Robust Design within the Department of Product and Production Development. His work bridges academia and industry through collaborations with automotive and aerospace sectors, focusing on optimizing variation simulation for non-rigid assemblies . Affiliation : Chalmers University of Technology Research Area : Geometry Assurance, Digital Twins, Smart Manufacturing Research Interests : Roham’s research spans Smart Manufacturing , Digital Twins , and Modeling and Simulation , with a technical focus on non-rigid assembly optimization . His work develops physics-informed AI methods to enhance geometric precision in automotive and aerospace production, addressing challenges in variation simulation and contact modeling . Publication Trends : His recent articles emphasize digital twin infrastructure for manufacturing, reinforcement learning in disassembly planning, and physics-based simulation for non-rigid parts. Key themes include spot welding sequence optimization , fixture layout , and stochastic batch assembly improvements. Professional Affiliations : Research Affiliate at CIRP, Member of ASME Projects : DigiSync, AIDCAM, PIADT, AIDDT, Digital Quality Assurance, Smart Assembly 4.0 Funding : VINNOVA, Swedish Foundation for Strategic Research (SSF) Labs & Teams : He works within the Geometry Assurance and Robust Design group, contributing to multidisciplinary projects like Digital Twin-Based Clamping Sequence Analysis and Physics-Informed AI for Assembly .

• Drilling Automation
• Digitalization in Energy
• Artificial Intelligence
• +17 more

Dan Sui is a Professor in the Department of Energy and Petroleum Engineering at the University of Stavanger, within the Faculty of Science and Technology. His research is centered on drilling automation, digitalization, artificial intelligence, machine learning, data analytics, modeling, optimization, and control systems in petroleum and geothermal energy contexts. His research interests span drilling automation, AI, machine learning, data processing, modeling, optimization, simulation, control system design (including model predictive control, PID, Kalman filters), advanced drilling technologies, drilling event detection, geothermal drilling, and digital twin development. He actively contributes to the development of smart drilling systems and data-driven models for real-time decision support. The recent publications (2020–2025) highlight a strong trend in applying reinforcement learning, deep learning, and data-driven modeling to drilling optimization, ROP prediction, well path design, and subsea control. These works are published in high-impact journals such as SPE Journal , Journal of Petroleum Science and Engineering , and Applied Sciences , as well as in proceedings from ASME and IADC/SPE conferences, indicating a strong presence in both petroleum and mechanical engineering domains. Automatic calibration of directional drilling control Multi-agent reinforcement learning for waterflooding PI controller tuning using Deep Q-Learning Safe operating envelope for directional drilling Neural network optimization for ROP prediction Real-time ROP trend analysis Well path optimization with Bezier curves Anti-collision trajectory design Automated drilling algorithms on lab rigs Subsea shuttle tanker depth control While no specific scientific awards are listed, his extensive publication record and involvement in AI and digital twin projects reflect significant recognition in the field. He advises students and collaborates on research involving laboratory-scale drilling automation systems, hybrid test environments, and smart drilling robots, contributing to both theoretical and applied advancements. His work includes development of algorithms for autonomous drilling agents, feature selection for kick detection, and experimental studies on drillstring dynamics. Dan Sui is a key contributor to the OpenLab project, a modern drilling digitalization infrastructure, and leads research in data quality improvement, downhole data correction, and sensor data reconstruction using recurrent neural networks. His lab-based work includes designing autonomous small-scale drilling rigs and testing machine learning algorithms for incident detection, showcasing a strong integration of experimental and computational research.