جست‌وجوی استاد و پژوهشگر

• 3D Printing
• Additive Manufacturing
• Welding
• +۶ مورد دیگر

Ulas Yaman is an Assistant Professor in the Department of Mechanical Engineering at Middle East Technical University (ODTÜ), Ankara, Turkey. He holds a PhD (2014), MSc (2010), and BSc (2007) in Mechanical Engineering from ODTÜ, with a minor in Mechatronics. His academic career includes a Visiting Assistant Professor role at Purdue University (2014-2015) and Research Assistant positions at ODTÜ (2007-2014). Education: PhD, Mechanical Engineering, ODTÜ (2007-2014) MSc, Mechanical Engineering, ODTÜ (2007-2010) BSc, Mechanical Engineering, ODTÜ (2003-2007) Minor in Mechatronics, ODTÜ (2004-2007) Professor Yaman's research focuses on 3D Printing, Additive Manufacturing, CAD/CAM architectures, FPGA-based embedded systems, and computational geometry for manufacturing . His work addresses challenges in dimensional accuracy, interior structure optimization, and command generation paradigms for CNC and 3D printing systems. He developed the LIPRO pipeline, leveraging Python-based scripting and List Processors to reduce G-code file sizes by up to 99.7% in FDM applications. Scientific Contributions: Fundamental advancements in 2.5D curve offset generation using mathematical morphology Innovative shrinkage compensation techniques for FDM 3D printing Hybrid manufacturing systems integrating additive and subtractive processes Query-based CAD/CAM architectures for heterogeneous printing Real-time interpolator implementations on FPGA hardware Awards & Grants: Best Paper Award, IEEE Workshop on Intelligent Solutions in Embedded Systems (2016) TÜBİTAK 1001 Project Grant (2017-2020) for Hybrid Manufacturing Systems TÜBİTAK 3001 Grant (2017-2018) for LIPRO Pipeline Development ODTÜ-BAP Grant (2016) for Dimensional Accuracy Improvement TÜBİTAK PhD Scholarship (2010-2014) As an educator, he has taught advanced courses including ME 533 - Computer-Aided Design and ME 414 - System Dynamics at ODTÜ since 2015. His laboratory leads projects on smart manufacturing systems and develops open-architecture platforms for experimental validation of novel fabrication paradigms.

• STEM Education
• Mathematics Education
• Artificial Intelligence in Education
• +۵ مورد دیگر

Dr. Yuling Zhuang is an Assistant Professor in the Department of Teaching, Learning and Culture at Texas A&M University's College of Education and Human Development. She holds a Ph.D. and M.A. in mathematics education from the University of Georgia (2020) and an M.Ed. from Beijing Normal University (2015). Ph.D., Mathematics Education, University of Georgia (2020) M.A., Mathematics, University of Georgia (2020) M.Ed., Mathematics Education, Beijing Normal University (2015) Her research focuses on empowering teachers to support STEM learning through argumentation, integrating artificial intelligence and educational robotics in classrooms. She develops interventions to enhance teachers' questioning strategies and proof validation skills using frameworks like Habermas' rationality and Toulmin's model. Recent work explores AI-driven teaching tools and generative AI applications in mathematics education, with publications in top journals like Educational Studies in Mathematics and Journal of Mathematics Teacher Education . She collaborates with interdisciplinary teams across engineering, computer science, and instructional technology. Scientific awards include: Association of Mathematics Teacher Educators (AMTE) STaR Fellow (2022) Dr. Zhuang teaches mathematics content and pedagogy courses, with prior experience in both China and the US. She serves on STEM outreach program boards and presents at international conferences like PME-NA.

John Essexمشاهده پروفایل

استاد

• Molecular simulations of biological systems
• Computer aided drug discovery
• Method development in molecular simulations

Professor Jonathan W. Essex is a faculty member in the Department of Chemistry at the University of Southampton, specializing in Computational Systems Chemistry. His research focuses on molecular simulations of biological systems, computer-aided drug discovery, and method development in molecular simulations. Education: First-class honors in Chemistry from Oriel College, Oxford (1989); D.Phil. in computational modeling at Oxford Academic Career: Royal Society University Research Fellow (1994), Lecturer (1997), Senior Lecturer (2001), Reader (2005), Personal Chair (2007) Research interests center on advancing computational methodologies for biological systems, with applications in pharmaceutical development and medical diagnostics. His group develops innovative simulation techniques deployed in drug design, antibody structure analysis, and nano-scale material studies through collaborations with industry and academic partners. Scientific contributions include 13 major publications (2013-2025) spanning computational drug discovery, biomolecular simulations, and quantum physics. Key projects involve: Model for Anti-Toxin Medical Countermeasures (DTRA) Immunostimulatory Antibodies (Cancer Research UK) Protein Dynamics Visualization ('Time Travel' project) 2002 Marlow Medal (Royal Society of Chemistry) Royal Society Wolfson Research Merit Award (2013) He serves on the EPSRC College and CCPBioSim advisory board, with extensive grant funding from EPSRC, BBSRC, and Cancer Research UK for projects including ExaBioSim (exascale biomolecular simulations), Sequential Monte Carlo sampling, and antibody engineering research.

Ling-Qi Yanمشاهده پروفایل

دانشیار

• Computer Graphics
• Rendering Algorithms
• Real-time Ray Tracing
• +۵ مورد دیگر

Ling-Qi Yan is an Associate Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he co-directs the MIRAGE Lab and is affiliated with the Four Eyes Lab. His research focuses on computer graphics, particularly real-time rendering, physically-based appearance modeling, and advanced light transport algorithms. Prior to UCSB, he earned his PhD from UC Berkeley, advised by Ravi Ramamoorthi, and completed internships at Disney, Autodesk, Weta Digital, and NVIDIA Research. He also holds a B.E. in Computer Science from Tsinghua University. Yan's education includes a PhD in Computer Science from UC Berkeley (2018) and a B.E. from Tsinghua University (2013). His research interests span rendering photo-realistic visuals, real-time ray tracing, and appearance modeling for materials like fabrics and fur. Notable achievements include the 2023 EGSR Best Paper Award for cloth shading work and the 2019 ACM SIGGRAPH Outstanding Doctoral Dissertation Award. His awards include the Regents' Junior Faculty Fellowship (UCSB), Best Visual Effects Award (EGSR 2023), and NVIDIA Graduate Fellowship supervision recognition. He teaches courses such as Introduction to Computer Graphics and Real-Time High-Quality Rendering , and has developed online courses in Chinese like GAMES101 and GAMES202 . Yan's lab collaborations and industry ties include roles as a research consultant at Intel and visiting professor at NVIDIA. His research emphasizes bridging theory and practice, with over 50 publications in top venues like SIGGRAPH and ACM Transactions on Graphics.

• Computational Geometry
• Algorithm Design and Analysis
• VLSI Computer-Aided Design
• +۳ مورد دیگر

Evanthia Papadopoulou is a Full Professor of Computer Science at the University of Lugano (Università della Svizzera italiana) since 2016. Previously, she was an Associate Professor at USI (2008–2016), a Research Staff Member at IBM T.J. Watson Research Center (1996–2008), and an Assistant Professor at Athens University of Economics and Business (2004–2008). She holds a BS in Mathematics from the University of Athens, an MS in Computer Science from the University of Illinois at Chicago, and a PhD in Computer Science from Northwestern University (1995). Her research focuses on computational geometry, algorithm design, and their applications in VLSI CAD and geometric computing. Key areas include Voronoi diagrams, proximity algorithms, triangulations, and geometric optimization. She has received the IBM Outstanding Innovation Award (2006) and the Technical Accomplishment for IBM Research (2006) for her work on VLSI critical area analysis using Voronoi diagrams. As part of the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI), her work integrates theoretical and applied aspects of computational geometry. Her contributions span algorithmic frameworks, geometric data structures, and practical applications in VLSI layout analysis and manufacturing. Her recent research emphasizes high-order Voronoi diagrams, subdivision methods for geometric optimization, and certified approximation algorithms. These advancements address challenges in geometric computing, such as farthest-color Voronoi diagrams and dynamic geometric problems.

Eugene Fiumeمشاهده پروفایل

استاد

• Computer Graphics
• Animation
• Fluid Simulation
• +۳ مورد دیگر

Eugene Fiume is a Professor and Dean of the Faculty of Applied Sciences at Simon Fraser University (SFU). He holds a Ph.D. in Computer Science from the University of Toronto (1986), an M.Sc. from the same institution (1982), and a B.Math (Hons.) in Computer Science from the University of Waterloo (1981). His research focuses on computer graphics, animation techniques, and educational applications of technology. He leads the Tangent Lab, exploring advanced topics in fluid simulation, facial animation, and physics-based motion retargeting. His work spans interdisciplinary areas, including fluid dynamics, mesh processing, and game development. Notable contributions include VEMPIC (particle-based fluid simulation), animator-centric tools like Jali for lip synchronization, and vocal animation frameworks for expressive speech. He has held leadership roles in academic administration and has contributed to industry-research collaborations through his deanship. Publications emphasize innovation in animation systems, real-time rendering, and procedural modeling. His research has been applied in gaming (e.g., Cyberpunk 2077 facial animations) and medical imaging, reflecting a blend of theoretical and applied computer science.

Gary Simpsonمشاهده پروفایل

مدرس ارشد

• Data Envelopment Analysis
• Performance Measurement
• Higher Education Management
• +۴ مورد دیگر

Gary Simpson is a Senior Lecturer at Aston Business School, part of the College of Business and Social Sciences at Aston University. He specializes in Operations and Service Management, with a focus on Data Envelopment Analysis (DEA), performance measurement, and educational technology innovation. Education: Doctor of Philosophy (1996), University of Salford Certificate in Education (1996), University of Central England BSc Joint Honours in Science (Mathematics & Computer Science, 1987), University of Salford Research interests include: DEA applications in education and business analytics Spreadsheet model development and validation Technology integration in higher education (e.g., gamification, VLEs) Educational policy evaluation through quantitative methods His publications span DEA methodologies, FDI impacts, and education policy, with a focus on nonparametric techniques and efficiency analysis. Notable work includes comparative studies on school performance and gender-based GCSE outcomes. Awards: Fellow of the Higher Education Academy Administrative roles include Associate Dean for Learning and Teaching at Aston Business School, and membership in the Operational Research Society. He has supervised 3 academic works and contributed to educational technology initiatives like lecture capture systems and gamification research.

Ragni Pieneمشاهده پروفایل

استاد

• Algebraic geometry
• Enumerative geometry
• Intersection theory
• +۵ مورد دیگر

Ragni Piene is a Professor at the University of Oslo, affiliated with the Faculty of Mathematics and Natural Sciences. Her career spans decades of contributions to algebraic geometry and related fields. Education: Ph.D. from MIT (1976), M.Sc. and D.E.A. from the University of Oslo and Université de Paris (Orsay). Visiting Positions: Held at Institut Mittag-Lefler, MSRI Berkeley, École Normale Supérieure Paris, Harvard University, Université Grenoble, IHES Paris, Ecole Polytechnique Paris, and MIT. Research Interests: Focus on algebraic geometry, particularly enumerative geometry and intersection theory, singularity theory, moduli spaces, Hilbert schemes, toric varieties, and algebraic methods in computer-aided geometric design. Scientific Leadership & Awards: Chair of the Abel Committee (2010–2014), Fellow of the American Mathematical Society (2012), and memberships in prestigious academies including Academia Europaea (2012) and the Norwegian Academy of Science and Letters (1994). Committee Roles: Extensive service on international boards like the Executive Committee of IMU (2003–2010), Scientific Advisory Board of RICAM (2012–), Orientation Council of INSMI (2011–), and editorial boards of Communications in Algebra and Astérisque .

Elena Ivanova Zaharieva-Stoyanovaمشاهده پروفایل

دانشیار

• Computer-Aided Design (CAD)
• Image Processing
• Knitting Industry Automation
• +۵ مورد دیگر

Elena Ivanova Zaharieva-Stoyanova is an Associate Professor at the Technical University of Gabrovo, Bulgaria, specializing in Computer Systems and Technologies. She holds a Doctorate in Automated Design Systems in Knitwear Production (1999) and was appointed Associate Professor in 2005. Her academic career spans over 25 years at the Technical University of Gabrovo, progressing from Assistant to her current position. Dr. Zaharieva-Stoyanova's research focuses on the intersection of computer science and traditional textile arts, particularly developing CAD/CAM systems for knitting and crochet industries. Her work bridges software engineering with cultural heritage preservation, creating digital representations of traditional costumes and developing specialized XML-based languages for craft pattern description. She teaches Object-Oriented Programming and Introduction to Programming at the bachelor's level, and Platform-Independent Programming at the master's level. Her publication record shows a clear progression from foundational CAD system development to sophisticated digital representation of traditional crafts. The most recent articles demonstrate her specialization in XML-based languages for knitting and crochet symbols, color stitch representation, and validation modules for traditional costume digitization. This research trajectory reflects a deep commitment to preserving cultural heritage through technological innovation. Dr. Zaharieva-Stoyanova has participated in numerous scientific projects funded by the Scientific Research Fund from 2001-2017, covering image processing in CAD systems, digital data transmission, and most recently, cloud-based medication monitoring systems. She is a member of both the Union of Scientists in Bulgaria and the Union of Automation and Informatics. Fluent in English and Russian with excellent reading and very good writing and speaking skills in both languages, she has conducted specializations in the Czech Republic and Croatia under the CEEPUS project. Her international collaborations are evident in her publications presented at conferences across Europe including Bulgaria, Serbia, Macedonia, Greece, Spain, Austria, Romania, and Ireland.

Isabel Proençaمشاهده پروفایل

دانشیار

• Econometrics
• Microeconometrics
• Spatial Econometrics
• +۶ مورد دیگر

Isabel Proença is an Associate Professor with Aggregation in Econometrics at ISEG – Lisbon School of Economics and Management, Universidade de Lisboa. She holds a PhD in Economics from Université Catholique de Louvain (1995) and an Agregação in Mathematics Applied to Economics and Management (MAEG) from Universidade de Lisboa (2014). Her academic career spans over three decades, with roles including Coordinator of the Scientific Area of Econometrics, President of CEMAPRE, and member of various academic committees. Her research focuses on microeconometrics, spatial econometrics, panel data analysis, and semiparametric methods, with applications to labor economics, gender disparities, international trade, and regional development. Notable projects include work on the spatial distribution of FDI spillovers in Portugal and the gender pay gap’s impact on income and poverty. She has supervised over 40 master’s and 2 PhD students. Proença has published extensively in journals like *Applied Economics*, *Computational Statistics*, and *Empirical Economics*. Her recent work addresses topics such as the effects of eliminating the gender pay gap and the evaluation of spatial econometric models in precision agriculture. She is actively involved in projects funded by Horizon2020 and FCT, focusing on gender equity in research and regional economic accessibility. In teaching, she instructs econometrics courses across undergraduate, master’s, and doctoral programs. Her professional service includes roles on the ISEG School Board and leadership in research units like CEMAPRE.

Fredrik Georgssonمشاهده پروفایل

مدرس ارشد

• Medical Image Processing
• Computer Aided Mammography
• Fractal Analysis
• +۳ مورد دیگر

Fredrik Georgsson is a Senior Lecturer and Program Director at the Department of Computing Science, Umeå University. His roles include teaching, research leadership, and academic administration. He holds a PhD in Computing Science (2001) and has been at Umeå University since 1996, progressing from PhD student to his current Senior Lecturer position. Education: PhD in Computing Science, Umeå University (2001) Licentiate of Philosophy, Umeå University (1999) MSc in Computing Science and Engineering, Umeå University (1996) Research Interests: Medical Image Processing (e.g., mammography, tumor analysis) Fractal analysis of medical images Autonomous vehicle systems Pattern recognition and computer vision Teaching & Advising: Responsible for courses like Medical Image Processing and Computational Intelligence Supervised over 15 Master's and PhD students in medical imaging and related fields Developed curricula for advanced medical image analysis courses Grants & Projects: Lead developer of autonomous forest machinery path-tracking systems Recipient of multiple research grants for medical imaging projects Labs & Teams: Principal investigator in the Medical Imaging Analysis Lab and Autonomous Systems Group at Umeå University.

Jelmer Wolterinkمشاهده پروفایل

استادیار

• Machine Learning
• Medical Image Analysis
• Deep Learning
• +۷ مورد دیگر

Dr. Jelmer Wolterink is an Assistant Professor in the Department of Systems, Analysis and Computational Science (SACS) within the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente. He is a member of the Mathematics of Imaging & AI (MIA) group and contributes to the Digital Society Institute and TechMed Centre. His research bridges artificial intelligence and medical imaging, with a strong focus on cardiovascular disease analysis. His educational background includes a Master's in Artificial Intelligence from Radboud University and a second Master's in Mathematical Sciences and Scientific Computing from Utrecht University. He earned his PhD in 2017 from Utrecht University (UMC Utrecht) on machine learning for coronary artery calcification analysis. Dr. Wolterink's research interests lie in machine learning for medical image analysis , particularly deep learning , generative models , and geometric deep learning . His work aims to extract more information from medical images (CT, MRI, ultrasound) to improve diagnosis and enable personalized treatment in conditions like abdominal aortic aneurysm. He develops AI methods to predict aneurysm growth and rupture risk beyond simple diameter measurements, using biomechanical and morphological features. He has secured significant research funding, including an NWO Veni grant and multiple project grants, and is part of the 4TU Precision Medicine program. His work enables better use of existing clinical images for secondary analysis, such as detecting aortic data in gallstone CT scans. NWO Veni Grant (2020) – €250,000 TURBO Program Grant – €80,000 Pioneers in Health Care Grant – €60,000 Dr. Wolterink teaches the course Deep Learning for Medical Imaging Analysis in the Applied Mathematics master’s track Artificial Intelligence for Health . He supervises Technical Medicine students on internships at hospitals, focusing on AI applications in vascular surgery, orthopedics, and gastroenterology. These collaborations foster innovation and clinical partnerships. He is actively involved in research teams within the MIA group and the broader 4TU network, contributing to interdisciplinary efforts in precision medicine and AI-driven healthcare transformation.

• Mathematical Analysis
• Calculus of Variations
• Homogenization Theory
• +۳ مورد دیگر

Giuliano Gargiulo is a Researcher in Mathematical Analysis (MAT/05) at the Department of Science and Technology (DST) of the University of Sannio, Italy. His academic career spans over two decades with numerous publications in mathematical analysis, particularly in calculus of variations, homogenization theory, and fracture mechanics. Dr. Gargiulo's research interests focus on: Calculus of Variations and Homogenization Theory Mathematical aspects of Fracture Mechanics SBD spaces and lower semicontinuity problems Dimension reduction for thin structures Applications to continuum mechanics and materials science His publication record shows consistent research output from 1995 to 2021, with recent work focusing on multiscale homogenization in Orlicz-Sobolev settings and dimension reduction problems. His research bridges pure mathematical analysis with applications in materials science and physics, including studies on Josephson junctions and educational tools for differential equations. Dr. Gargiulo has collaborated with researchers across multiple institutions, with international publications spanning Europe, Asia, and the Americas. His work appears in reputable mathematical journals covering analysis, partial differential equations, and applied mathematics.

• Games Design
• Interactive Storytelling
• Virtual Reality
• +۴ مورد دیگر

Dr. Huiwen Zhao is a Senior Lecturer in Games Design at Bournemouth University , with a focus on interactive storytelling, virtual reality (VR), and mass customization. Her work bridges user experience (UX) research with practical game design and VR applications. Contact: hzhao@bournemouth.ac.uk Education: PhD in Emotion-driven Interactive Storytelling (China Scholarship Council, 2012) Research Interests: Dr. Zhao’s research centers on creating immersive, emotion-aware digital experiences through games design and VR. Her work explores consumer behavior in mass customization, affective storytelling techniques, and innovative applications of VR for education and training. She also investigates how digital narratives can be optimized for user engagement and educational impact. Grants & Projects: She has led or contributed to projects funded by the EU Horizon 2020 MSCA, National Social Science Foundation of China, and Bournemouth University’s Centre for Excellence in Media Practice. Topics include affective storytelling, VR training simulators, and interactive video design. Collaborations: Dr. Zhao collaborates with researchers like Dr. L. McLoughlin, Prof. A. Pasko, and Dr. V. Hulusic. She co-developed the StoryPlaces Authoring Tool for locative storytelling and has published extensively on emotion-driven design and 3D customization toolkits.

Lindsey Kuperمشاهده پروفایل

استادیار

• programming languages
• distributed computing
• concurrency
• +۵ مورد دیگر

Lindsey Kuper is an Assistant Professor in the Computer Science and Engineering Department at the Baskin School of Engineering, University of California, Santa Cruz. Her research focuses on programming languages, distributed systems, concurrency, parallelism, and software verification. Ph.D., Indiana University (2015) Research interests include: Programming-language-based approaches for concurrent/distributed systems Library-level choreographic programming (Haskell, Rust, TypeScript) Dependently-typed diagrams for inductive reasoning Causal message delivery with refinement types Key research projects: 2025: KameraBag (Kubernetes observability) 2024: Sender-side causal message protocol 2023: HasChor (Haskell choreographic programming) 2022: Liquid Haskell causal broadcast verification Scientific awards: NSF CAREER Award Stellar Development Foundation Grant Google Faculty Research Award Amazon Web Services gift Zulip in-kind sponsorship Teaching history includes courses on: Foundations of Programming Languages (CSE114A) Distributed Systems (CSE232/CSE138) SMT Solving and Solver-Aided Systems Programming Abstractions (Python) Service contributions: Co-founded !!Con and !!Con West Chaired: Choreographic Programming 2024, PLMW workshops, DSLDI, OBT ICFP/OOPSLA/PLDI program committee member Research group: CASL Group (Concurrency and Safety Lab) Languages, Systems, and Data (LSD) Lab Current members: 6 PhD students