جست‌وجوی استاد و پژوهشگر

• Mathematics Education
• Geometry
• Algebra
• +۳ مورد دیگر

Martin Kindt is a Lecturer in Mathematics Education at the Freudenthal Institute, Faculty of Science, Utrecht University. He has maintained an active presence in mathematics education research and practice since at least 2001, with particular focus on geometry, algebra, and historical perspectives in mathematics teaching. His research interests include: Geometry and spatial reasoning, particularly symmetry and regularity in plane and space Algebraic thinking and conceptual understanding pathways History of mathematics and its application to modern educational practices Integration of geometry and algebra in teaching frameworks Real-world mathematical applications, especially in engineering contexts Curriculum development for secondary mathematics education Kindt's scholarly work demonstrates a distinctive approach that connects historical mathematical developments with contemporary educational challenges. His presentations on figures like Albrecht Dürer and ancient systems like Babylonian mathematics reveal a consistent theme of using historical context to illuminate modern teaching practices. The progression of his work shows increasing sophistication in connecting geometric visualization with algebraic structures, as evidenced by titles like 'Geometry and Algebra, a Happy Marriage' and 'Regularity in Plane and Space.' His international engagement is notable, with presentations delivered across multiple continents including Asia, South America, and Europe. This global perspective informs his contributions to the field of mathematics education, particularly through the lens of Realistic Mathematics Education, which originated in the Netherlands.

Chuang Ganمشاهده پروفایل

استادیار

• Computer Vision
• Graph Deep Learning
• Multimodal Learning
• +۵ مورد دیگر

Chuang Gan is a distinguished researcher holding dual positions as a Principal Research Staff Member at the MIT-IBM Watson AI Lab and an Assistant Professor at the University of Massachusetts Amherst. His work bridges academic research and industrial applications in artificial intelligence, with particular focus on advancing the frontiers of computer vision and multimodal learning systems. Dr. Gan's research interests span multiple interconnected domains within artificial intelligence. He specializes in video understanding, with deep expertise in representation learning, neural-symbolic visual reasoning, audio-visual scene analysis, and embodied intelligence. His work frequently integrates graph deep learning techniques with neuro-symbolic approaches to create more interpretable and robust AI systems. The recurring themes across his research portfolio include developing models that can understand physical dynamics from visual inputs, creating systems capable of embodied reasoning, and building bridges between symbolic and neural approaches to artificial intelligence. His publications reveal a strong trend toward increasingly sophisticated multimodal systems that integrate visual, auditory, and linguistic information. Over time, his work has evolved from basic video understanding tasks to complex embodied reasoning systems capable of physical simulation, 3D scene understanding, and multi-agent collaboration. A notable pattern is the progression from analyzing static scenes to understanding dynamic physical interactions and embodied agent behaviors in increasingly complex environments. Microsoft Fellowship Baidu Fellowship Dr. Gan's research has received significant recognition from major technology companies through prestigious fellowships and has been widely covered by leading media outlets including CNN, BBC, The New York Times, WIRED, Forbes, and MIT Tech Review. His work at the MIT-IBM Watson AI Lab provides him with access to substantial resources for cutting-edge AI research, while his academic position enables him to train the next generation of AI researchers. His collaborations with prominent researchers like Antonio Torralba demonstrate his integration within the top echelons of the computer vision and AI research community. At the MIT-IBM Watson AI Lab, Dr. Gan leads research initiatives focused on advancing video understanding and embodied intelligence. His work contributes to the lab's mission of developing AI systems that can perceive, reason about, and interact with the physical world in more human-like ways. His research group likely focuses on developing novel architectures for multimodal learning, creating benchmarks for physical reasoning, and building systems that can transfer knowledge between simulation and real-world environments.

• Mathematics Education
• Early Childhood Mathematics
• Teacher Education
• +۴ مورد دیگر

Jill Cheeseman serves as an Adjunct Senior Lecturer in Monash University's School of Curriculum Teaching & Inclusive Education, leveraging extensive prior experience as a primary school teacher and teacher-educator across Australia and internationally. Her academic role centers on mathematics education with specialization in early childhood learning environments and teacher-student interaction dynamics. Her research investigates how children develop mathematical understanding and how educators can effectively challenge learners' thinking through cognitively demanding tasks. Key focus areas include multiplicative reasoning, mass measurement concepts, teacher leadership in mathematics, and strategies for maintaining student persistence during challenging activities. This work builds on her foundational PhD research examining teacher behaviors that stimulate deep mathematical engagement in young children. Analysis of her recent publications (2020-2025) reveals consistent emphasis on teacher leadership practices, early division concepts, and task design principles that promote equitable mathematical participation. Her collaborative approach integrates classroom-based research with international partnerships to address persistent challenges in mathematics education. Scientific recognition includes: MERGA Research Award (2011) for the Early Numeracy Research Project team She has secured significant research funding including an ARC Discovery grant (2011-2014) on teacher expectations and student persistence, and current projects investigating early mass concepts. These initiatives involve collaborations with leading researchers like Peter Sullivan, Doug Clarke, and Jim Middleton across Australian and U.S. institutions. Dr. Cheeseman's work manifests through active classroom engagement in Monash courses (EDF1307, EDF3301, EDF2323, EDF6402) and ongoing contributions to the Mathematics Education Research Group of Australasia, maintaining strong connections between research, teacher education, and classroom practice.

• Veterinary Pathology
• Tumour Biology
• Immunohistochemistry
• +۵ مورد دیگر

Lorenzo Ressel serves as Lecturer in Veterinary Pathology at the University of Liverpool, where he has been a core faculty member since 2011. A diplomate of the European College of Veterinary Pathologists (DipECVP) since 2015 and Fellow of the Higher Education Academy (FHEA), he directs the Immunohistochemistry and Electron Microscopy Services while teaching anatomic pathology with emphasis on neoplasia. His educational foundation includes a veterinary degree (2005) and PhD (2009) from the University of Pisa, where his dissertation explored PTEN protein expression in canine and feline mammary tumours. This early work established his expertise in comparative tumour biology that continues to inform his research. Professor Ressel's research spans veterinary pathology with dual emphases: traditional diagnostic pathology (particularly immunohistochemistry for tumour grading) and cutting-edge computational approaches. His recent publications reveal a strategic pivot toward integrating artificial intelligence and natural language processing into veterinary diagnostics, while maintaining active work in forensic pathology and regenerative medicine. This interdisciplinary focus positions him at the forefront of digital transformation in veterinary medicine. Analysis of his 2025 publications shows strong momentum in AI applications, with multiple papers establishing methodological frameworks for computational pathology. His work bridges species-specific veterinary challenges with broader diagnostic innovation, particularly in image analysis standardization and 3D visualization techniques for both educational and diagnostic purposes. Eusropean Society of Veterinary Pathology (ESVP) Oral presentation Award (2013) European Society of Veterinary Oncology (ESVONC) Junior Research Award (2009) Professor Ressel actively supervises postgraduate research through multiple funded projects including Kidney Research UK studies on regenerative therapies and Horserace Betting Levy Board investigations into equine pulmonary diseases. His grant portfolio demonstrates successful translation of basic research into clinical applications, with particular strength in securing competitive European and UK funding. The Immunohistochemistry Service he developed serves as a critical nexus between diagnostic practice and research innovation. As head of the Immunohistochemistry and Electron Microscopy Services, Professor Ressel oversees integrated diagnostic and research operations that handle hundreds of cases annually. These services provide the foundation for his methodological innovations while supporting the University of Liverpool's veterinary hospital and research community, creating a dynamic environment where diagnostic challenges directly inform research priorities.

Fabrice Lamarcheمشاهده پروفایل

دانشیار

• Virtual Humans
• Crowd Simulation
• Motion Planning
• +۵ مورد دیگر

Fabrice Lamarche serves as an Associate Professor at Université de Rennes 1 within the ESIR School of Engineering, while maintaining dual affiliation with the MimeTIC research team at IRISA / INRIA Rennes. His academic career spans uninterrupted service since 2004, evolving from Assistant Professor roles at IFSIC (2003-2009) to current positions at ESIR. As co-founder of Golaem (2009), he bridges academic research with commercial application in crowd simulation technology. His institutional journey includes sequential membership in SIAMES (2004-2006), Bunraku (2007-2011), and MimeTIC (2011-present) research teams at INRIA. Lamarche earned his PhD in Computer Sciences from Université de Rennes 1 in 2003 with thesis work on virtual human autonomy. His educational foundation includes a Master of Computer Sciences specializing in Computer Graphics and AI (1999-2000), a Master of Engineering from INSA de Rennes (1997-2000), and a Technical degree from IUT de Limoges (1995-1997). His research program centers on virtual human behavior modeling with emphasis on decision-making systems, path planning under environmental constraints, and crowd simulation architectures. Key innovations include TopoPlan for human-scale navigation and frameworks integrating high-level task scheduling with low-level motion planning. This work addresses fundamental challenges in creating autonomous virtual characters capable of navigating complex 3D environments while exhibiting realistic behaviors, with applications spanning virtual reality, gaming, and simulation-based training systems. Publication analysis reveals consistent output from 2001-2014, evolving from foundational behavioral animation (2001-2004) to sophisticated crowd simulation systems (2013-2014). A notable trajectory shows increasing integration of cognitive modeling with motion planning, alongside exploration of Brain-Computer Interfaces for virtual navigation. Recent work demonstrates particular strength in semantic decomposition of urban environments and time-space constrained task scheduling. His scientific contributions have earned significant recognition: Rennes city medal (2009) for research excellence Second prize at Deutsch Telekom Awards (FMX 2008) for TopoPlan/MKM integration As an active researcher and educator, Lamarche advises students through Université de Rennes 1 while leveraging INRIA resources and Golaem industry partnerships. His publication record indicates sustained grant funding, particularly through INRIA channels, with collaborative projects extending to neuroscience applications via Brain-Computer Interface research. The MimeTIC team affiliation provides infrastructure for multimodal interaction research in complex virtual environments. Lamarche's laboratory work through MimeTIC focuses on developing practical implementations of virtual human autonomy systems. His research group maintains strong industry connections via Golaem, which commercializes crowd simulation technology. Current efforts emphasize semantic understanding of virtual urban spaces and robust path planning under dynamic constraints, building on foundational work in topological navigation and behavioral decision systems.